Journal articles: 'Analyse image'

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Akoum, Alhussain, Samia Bahlak, and Nagham Abou Daher. "Image Forgery Analyse and Detection." International Journal of Computer Science and Engineering 8, no. 8 (August 25, 2021): 8–12. http://dx.doi.org/10.14445/23488387/ijcse-v8i8p102.

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Bartels, U., W. Friedmann, C. Minguillon, and U. Büscher. "Image-zytophotometrische DNA-Analyse beim Mammakarzinom." Archives of Gynecology and Obstetrics 254, no. 1-4 (December 1993): 822–23. http://dx.doi.org/10.1007/bf02266191.

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Bell, Peter, and Leonardo Impett. "Ikonographie und Interaktion. Computergestützte Analyse von Posen in Bildern der Heilsgeschichte." Das Mittelalter 24, no. 1 (July 11, 2019): 31–53. http://dx.doi.org/10.1515/mial-2019-0004.

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Abstract The last few years have seen an explosion of medieval images in digital form, chiefly as a result of photo-library and manuscript digitisation projects. An entire corpus of images, even selected solely by scene or iconography, becomes an unwieldy object of study by traditional art-historical means. This is even more the case for medieval images, where authorship and dating are often cloudy and unclear, and the image itself is in many cases the first resource for scholarly inquiry.We take the digital image – in particular, the digital image of the body – as our object of study in a wide-ranging computationally-augmented reading of an image-corpus; ours is made up of thousands of depictions of the ‘Annunciation’ and ‘Baptism’, selected not only for their primacy in Christian art but for their dialogical interaction. Our corpus of 6,564 ‘Annunciations’ and 883 ‘Baptisms’, whilst not necessarily representative in density, includes a wide range of stylistic, theological and historical tendencies.We computationally extract not only body images but poses, gestures and interactions. Such a range of gestures allows for a morphological treatment of bodily motifs, whose multi-dimensional, quantitative nature allows us to complicate and problematise iconographic taxonomies, populating the spaces between categories. Finally, our gestural manifolds provide a morphological pointer to dissecting the microtemporalities of the scenes, and their relative dynamics and inconsistencies.

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Dany, L., T. Apostolidis, P. Cannone, E. Suarez-Diaz, and F. Filipetto. "Image corporelle et cancer: une analyse psychosociale." Psycho-Oncologie 3, no. 2 (June 2009): 101–17. http://dx.doi.org/10.1007/s11839-009-0128-y.

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Padma Usha M, Kannan G, Ramamoorthy M, Sharmila M, Huzaifa Anjum G.A, and Hairunnisha M.S.H. "Multimodal Brain Image Fusion using Graph Intelligence Method." International Journal of Research in Pharmaceutical Sciences 11, no. 2 (June 22, 2020): 2713–24. http://dx.doi.org/10.26452/ijrps.v11i2.2293.

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Image fusion plays a vital role for enhancing the quality of images in medical applications. It is known that CT images of brain shows the details of the bone structure and MRI images of brain shows the details of the soft tissue. The Objective of this research is to fuse CT (Computed Tomography) and MRI(Magnetic Resonance Imaging) of normal brain images and tumor affected brain images and to find out structural similarity(SSIM) of the fused image. Axial slice of normal brain and brain tumor images are taken for image fusion. Totally, 24 brain images has been taken out of which 6 pairs are normal brain images and another 6 pairs are tumor affected brain images. Techniques used are Graph-cut method for segmentation, Maximum method for fusion and Swarm Intelligence method for optimization. The proposed fusion method increases SSIM (Structural Similarity) when compared to conventional method of fusion. Tumor size in the fused image is also extracted and this fused image is helpful for doctors to analyse the post radio therapy patient or operated patient whether any tumor residues still exist. Also this method minimises the number of pixels and increases the information content in a single fused image. This technique aids the physician to analyse complementary details in a single image.

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Gudmann, András, Nándor Csikós, Péter Szilassi, and László Mucsi. "Improvement in Satellite Image-Based Land Cover Classification with Landscape Metrics." Remote Sensing 12, no. 21 (October 31, 2020): 3580. http://dx.doi.org/10.3390/rs12213580.

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The use of an object-based image analysis (OBIA) method has recently become quite common for classifying high-resolution remote-sensed images. However, despite OBIA’s segmentation being equally useful for analysing medium-resolution images, it is not used for them as often. This study aims to analyse the effect of landscape metrics that have not yet been used in image classification to provide additional information for land cover mapping to improve the thematic accuracy of satellite image-based land cover mapping. To this end, multispectral satellite images taken by Landsat 8 Operational Land Imager (OLI) and Sentinel-2 Multispectral Instrument (MSI) during three different seasons in 2017 were analysed. The images were segmented, and based on these segments, four patch-level landscape metrics (mean patch size, total edge, mean shape index and fractal dimension) were calculated. A random forest classifier was applied for classification, and the Coordination of Information on the Environment Land Cover (CLC) 2018 database was used as reference data. According to the results, landscape metrics both with and without segmentation can significantly improve the overall accuracy of the classification over classification based on spectral values. The highest overall accuracy was achieved using all data (i.e., spectral values, segmentation, and metrics).

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Gururaj, Mirji Sairaj, and A. Arockia Selvakumar. "Image Processing Techniques to Analyse a 3D Model." Applied Mechanics and Materials 787 (August 2015): 922–26. http://dx.doi.org/10.4028/www.scientific.net/amm.787.922.

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The Image processing technique incorporates human perception and intelligence which makes this field more interesting to the research community. The edge detection process is the most important step in image recognition system. In this paper a simple three dimensional model is created by taking the best edge detected image followed by comparison with various edge detection techniques using Labview software. HereCatia model of spur gear isdrawn by observing and analysing best suited edge detected image in order to make the design more precise in edges and geometry and also to make object recognition simple and further scope is given to design a Catia model using dimensional parameters with the help of vision assistant tool.

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Upadhyaya, Vivek, and Mohammad Salim. "To Analyse the Effect of Relaxation Type on Magnetic Resonance Image Compression Using Compressive Sensing." International Journal of Online and Biomedical Engineering (iJOE) 17, no. 04 (April 6, 2021): 21. http://dx.doi.org/10.3991/ijoe.v17i04.20759.

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Medical Imaging and scanning technologies are used to provide better resolution of body and tissues. To achieve a better quality Magnetic Resonance (MR) image with a minimum duration of processing time is a tedious task. So our purpose in this paper is to find out a solution that can minimize the reconstruction time of an MRI signal. Compressive sensing can be used to accelerate Magnetic Resonance Image (MRI) acquisition by acquiring fewer data through the under-sampling of k-space, so it can be used to minimize the time. But according to the relaxation time, we can further classify the MRI signal into T1, T2, and Proton Density (PD) weighted images. These weighted images represent different signal intensities for different types of tissues and body parts. It also affects the reconstruction process conducted by using the Compressive Sensing Approach. This study is based on finding out the effect of T1, T2, and Proton Density (PD) weighted images on the reconstruction process as well as various image quality parameters like MSE, PSNR, & SSIM also calculated to analyze this effect. Meanwhile, we can analyze how many samples are enough to reconstruct the MR image so the problem associated with time and scanning speed can be reduced up to an extent. In this paper, we got the Structural Similarity Index Measure (SSIM) value up to 0.89 & PSNR value 37.83451 dB at an 85 % compression ratio for the T2 weighted image.

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Arumugam, Shankar, and Kannammal Annadurai. "An Efficient Machine Learning Based Image Encryption Scheme for Medical Image Security." Journal of Medical Imaging and Health Informatics 11, no. 6 (June 1, 2021): 1533–40. http://dx.doi.org/10.1166/jmihi.2021.3470.

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Medical images are very important in most of the application than any other images. In real time applications like telemedicine application, communication of medical image through open access needs protection as well as security at high level. Many imaging information has its own unique features which are so difficult to analyse and make decision to identify necessary techniques for protecting confidential image of unauthenticated access, Utmost all the existing encryption algorithms are mainly concentrating on textual data, but for multimedia data like images, it is not suitable. The main contribution done in this work is for ensuring increased security level over medical images regardless of presence of noises. In this algorithm, DNA subsequence operations combining with the use of improved Combined Linear Congruential Generator (C-LCG) were used for encryption of information. This paper discuss the idea of the improvement of safe and secure techniques using machine learning which is justified by the entropy value and correlation among adjacent pixels with performance parameters. The original image was scrambled using Combined Linear Congruential Generator with Bit rotation operation (BRO) and then image is transformed by effective encryption method using DNA subsequence operations. The proposed scheme discloses the correlation between pixel and entropy. Experimentation results showed that correlation among pixels is reduced while maximizing entropy. Number of Pixel Change Rate (NPCR) and Peak signal to noise (PSNR) ratio were also been analysed. In proposed algorithm, maximum NPCR values is achieved which shows the scattering of pixels in Encrypted image is high. PSNR shows a better encryption quality with lower the values.

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Et al., A. Mohanarathinam. "AN ANALYSIS ON IMAGE ENCRYPTION FOR SECURED TRANSMISSION OF BIOMEDICAL APPLICATIONS." INFORMATION TECHNOLOGY IN INDUSTRY 9, no. 1 (February 12, 2021): 01–11. http://dx.doi.org/10.17762/itii.v9i1.82.

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Digital images are very popularly used for communications over the internet. Embedded information in the digital image has to be securely transmitted without any modification in the image. The biomedical telemedicine gains significant importance in information transmission and with increasing popularity with Tele-ophthalmology, requirement of medical data confidentiality and privacy also increases for data storage and secure transformation. The objective is to analyse the bioimage encryption algorithms which provides security and privacy to the bioimages. In this paper retinal fundus image online available dataset have used. The proposed work is analysed by considering, three performance parameters such as PSNR, MSE and CR. The two different encryption algorithms namely block-based perceptual encryption (BBPE) and advanced encryption standard (AES) algorithm along with arithmetic compression have tested . The proposed work results tested on standard test images and retinal fundus images shows that the BBPE method attains PSNR of 27.58db , MSE of 3.20e+03 and CR of 4.27 for standard test images and 13.35db, 1.4046e+04 and 7.28 respectively for medical HRF images. The BBPE algorithm can be used in tele-ophthalmology and telemedicine applications.

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Smith, N. D., C. N. Mitchell, and C. J. Budd. "Image-model coupling: a simple information theoretic perspective for image sequences." Nonlinear Processes in Geophysics 16, no. 2 (March 20, 2009): 197–210. http://dx.doi.org/10.5194/npg-16-197-2009.

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Abstract. Images are widely used to visualise physical processes. Models may be developed which attempt to replicate those processes and their effects. The technique of coupling model output to images, which is here called "image-model coupling", may be used to help understand the underlying physical processes, and better understand the limitations of the models. An information theoretic framework is presented for image-model coupling in the context of communication along a discrete channel. The physical process may be regarded as a transmitter of images and the model as part of a receiver which decodes or recognises those images. Image-model coupling may therefore be interpreted as image recognition. Of interest are physical processes which exhibit "memory". The response of such a system is not only dependent on the current values of driver variables, but also on the recent history of drivers and/or system description. Examples of such systems in geophysics include the ionosphere and Earth's climate. The discrete channel model is used to help derive expressions for matching images and model output, and help analyse the coupling.

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Kocaman, S., I. Yalcin, and M. Guler. "RADIOMETRIC AND GEOMETRIC ACCURACY ANALYSIS OF RASAT PAN IMAGERY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (June 3, 2016): 349–53. http://dx.doi.org/10.5194/isprsarchives-xli-b1-349-2016.

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RASAT is the second Turkish Earth Observation satellite which was launched in 2011. It operates with pushbroom principle and acquires panchromatic and MS images with 7.5 m and 15 m resolutions, respectively. The swath width of the sensor is 30 km. The main aim of this study is to analyse the radiometric and geometric quality of RASAT images. A systematic validation approach for the RASAT imagery and its products is being applied. RASAT image pair acquired over Kesan city in Edirne province of Turkey are used for the investigations. The raw RASAT data (L0) are processed by Turkish Space Agency (TUBITAK-UZAY) to produce higher level image products. The image products include radiometrically processed (L1), georeferenced (L2) and orthorectified (L3) data, as well as pansharpened images. The image quality assessments include visual inspections, noise, MTF and histogram analyses. The geometric accuracy assessment results are only preliminary and the assessment is performed using the raw images. The geometric accuracy potential is investigated using 3D ground control points extracted from road intersections, which were measured manually in stereo from aerial images with 20 cm resolution and accuracy. The initial results of the study, which were performed using one RASAT panchromatic image pair, are presented in this paper.

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Kocaman, S., I. Yalcin, and M. Guler. "RADIOMETRIC AND GEOMETRIC ACCURACY ANALYSIS OF RASAT PAN IMAGERY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (June 3, 2016): 349–53. http://dx.doi.org/10.5194/isprs-archives-xli-b1-349-2016.

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RASAT is the second Turkish Earth Observation satellite which was launched in 2011. It operates with pushbroom principle and acquires panchromatic and MS images with 7.5 m and 15 m resolutions, respectively. The swath width of the sensor is 30 km. The main aim of this study is to analyse the radiometric and geometric quality of RASAT images. A systematic validation approach for the RASAT imagery and its products is being applied. RASAT image pair acquired over Kesan city in Edirne province of Turkey are used for the investigations. The raw RASAT data (L0) are processed by Turkish Space Agency (TUBITAK-UZAY) to produce higher level image products. The image products include radiometrically processed (L1), georeferenced (L2) and orthorectified (L3) data, as well as pansharpened images. The image quality assessments include visual inspections, noise, MTF and histogram analyses. The geometric accuracy assessment results are only preliminary and the assessment is performed using the raw images. The geometric accuracy potential is investigated using 3D ground control points extracted from road intersections, which were measured manually in stereo from aerial images with 20 cm resolution and accuracy. The initial results of the study, which were performed using one RASAT panchromatic image pair, are presented in this paper.

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Renukalatha, S., and K. V. Suresh. "A REVIEW ON BIOMEDICAL IMAGE ANALYSIS." Biomedical Engineering: Applications, Basis and Communications 30, no. 04 (August 2018): 1830001. http://dx.doi.org/10.4015/s1016237218300018.

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Bio-medical image analysis is an interdisciplinary field which includes: biology, physics, medicine and engineering. It deals with application of image processing techniques to biological or medical problems. Medical images to be analyzed contain a lot of information regarding the anatomical structure under investigation to reveal valid diagnosis and thereby helping doctors to choose adequate therapy. Doctors usually analyse these medical images manually through visual interpretation. But visual analysis of these images by human observers is limited due to variation in interpersonal interpretations, fatigue errors, surrounding disturbances and moreover this kind of analysis is purely subjective. On the other hand, automated analysis of these images using computers with suitable techniques favours the objective analysis by an expert and thereby improving the diagnostic confidence and accuracy of analysis. This survey is a consolidation of the exhaustive literature records related to biomedical image analysis.

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Baniukiewicz, Piotr. "Automatic segmentation of radiographic images in industrial applications." Archives of Electrical Engineering 60, no. 3 (September 1, 2011): 349–56. http://dx.doi.org/10.2478/v10171-011-0030-7.

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Automatic segmentation of radiographic images in industrial applications A technology that utilizes penetrating rays is one of the oldest nondestructive testing methods. Nowadays, the process of radiogram analysis is performed by qualified human operators and automatic systems are still under development. In this work we present advanced algorithms for automatic segmentation of radiographic images of welded joints. The goal of segmentation of a radiogram is to change and simplify representation of the image into a form that is more meaningful and easier to analyse automatically. The radiogram is divided into parts containing the weld line, image quality indicators, lead characters, and possible defects. Then, each part is analysed separately by specialized algorithms within the framework of the Intelligent System for Radiogram Analysis.

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Lim, P. C., T. Kim, S. I. Na, K. D. Lee, H. Y. Ahn, and J. Hong. "ANALYSIS OF UAV IMAGE QUALITY USING EDGE ANALYSIS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4 (September 19, 2018): 359–64. http://dx.doi.org/10.5194/isprs-archives-xlii-4-359-2018.

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Abstract. UAVs (Unmanned aerial Vehicles) can acquire images easily without large cost. For this reason, use of UAV is spreading to diverse fields such as orthoimages and DEM/DSM production. The spatial resolution of images is usually expressed as a GSD (Ground Sampling Distance). The GSD from UAV has higher performance than other platforms such as satellites and aircraft because it shoot at low altitude. However, blurring and noise may occur on UAV images due to the weather and the stability of UAV. However, since the GSD from UAV cannot sufficiently meet the spatial resolving power of the actual image system, a criterion for determining the spatial resolution of image is needed. Therefore we emphasize that the quality of the image needs to be analysed. Actual performance indicators such as GRD (Ground Resolved Distance) and NIIRS (National Image Interpretability Rating Scales), which can be measured through image analysis, are representative examples of image quality interpretation. It is possible to extract NIIRS form image quality related parameters such as MTF (Modulation Transfer Function), RER (Relative Edge Response) and SNR (Signal to Noise Ratio). In this paper, we aim to apply the Edge analysis method to UAV and to analyse the result. The analysis result showed that while GSD and NIIRS were highly dependent to imaging altitude, GRD and image sharpness showed optimal altitude ranges. The exact optimal range varied between images taken at different weather conditions. While we need a further study, this may indicate that edge analysis may provide an optimal operational altitude range suitable for the sensors.

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Grgić, Mislav, Sonja Grgić, and Branka Zovko-Cihlar. "DCTlab: Educational Software for Still Image Compression and its Application in a Digital Television Course." International Journal of Electrical Engineering & Education 38, no. 3 (July 2001): 187–98. http://dx.doi.org/10.7227/ijeee.38.3.1.

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Current standards for the compression of still and moving images use Discrete Cosine Transform (DCT) to remove spatial redundancy in images. Students specialising in image and video system engineering need to know why DCT is important in their field of interest and to understand the influence of DCT-based image compression on picture quality. Therefore, we have developed educational software, called DCTlab, that helps students to analyse DCT application in still image compression systems. This paper describes software characteristics, its application in a digital television course and learning outcomes.

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Janquart, Justin, Otto A. Hannuksela, K. Haris, and Chris Van Den Broeck. "A fast and precise methodology to search for and analyse strongly lensed gravitational-wave events." Monthly Notices of the Royal Astronomical Society 506, no. 4 (July 15, 2021): 5430–38. http://dx.doi.org/10.1093/mnras/stab1991.

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ABSTRACT Gravitational waves, like light, can be gravitationally lensed by massive astrophysical objects such as galaxies and galaxy clusters. Strong gravitational-wave lensing, forecasted at a reasonable rate in ground-based gravitational-wave detectors such as Advanced LIGO, Advanced Virgo, and KAGRA, produces multiple images separated in time by minutes to months. These images appear as repeated events in the detectors: gravitational-wave pairs, triplets, or quadruplets with identical frequency evolution originating from the same sky location. To search for these images, we need to, in principle, analyse all viable combinations of individual events present in the gravitational-wave catalogues. An increasingly pressing problem is that the number of candidate pairs that we need to analyse grows rapidly with the increasing number of single-event detections. At design sensitivity, one may have as many as $\mathcal {O}(10^5)$ event pairs to consider. To meet the ever-increasing computational requirements, we develop a fast and precise Bayesian methodology to analyse strongly lensed event pairs, enabling future searches. The methodology works by replacing the prior used in the analysis of one strongly lensed gravitational-wave image by the posterior of another image; the computation is then further sped up by a pre-computed lookup table. We demonstrate how the methodology can be applied to any number of lensed images, enabling fast studies of strongly lensed quadruplets.

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Manikantan, K. "Analyse And Overview on Digital Image Tampering Detection Using Matlab." International Journal of Computer Sciences and Engineering 6, no. 8 (August 31, 2018): 902–6. http://dx.doi.org/10.26438/ijcse/v6i8.902906.

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Dubé, Raymonde, Gabriel Goyette, Monique Lebrun, and Marie-Thérèse Vachon. "Image mentale et apprentissage de l’orthographe lexicale." Articles 17, no. 2 (November 16, 2009): 191–205. http://dx.doi.org/10.7202/900695ar.

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Cette étude analyse le rôle de la mémoire visuelle et, plus particulièrement, le recours à l’image mentale dans l’apprentissage de l’orthographe lexicale. Pour ce faire, on a proposé à des écoliers de première et de deuxième années une série de tests sollicitant l’habileté à analyser et à reproduire des images mentales à partir de dessins et de mots. Les données quantitatives ne fournissent pas de résultats toujours significatifs; par contre, l’entrevue montre un développement des habilités à utiliser l’image mentale et à mettre en branle la métacognition.

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Pisters, Patricia. "Flashforward: The Future is Now." Deleuze Studies 5, supplement (December 2011): 98–115. http://dx.doi.org/10.3366/dls.2011.0039.

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In The Future of the Image (2007) Jacques Rancière states that the end of images is behind us. He argues for an aesthetics of the image that acknowledges the continuing power of images as educating documentations of traces of history, as directly affecting interruptions, and as open-to-combining signs of the visible and the sayable ad infinitum. But does Rancière's claim also concern the future of cinema? His cinematic references, in a Deleuzian sense, are mostly to modern time-images. Is the future of film indeed a form of the time-image, or has the ‘heart’ of cinema moved beyond this image-type? This paper proposes to look at a third category of cinematographic images, based in the third synthesis of time as developed by Deleuze in Difference and Repetition. This filmic image, that could be called the neuro-image, is connected to the impure regime of images typical for the database logic of the digital age. By comparing Alain Resnais's Hiroshima Mon Amour (1959) to the television series FlashForward (2009) , I will analyse the temporal operations of the image of the time-image to these images of a new regime of images, the image of and from the future. 1

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Giancane, Simone, Riccardo Nobile, Francesco W. Panella, and Vito Dattoma. "Damage Evolution of Composite Laminates with Digital Image Correlation." Key Engineering Materials 452-453 (November 2010): 377–80. http://dx.doi.org/10.4028/www.scientific.net/kem.452-453.377.

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DIC (Digital Image Correlation) based methodology gives full field measure of the displacement using a well defined algorithm for matching the images of loaded and load free component, so that displacement in a plane can be evaluated for a certain number of grid reference points on the analysed surface. In this work, the authors present an application of DIC technique to analyse fatigue damage phenomena in two notched GFRC laminates under tensile load. Damage analysis based on optical DIC technique has been performed to detect the damaged areas on the specimen surface. The damage evolution and failure mechanism has been followed monitoring two parameters: the local hysteresis area of stress-strain cycles, the local stiffness variation.

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Ibrahim, N. S., S. M. Sharun, M. K. Osman, S. B. Mohamed, and S. H. Y. S. Abdullah. "The application of UAV images in flood detection using image segmentation techniques." Indonesian Journal of Electrical Engineering and Computer Science 23, no. 2 (August 1, 2021): 1219. http://dx.doi.org/10.11591/ijeecs.v23.i2.pp1219-1226.

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The application of unmanned aerial vehicle (UAV) used to capture the images of the flood areas are becoming interest of most researchers recently. This is due to its versatilities of capturing the images with low-cost and real time responses. At present, the captured images are analysed manually by human experts, which cause the task labourous, time consuming and prone toerror. This study aims to develop an UAV-based automated flood detection system. Samples of images that consist of land and river areas were capture using a camera attached to UAV to emulate flooded and non-flooded areas.The RGB and HSI colour models were utilised to represent the flood images. Two image segmentation methods were studied, which are k-mean clustering and region growing. The segmented images were validated with manually segmented (ground truth) images. Simulation results show that the RG using gray images gave better segmentation accuracy (88%) as compared to the K-mean clustering (76%). Finally, an automated flood monitoring system based on the region growing method, called flood detection structure (FDS) was developed to detect and analyse the flood severity.

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Ratan, Ram, and Arvind Yadav. "Security Analysis of Bit plane Level Image Encryption Schemes." Defence Science Journal 71, no. 2 (March 10, 2021): 209–21. http://dx.doi.org/10.14429/dsj.71.15643.

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A selective bit-plane encryption scheme was proposed for securing the transmission of image data in mobile environments with a claim that it provides a high security viz. the encryption of the four most significant bit-planes is sufficient for a high image data security. This paper presents the security analysis of the said encryption scheme and reports new important results. We perform the security analysis of the bit-level encryption by considering the normal images and their histogram equalised enhanced images. We consider different bit-plane aspects to analyse the security of the image encryption, and show that the encryption of the four most significant bit-planes is not adequate. The contents of the images can be obtained even when all the bit-planes except one least significant bit-plane are encrypted in the histogram equalised images as shown in the results. The bit-plane level security analysis seems very useful for the analysis of the bit-plane level image encryption schemes.

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FLIEGER, Marcin, and Michał FLIEGER. "IMAGE MANAGEMENT IN PUBLIC ADMINISTRATION." Scientific Journal of the Military University of Land Forces 162, no. 4 (October 1, 2011): 422–33. http://dx.doi.org/10.5604/01.3001.0002.3316.

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The article deals with the question of creating and sustaining a strong, positive image of public administration institutions. The idea is to emphasise the importance of putting ef-forts to manage the image actively and to present the undisputed benefits that this process brings. Hence, the paper explains thoroughly the characteristic of an image itself and how it developed to the so-called ‘rational approach’. Then the authors analyse very specific ideas and assumptions which lay at the basis of undertaking measures in the field of public relations, which differ substantially from the motivation in private companies. Moreover, the article scrutinizes crucial groups of the public which might be attracted to the region by its positive perception and profoundly analyses the instruments of image management, at the same focusing on the fields in which public administration institutions ought to take up measures in order to build a positive image.

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Kiviniemi, Anne-Laure. "Dire l’indicible et décrire l’indescriptible: Ressources imagières et linguistiques des poilus." Semiotica 2015, no. 207 (October 1, 2015): 139–74. http://dx.doi.org/10.1515/sem-2015-0054.

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RésuméCet article étudie et confronte les usages que font quatre soldats aux profils scolaires différents des ressources imagières et linguistiques pour exprimer l’inexprimable. Il s’agira de déterminer si leurs utilisations des mots et de l’image attestent d’une “déchirure du pouvoir d’expression” (Balibar 1985: 406) entre bénéficiaires de l’instruction primaire et bénéficiaires de l’instruction secondaire. L’usage concurrent, synergique ou fusionnel des deux systèmes sémiotiques sera étudié via une analyse stylistico-pragmatique. Seront passées en revue les manières dont les soldats parviennent à imager les dires et dire les images, dire en images ou dire avec l’image, donner du sens aux mots ou changer le sens des mots à travers leur image.

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Kolacz, Jacek. "Advanced separation technologies for pre-concentration of metal ores and the additional process control." E3S Web of Conferences 18 (2017): 01001. http://dx.doi.org/10.1051/e3sconf/20171801001.

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A new sensor based sorting system has been developed at Comex, based on complex image analysis. The sorting system employs different images generated by visible light and X-ray to provide maximal information about processed particles. Application of X-ray makes it possible to analyse the internal structure of the particles, which provides a 2D image with the valuable information. The advanced system for the texture and the pattern recognition is applied to analyse these images simultaneously, to provide the required identification of the particles for efficient separation. The paper describes a number of tests during sorting of Cu-Zn-Sn ores with high separation efficiency. As an example, the Cu content is enriched from 0.4% to 1.25% and the Zn content is increased from 0.83% to 2.24%. In addition, the performance of the X-ray sorting system is described for enrichment of Zn-Pb ore and compared with the heavy media separation technology. Simplifying the pre- concentration through the use of the sorting technology can significantly reduce the cost of these operations. Finally, the operating data from the sorting system have been analysed regarding a potential use for controlling the plant operation. This can bring the new tools for control strategies for the complex processing plants.

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Zeng, Qingjie, Hanlin Qin, Xiang Yan, Shuowen Yang, and Tingwu Yang. "Single Infrared Image-Based Stripe Nonuniformity Correction via a Two-Stage Filtering Method." Sensors 18, no. 12 (December 6, 2018): 4299. http://dx.doi.org/10.3390/s18124299.

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The presence of stripe nonuniformity severely degrades the image quality and affects the performance in many infrared (IR) sensing applications. Prior works correct the nonuniformity by using similar spatial representations, which inevitably damage some detailed structures of the image. In this paper, we instead take advantage of spectral prior of stripe noise to solve its correction problem in single IR image. We first analyse the significant spectral difference between stripes and image structures and utilize this knowledge to characterize stripe nonuniformity. Then a two-stage filtering strategy is adopted combining spectral and spatial filtering. The proposed method enables stripe nonuniformity to be eliminated from coarse to fine, thus preserving image details well. Extensive experiments on simulated images and raw IR images demonstrate that the proposed method achieves superior correction performance over the recent state-of-the-art methods.

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Hokka, Jenni, and Matti Nelimarkka. "Affective economy of national-populist images: Investigating national and transnational online networks through visual big data." New Media & Society 22, no. 5 (August 21, 2019): 770–92. http://dx.doi.org/10.1177/1461444819868686.

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In our article, we investigate the affective economy of national-populist image circulation on Facebook. This is highly relevant, since social media has been an essential area for the spread of national-populist ideology. In our research, we analyse image circulation as affective practice, combining qualitative and quantitative methods. We use computational data analysis methods to examine visual big data: image fingerprints and reverse image search engines to track down the routes of thousands of circulated images as well as make discourse-historical analysis on the images that have gained most attention among supporters. Our research demonstrates that these existing tools allow social science research to make theory-solid approaches to understand the role of image circulation in creating and sustaining national and transnational networks on social media, and show how national-populist thinking is spread through images that catalyse and mobilise affects – fear, anger and resentment – thus creating an effective affective economy.

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Zhao, Xi, Anthony T. S. Ho, and Yun Q. Shi. "Image Forensics Using Generalised Benford's Law for Improving Image Authentication Detection Rates in Semi-Fragile Watermarking." International Journal of Digital Crime and Forensics 2, no. 2 (April 2010): 1–20. http://dx.doi.org/10.4018/jdcf.2010040101.

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In the past few years, semi-fragile watermarking has become increasingly important to verify the content of images and localise the tampered areas, while tolerating some non-malicious manipulations. In the literature, the majority of semi-fragile algorithms have applied a predetermined threshold to tolerate errors caused by JPEG compression. However, this predetermined threshold is typically fixed and cannot be easily adapted to different amounts of errors caused by unknown JPEG compression at different quality factors (QFs). In this paper, the authors analyse the relationship between QF and threshold, and propose the use of generalised Benford’s Law as an image forensics technique for semi-fragile watermarking. The results show an overall average QF correct detection rate of approximately 99%, when 5%, 20% and 30% of the pixels are subjected to image content tampering and compression using different QFs (ranging from 95 to 65). In addition, the authors applied different image enhancement techniques to these test images. The proposed image forensics method can adaptively adjust the threshold for images based on the estimated QF, improving accuracy rates in authenticating and localising the tampered regions for semi-fragile watermarking.

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Tellez-Alvarez, Jackson, Manuel Gómez, Beniamino Russo, and Jose M. Redondo. "Using surface flow image velocimetry to analyse flow approaching grated inlets." Proceedings of the Institution of Civil Engineers - Water Management 173, no. 3 (June 2020): 152–62. http://dx.doi.org/10.1680/jwama.18.00103.

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Hudier, E. J.-J., D. Delisles, and P. Larouche. "ANALYSE DE LA DISTRIBUTION DES CRÊTES DE PRESSION SUR IMAGE SATELLITAIRE." Canadian Journal of Remote Sensing 19, no. 1 (January 1993): 083–87. http://dx.doi.org/10.1080/07038992.1993.10855154.

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Liu, S., H. Li, X. Wang, L. Guo, and R. Wang. "STUDY ON MOSAIC AND UNIFORM COLOR METHOD OF SATELLITE IMAGE FUSION IN LARGE SREA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (April 30, 2018): 1099–102. http://dx.doi.org/10.5194/isprs-archives-xlii-3-1099-2018.

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Due to the improvement of satellite radiometric resolution and the color difference for multi-temporal satellite remote sensing images and the large amount of satellite image data, how to complete the mosaic and uniform color process of satellite images is always an important problem in image processing. First of all using the bundle uniform color method and least squares mosaic method of GXL and the dodging function, the uniform transition of color and brightness can be realized in large area and multi-temporal satellite images. Secondly, using Color Mapping software to color mosaic images of 16bit to mosaic images of 8bit based on uniform color method with low resolution reference images. At last, qualitative and quantitative analytical methods are used respectively to analyse and evaluate satellite image after mosaic and uniformity coloring. The test reflects the correlation of mosaic images before and after coloring is higher than 95&thinsp;% and image information entropy increases, texture features are enhanced which have been proved by calculation of quantitative indexes such as correlation coefficient and information entropy. Satellite image mosaic and color processing in large area has been well implemented.

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Dhaya, R. "Construction of reliable image captioning system for web camera based traffic analysis on road transport application." June 2021 3, no. 2 (July 17, 2021): 114–30. http://dx.doi.org/10.36548/jtcsst.2021.2.004.

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The automated captioning of natural images with appropriate descriptions is an intriguing and complicated task in the field of image processing. On the other hand, Deep learning, which combines computer vision with natural language, has emerged in recent years. Image emphasization is a record file representation that allows a computer to understand the visual information of an image in one or more words. When it comes to connecting high-quality images, the expressive process not only requires the credentials of the primary item and scene but also the ability to analyse the status, physical characteristics, and connections. Many traditional algorithms substitute the image to the front image. The image characteristics are dynamic depending on the ambient condition of natural photographs. Image processing techniques fail to extract several characteristics from the specified image. Nonetheless, four properties from the images are accurately described by using our proposed technique. Based on the various filtering layers in the convolutional neural network (CNN), it is an advantage to extract different characteristics. The caption for the image is based on long short term memory (LSTM), which comes under recurrent neural network. In addition, the precise subtitling is compared to current conventional techniques of image processing and different deep learning models. The proposed method is performing well in natural images and web camera based images for traffic analysis. Besides, the proposed algorithm leverages good accuracy and reliable image captioning.

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Tseronis, Assimakis. "Determining the commitments of image-makers in arguments with multimodal allusions in the front covers of The Economist." International Review of Pragmatics 10, no. 2 (June 11, 2018): 243–69. http://dx.doi.org/10.1163/18773109-01002006.

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Abstract The alleged vagueness of visual images and the lack of a univocal coding scheme make it difficult to be sure about the propositions to which image-makers are committed. This is particularly problematic for the analysis of multimodal discourse from an argumentation studies perspective, because it makes it hard for the analyst to establish the argumentative nature and relevance of visuals. The paper explores how insights from Relevance Theory can be applied in order to determine the commitments of image-makers. In particular, it has recourse to the inferential processes involved in the recovery of explicit and implicit content in order to analyse a series of covers from The Economist, where visuals in combination with verbal text cue allusions to films and paintings. It argues that these multimodal allusions are not simply used to attract the audience’s attention but also help the analyst to reconstruct the argument of the cover.

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SUNDASARI, Witakania, and Ferli HASANAH. "LITTLE BONEY, GROSSE MENACE : UNE ANALYSE DE L’IMAGE." FRANCISOLA 2, no. 2 (December 31, 2017): 202. http://dx.doi.org/10.17509/francisola.v2i2.9412.

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RÉSUMÉ. Exprimant un message, une image est utilisée comme moyens de communication. Malgré son effet comique, une caricature politique construit indispensablement un discours politique. En 1804 James Gillray a lancé un dessin satirique qui dénonce Napoléon Bonaparte ainsi que les idées républicaines de la Révolution de 1789 pour sensibiliser le public Britannique par ses regards royalistes contre la France révolutionnaire et napoléonienne. La présente recherche s’insère sur l’étude sémiologique de l’image publiée pendant cette période turbulente et l’analyse s’effectue en appliquant les lectures dénotative et connotative sur les signes linguistiques, iconiques et plastiques. Cette analyse a pour but de montrer comment cette caricature communique ses messages et comment l’artiste communique son engagement politique. Les résultats montrent que l’artiste a transmis son message par les parallélismes ainsi que par les oppositions que tous les signes reposent sur l’image. Mots-clés : analyse d’image, angleterre, caricature, révolution française. ABSTRACT. Expressing a message, an image is used as a tool of communication. Despite its comic effects, a political caricature unavoidably constructs a political discourse. In 1804, James Gillray launched a satirical drawing that denounced Napoleon Bonaparte and the Republican ideas of the Revolution of 1789 to alert the British public through his royalist point of view against revolutionary and Napoleonic France. This research is based on the semiological study of the image which was published during this turbulent period and the analysis is carried out by applying the denotative and connotative readings on linguistic, iconic and plastic signs. This research aims to show how this caricature transfers its messages and how the artist declared communicate his political commitments. The results show that the artist sent his message through the parallelism as well as the oppositions that all the signs rest on the image.Keywords: caricature, caricature analysis, England, French revolution.

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Wu, Cheng Yu, Fei Qing Wu, and Hui Mei Yang. "Measurement of Work Piece Surface Quality Based on Digital Image Processing." Applied Mechanics and Materials 101-102 (September 2011): 689–92. http://dx.doi.org/10.4028/www.scientific.net/amm.101-102.689.

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This article discusses how to apply sensor mixture, modern image handle and computer vision technology to analyse and to deal with the feature messages of the ground work piece surface flaw, and computer how to apply the filtered feature messages to identify these flaws. Result shows that this system can find the defect work piece real time from the images for testing.

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Sieberth, T., R. Wackrow, and J. H. Chandler. "UAV IMAGE BLUR – ITS INFLUENCE AND WAYS TO CORRECT IT." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-1/W4 (August 26, 2015): 33–39. http://dx.doi.org/10.5194/isprsarchives-xl-1-w4-33-2015.

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Unmanned aerial vehicles (UAVs) have become an interesting and active research topic in photogrammetry. Current research is based on image sequences acquired by UAVs which have a high ground resolution and good spectral resolution due to low flight altitudes combined with a high-resolution camera. One of the main problems preventing full automation of data processing of UAV imagery is the unknown degradation effect of blur caused by camera movement during image acquisition. The purpose of this paper is to analyse the influence of blur on photogrammetric image processing, the correction of blur and finally, the use of corrected images for coordinate measurements. It was found that blur influences image processing significantly and even prevents automatic photogrammetric analysis, hence the desire to exclude blurred images from the sequence using a novel filtering technique. If necessary, essential blurred images can be restored using information of overlapping images of the sequence or a blur kernel with the developed edge shifting technique. The corrected images can be then used for target identification, measurements and automated photogrammetric processing.

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Asatryan, D. G. "Gradient-based technique for image structural analysis and applications." Computer Optics 43, no. 2 (April 2019): 245–50. http://dx.doi.org/10.18287/2412-6179-2019-43-2-245-250.

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This paper is devoted to application of gradients field characteristics in selected problems of image intellectual analysis and processing. To analyse the properties and structure of an image several approaches and models based on the use of the gradients field characteristics, are proposed. In this paper, models based on Weibull distribution are considered, an image dominant direction estimation algorithm using the parameters of scattering ellipse of gradients field components is proposed, and a similarity measure of two images with arbitrary dimensions and orientation is proposed. Some examples of applications of these models for estimation of blur and structuredness of an image, for the quality assessment of resizing and rotating algorithms, as well as for detection of a specified object on the image delivered by an unmanned aerial vehicle, are given.

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Bretzke, Pascal. "Computertomografie – Kosten-Nutzen-Analyse von Computertomografie-Scannern." Gesundheitsökonomie & Qualitätsmanagement 22, no. 06 (December 2017): 275. http://dx.doi.org/10.1055/s-0043-123902.

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Burgers LT et al. Cost-effectiveness analysis of new generation coronary CT scanners for difficult-to-image patients. The European Journal of Health Economics 2017; 18: 731–742 Die koronare Herzkrankheit (KHK) zählt zu den häufigsten Todesursachen im Erwachsenenalter. Insbesondere die patientenassoziierten Folgen sind gravierend, da jeder fünfte Sterbefall im Jahr 2003 durch eine KHK verursacht wurde. Zur Diagnostik einer KHK stehen sowohl die invasive Koronarangiografie (ICA), als auch Geräte der neuen Generation (New generation dual-source coronoray CT/NGCCT) zur Verfügung. Ziel der Studie war die Evaluation des Einsparpotenzials sowie des Nutzens beider Alternativen.

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Lu, Zhaolin, Xiaojuan Hu, and Yao Lu. "Particle Morphology Analysis of Biomass Material Based on Improved Image Processing Method." International Journal of Analytical Chemistry 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/5840690.

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Particle morphology, including size and shape, is an important factor that significantly influences the physical and chemical properties of biomass material. Based on image processing technology, a method was developed to process sample images, measure particle dimensions, and analyse the particle size and shape distributions of knife-milled wheat straw, which had been preclassified into five nominal size groups using mechanical sieving approach. Considering the great variation of particle size from micrometer to millimeter, the powders greater than 250 μm were photographed by a flatbed scanner without zoom function, and the others were photographed using a scanning electron microscopy (SEM) with high-image resolution. Actual imaging tests confirmed the excellent effect of backscattered electron (BSE) imaging mode of SEM. Particle aggregation is an important factor that affects the recognition accuracy of the image processing method. In sample preparation, the singulated arrangement and ultrasonic dispersion methods were used to separate powders into particles that were larger and smaller than the nominal size of 250 μm. In addition, an image segmentation algorithm based on particle geometrical information was proposed to recognise the finer clustered powders. Experimental results demonstrated that the improved image processing method was suitable to analyse the particle size and shape distributions of ground biomass materials and solve the size inconsistencies in sieving analysis.

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Li, Yonglong, Hua Zhang, Shuang Wang, Haoran Wang, and Jialong Li. "Image-Based Underwater Inspection System for Abrasion of Stilling Basin Slabs of Dam." Advances in Civil Engineering 2019 (October 1, 2019): 1–13. http://dx.doi.org/10.1155/2019/6924976.

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The abrasion of stilling basin slabs which is caused by waterborne particles is one of the main surface damages in the operation of hydropower station. For determining whether to repair the stilling basin slabs, periodic inspections of erosion condition of stilling basin slabs are required. The practical problem is how to get the underwater image without unwatering and how to analyse the abrasion though the images. This paper developed a novel underwater inspection system named UIS-1 which consists of a customized underwater robot and special quantitative analysis method for this situation. Firstly, the integrated component was designed for the underwater robot that partially removes the siltation and obtains the image of the concrete surface of stilling basin slabs in the desired position. Secondly, the paper proposed an image algorithm to obtain aggregate exposure ratio for quantitative abrasion analysis. This image algorithm used SLIC superpixel and the SVM machine learning method to detect the coarse aggregate exposure automatically. Then, the aggregate exposure ratio was calculated to analyse the degree of abrasion. Finally, the UIS-1 system was evaluated in the field experiments of a dam in Sichuan, China, and its performance was discussed by comparison.

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Naganandhini, S., P. Shanmugavadivu, and V. Sivakumar. "MR Brain Image Segmentation Using k-Means Clustering and Expectation Maximization." Journal of Computational and Theoretical Nanoscience 16, no. 8 (August 1, 2019): 3637–41. http://dx.doi.org/10.1166/jctn.2019.8362.

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Magnetic Resonance Images (MRI) for brain play an important role to identify the disease, dysfunction or disorder of human brain. These images are the primary source to study, analyse and diagnose the anatomy of the brain. This paper presents a new combinatorial technique titled, “MR Brain Image Segmentation using k-Means Clustering and Expectation Maximization (MRB-KMEM)” that performs skull stripping, impulse noise removal, segmentation of brain tissues and classification of brain images. The skull is removed using the technique of morphology-bound brain segmentation and Progressive Switching Median Filter (PSMF) is used to suppress brain image distortion. Further, brain tissues segmentation into white matter and grey matter is performed by KM-EM. The research outcomes can be used to study the features of a brain, its defects and to detect Alzheimer’s disease.

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Purwani, Sri, Julita Nahar, and Carole Twining. "Brain Image Segmentation with Gradient Information." International Journal of Engineering & Technology 7, no. 4.38 (December 3, 2018): 1392. http://dx.doi.org/10.14419/ijet.v7i4.38.27882.

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Segmentation is the process of extracting structures within the images. The purpose is to simplify the representation of the image into something meaningful and easier to analyse. A magnetic resonance (MR) brain image can be represented as three main tissues, e.g. cerebrospinal fluid (CSF), grey matter and white matter. Although various segmentation methods have been developed, such images are generally segmented by modelling the intensity histogram by using a Gaussian Mixture Model (GMM). However, the standard use of 1D histogram sometimes fails to find the mean for Gaussians. We hence solved this by including gradient information in the 2D intensity and intensity gradient histogram. We applied our methods on real data of 2D MR brain images. We then compared the methods with the previous published method of Petrovic et al. on their dataset, as well as on our larger datasets extracted from the same database of 3D MR brain mages, where the ground-truth annotations are available. This shows that our method performs better than the previous method.

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Tian, J., T. Schneider, C. Kempf, Y. Xia, M. Lusseau, J. Hill, E. Jachmann, and P. Reinartz. "EARLY DETECTION OF FOREST DROUGHT STRESS WITH VERY HIGH RESOLUTION STEREO AND HYPERSPECTRAL IMAGERY." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences V-2-2020 (August 3, 2020): 781–87. http://dx.doi.org/10.5194/isprs-annals-v-2-2020-781-2020.

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Abstract. The project ‘Application of remote sensing for the early detection of drought stress at vulnerable forest sites (ForDroughtDet)’ is funded by the German Federal Agency of Agriculture and Food and aims to detect drought stress in an early phase using remote sensing techniques. In this project, three test sites in the south and middle part of Germany are selected. Three levels of observation and analyses are performed. In the first level, close-range stereo images and spectral information are captured with a research crane in Kranzberg forest. In the second level, three study sites are imaged twice in three years by airborne hyperspectral and stereo cameras. In the third level, the drought stress detection approach will be transferred to regional scale by satellite image. In this paper, we will briefly report our results from the first and second levels. In the first level, 3D models of the forest canopies are generated with the MC-CNN based dense matching approaches, with which the 3D shapes of the stressed and healthy trees are analysed. In addition, for the spectral analyses, different chlorophyll-sensitive indices are calculated and compared for the stressed and healthy trees. In order to further analyse the tree drought stress in the second level, a novel individual tree crown (ITC) segmentation approach is proposed and tested on the airborne stereo dataset.

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Pieczywek, Piotr M., Justyna Cybulska, Barbara Dyki, Dorota Konopacka, Monika Mieszczakowska-Frąc, and Artur Zdunek. "New image analysis method for the estimation of global and spatial changes in fruit microstructure." International Agrophysics 30, no. 2 (April 1, 2016): 219–29. http://dx.doi.org/10.1515/intag-2015-0073.

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Abstract A new image analysis method for the spatial characterization of microscopy images of fruit microstructure is proposed in order to analyse the heterogeneous microstructure of unprocessed fruit and the possible inhomogeneous effects of various technological treatments on this microstructure. The micro-structure of tissue samples was characterized using the global statistics of size and shape parameters calculated for all visible objects. Global analysis was supported by a novel algorithm that allowed for drawing of the maps of the cell wall fraction from microscopy images and for the analysis of both global and local compaction or loosening of tissue. The spatial distribution of the cell wall fraction was visualised in the convenient form of bivariate histograms. To test the developed image analysis protocols, structural changes resulting from ultrasonic and osmotic treatments of apple tissue samples were studied. Peeled and cored apples were submersed in a liquid medium (distilled water or 60 °Bx sucrose solution) for 45 and 90 min with and without ultrasonic treatment. After these treatment procedures, tissue samples were cut into slices, stained and imaged using a microscope. The proposed method allowed to characterise the effects of different sample treatments.

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MANZIUK, E., T. SKRYPNYK, and M. HIRNYI. "DETERMINATION OF RECIPES CONSTITUENT ELEMENTS BASED ON IMAGE." Computer Systems and Information Technologies 1, no. 1 (September 2, 2020): 42–46. http://dx.doi.org/10.31891/csit-2020-1-5.

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Image recognition is used to retrieve, analyse, understand, and process images from the real world to convert them into digital information. In this area involved data mining, machine learning, pattern recognition, knowledge extension. Developments in the image recognition area have resulted in computers and smartphones becoming capable of mimicking human eyesight. Improved cameras in modern devices can take pictures of very high quality, and with the help of new software, they receive the necessary information and on the basis of the received data is processed images. However, food recognition challenges modern computer vision systems and needs to go beyond just an visible image. Compared to understanding the natural image, visual prediction of ingredients requires high-level solutions and previous knowledge. This creates additional problems, because food components have high variability between the class, when cooking, you have to convert components and the ingredients are often included in the cooked dish. The recognition system allows you to take a step toward understanding the food supply systems such as calorie score and create recipes. The recognition system can be used to address wider problems, such as the prediction of the image on the consistency of the folding elements.

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Tacelli, N., K. Boroto, M. Rémy-Jardin, J. B. Faivre, V. Deken, V. Pansini, A. Gorgos, and J. Rémy. "Angioscanographie thoracique avec ultra haute resolution temporelle : analyse de la qualite image." Journal de Radiologie 89, no. 10 (October 2008): 1421. http://dx.doi.org/10.1016/s0221-0363(08)76307-8.

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Chrysochoos, André, and Hervé Louche. "An infrared image processing to analyse the calorific effects accompanying strain localisation." International Journal of Engineering Science 38, no. 16 (November 2000): 1759–88. http://dx.doi.org/10.1016/s0020-7225(00)00002-1.

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Tuononen, Ari J. "Digital Image Correlation to analyse stick–slip behaviour of tyre tread block." Tribology International 69 (January 2014): 70–76. http://dx.doi.org/10.1016/j.triboint.2013.09.003.

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Journal articles on the topic 'Analyse image'

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