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Journal articles on the topic 'Animal detection – Still images'

Author: Grafiati

Published: 4 June 2021

Last updated: 16 February 2022

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1

Barbedo, Jayme Garcia Arnal, Luciano Vieira Koenigkan, and Patrícia Menezes Santos. "Cattle Detection Using Oblique UAV Images." Drones 4, no. 4 (2020): 75. http://dx.doi.org/10.3390/drones4040075.

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The evolution in imaging technologies and artificial intelligence algorithms, coupled with improvements in UAV technology, has enabled the use of unmanned aircraft in a wide range of applications. The feasibility of this kind of approach for cattle monitoring has been demonstrated by several studies, but practical use is still challenging due to the particular characteristics of this application, such as the need to track mobile targets and the extensive areas that need to be covered in most cases. The objective of this study was to investigate the feasibility of using a tilted angle to increa

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Barbedo, Jayme Garcia Arnal, Luciano Vieira Koenigkan, Thiago Teixeira Santos, and Patrícia Menezes Santos. "A Study on the Detection of Cattle in UAV Images Using Deep Learning." Sensors 19, no. 24 (2019): 5436. http://dx.doi.org/10.3390/s19245436.

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Unmanned aerial vehicles (UAVs) are being increasingly viewed as valuable tools to aid the management of farms. This kind of technology can be particularly useful in the context of extensive cattle farming, as production areas tend to be expansive and animals tend to be more loosely monitored. With the advent of deep learning, and convolutional neural networks (CNNs) in particular, extracting relevant information from aerial images has become more effective. Despite the technological advancements in drone, imaging and machine learning technologies, the application of UAVs for cattle monitoring

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Harvey, Andrea M., John M. Morton, David J. Mellor, Vibeke Russell, Rosalie S. Chapple, and Daniel Ramp. "Use of Remote Camera Traps to Evaluate Animal-Based Welfare Indicators in Individual Free-Roaming Wild Horses." Animals 11, no. 7 (2021): 2101. http://dx.doi.org/10.3390/ani11072101.

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We previously developed a Ten-Stage Protocol for scientifically assessing the welfare of individual free-roaming wild animals using the Five Domains Model. The protocol includes developing methods for measuring or observing welfare indices. In this study, we assessed the use of remote camera traps to evaluate an extensive range of welfare indicators in individual free-roaming wild horses. Still images and videos were collected and analysed to assess whether horses could be detected and identified individually, which welfare indicators could be reliably evaluated, and whether behaviour could be

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Cahya, Habib Dwi, and Agus Harjoko. "Otomasi Kamera Perangkap Menggunakan Deteksi Gerak dan Komputer Papan Tunggal." IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) 9, no. 1 (2019): 11. http://dx.doi.org/10.22146/ijeis.36102.

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USB camera is currently used in daily life for various purposes. On its development, the use of USB camera can be used to create camara traps and can be used to observe the development of animal with integrated systems. In this research, motion detection was used to observe animals online using Single Board Computer (SBC) Camera trap in this research using Single Board camera in form of raspberry pi 3 B. Python proggramming language is used with OpenCV library. The method used to detect motion is the Mixture of Gaussian (MOG). The result image gained by motion detection will be uploaded to the

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Lonhus, Kirill, Dalibor Štys, Mohammadmehdi Saberioon, and Renata Rychtáriková. "Segmentation of Laterally Symmetric Overlapping Objects: Application to Images of Collective Animal Behavior." Symmetry 11, no. 7 (2019): 866. http://dx.doi.org/10.3390/sym11070866.

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Video analysis is currently the main non-intrusive method for the study of collective behavior. However, 3D-to-2D projection leads to overlapping of observed objects. The situation is further complicated by the absence of stall shapes for the majority of living objects. Fortunately, living objects often possess a certain symmetry which was used as a basis for morphological fingerprinting. This technique allowed us to record forms of symmetrical objects in a pose-invariant way. When combined with image skeletonization, this gives a robust, nonlinear, optimization-free, and fast method for detec

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Aulia Rahman, Dede, and Yudi Setiawan. "Possibility of applying unmanned aerial vehicle and thermal imaging in several canopy cover class for wildlife monitoring – preliminary results." E3S Web of Conferences 211 (2020): 04007. http://dx.doi.org/10.1051/e3sconf/202021104007.

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Tropical rainforests are one of the important habitats on earth but are rarely explored because they are diﬃcult to access, making their cryptic animals challenging to monitor. Unmanned aerial vehicle (UAV) with thermal infrared imaging (TIR) technology is gaining entry into wildlife research and monitoring. The researcher tested the possibility of applying DJI Mavic 2 Enterprise Dual with FLIR as aerial survey platforms to wildlife in the five tree density classes in the IPB University Campus. To assess the effectiveness of using drones in detecting wildlife, the researcher measured the optim

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Condotta, Isabella. "380 Precision Management of Animals: Image Processing and Computer Vision Applications." Journal of Animal Science 98, Supplement_4 (2020): 137. http://dx.doi.org/10.1093/jas/skaa278.252.

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Abstract Growing populations, rising wealth, and urbanization are translating into increased demand for animal products, which causes a need for rapid intensification of production. With that, economic pressures mount on animal producers, who are forced to increase herds’ sizes in order to be commercially feasible, limiting time of interaction with their animals. In contrast, society is demanding closer attention to the needs of individual animals and their well-being, and reduction of the environmental impact of animal production. Paying closer attention to the animal can not only positively

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Junaid, Muhammad, Luqman Shah, Ali Imran Jehangiri, et al. "Recognition of Images Formed in Pho on the Eyes of different Subjects." Revista Gestão Inovação e Tecnologias 11, no. 4 (2021): 3023–29. http://dx.doi.org/10.47059/revistageintec.v11i4.2335.

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With each passing day resolutions of still image/video cameras are on the rise. This amelioration in resolutions has the potential to extract useful information on the view opposite the photographed subjects from their reflecting parts. Especially important is the idea to capture images formed on the eyes of photographed people and animals. The motivation behind this research is to explore the forensic importance of the images/videos to especially analyze the reflections of the background of the camera. This analysis may include extraction/ detection/recognition of the objects in front of the

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Goetschalckx, Lore, and Johan Wagemans. "MemCat: a new category-based image set quantified on memorability." PeerJ 7 (December 12, 2019): e8169. http://dx.doi.org/10.7717/peerj.8169.

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Images differ in their memorability in consistent ways across observers. What makes an image memorable is not fully understood to date. Most of the current insight is in terms of high-level semantic aspects, related to the content. However, research still shows consistent differences within semantic categories, suggesting a role for factors at other levels of processing in the visual hierarchy. To aid investigations into this role as well as contributions to the understanding of image memorability more generally, we present MemCat. MemCat is a category-based image set, consisting of 10K images

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Francisco, Francisco, and Jan Sundberg. "Detection of Visual Signatures of Marine Mammals and Fish within Marine Renewable Energy Farms using Multibeam Imaging Sonar." Journal of Marine Science and Engineering 7, no. 2 (2019): 22. http://dx.doi.org/10.3390/jmse7020022.

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Techniques for marine monitoring have been greatly evolved over the past decades, making the acquisition of environmental data safer, more reliable and more efficient. On the other hand, the marine renewable energy sector has introduced dissimilar ways of exploring the oceans. Marine energy is mostly harvested in murky and high energetic places where conventional data acquisition techniques are impractical. This new frontier on marine operations brings the need for finding new techniques for environmental data acquisition, processing and analysis. Modern sonar systems, operating at high freque

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Jang, Taichang, Binulal Sathy, Yi-Hua Hsu, et al. "A distinct phenotypic change in gliomas at the time of magnetic resonance imaging detection." Journal of Neurosurgery 108, no. 4 (2008): 782–90. http://dx.doi.org/10.3171/jns/2008/108/4/0782.

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Object Although gliomas remain refractory to treatment, it is not clear whether this characteristic is fixed at the time of its origin or develops later. The authors have been using a model of neurocarcinogenesis to determine whether a time exists during a glioma's evolution during which it is detectable but still curable, thus providing a justification for exploring the clinical merits of an early detection and treatment strategy. The authors recently reported the presence of 2 distinct cellular subsets, 1 expressing nestin and the other both glial fibrillary acidic protein (GFAP) and osteopo

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McAloney, Camille A., Leslie C. Sharkey, Daniel A. Feeney, and Davis M. Seelig. "Diagnostic utility of renal fine-needle aspirate cytology and ultrasound in the cat." Journal of Feline Medicine and Surgery 20, no. 6 (2017): 544–53. http://dx.doi.org/10.1177/1098612x17720041.

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Objectives The primary objective of this study was to retrospectively assess the diagnostic utility of feline renal fine-needle aspiration cytology by assessing diagnostic yield, cytologic characteristics and diagnostic accuracy. The secondary objective was to characterize ultrasonographic features of sampled kidneys to determine if they influenced diagnostic yield. Methods Slides, images and patient data were collected from the University of Minnesota Veterinary Medical Center database. Slides were designated as diagnostic or non-diagnostic. Non-diagnostic slides were used in calculating diag

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Pho, Khoa, Muhamad Kamal Mohammed Amin, and Atsuo Yoshitaka. "Segmentation-driven Hierarchical RetinaNet for Detecting Protozoa in Micrograph." International Journal of Semantic Computing 13, no. 03 (2019): 393–413. http://dx.doi.org/10.1142/s1793351x19400178.

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Protozoa detection and identification play important roles in many practical domains such as parasitology, scientific research, biological treatment processes, and environmental quality evaluation. Traditional laboratory methods for protozoan identification are time-consuming and require expert knowledge and expensive equipment. Another approach is using micrographs to identify the species of protozoans that can save a lot of time and reduce the cost. However, the existing methods in this approach only identify the species when the protozoan are already segmented. These methods study features

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Stalder, Kenneth J. "296 Awardee Talk: The Genetics of Sow Longevity." Journal of Animal Science 98, Supplement_4 (2020): 28. http://dx.doi.org/10.1093/jas/skaa278.050.

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Abstract Sow longevity is a key productivity indicator trait that has real economic and welfare importance for commercial swine farms globally. The average parity at culling is 3.8 parities. Reports indicate that it takes 3 to 4 parities before a sow “pays for herself.” Research groups around the world have reported heritabilities estimates for sow longevity traits ranging from 0.05 to 0.35. Estimate differences result from the animal population under evaluation, the trait being evaluated, and the methodology employed to obtain the genetic parameter estimate. Because sow longevity is measured

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Gong, Adu, Jing Li, and Yanling Chen. "A Spatio-Temporal Brightness Temperature Prediction Method for Forest Fire Detection with MODIS Data: A Case Study in San Diego." Remote Sensing 13, no. 15 (2021): 2900. http://dx.doi.org/10.3390/rs13152900.

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Early detection of forest fire is helpful for monitoring the spread of fire promptly, minimizing the loss of forests, wild animals, human life, and economy. The performance of brightness temperature (BT) prediction determines the accuracy of fire detection. Great efforts have been made on BT prediction model building, but there still remains some uncertainty. Based on the widely used contextual BT prediction model (CM) and temporal-contextual BT prediction model (TCM), we proposed a spatio-temporal contextual BT prediction model (STCM), which involves historical images to contrast the BT corre

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Xu, Jian-Guang. "Evaluation of Neuropathic Pain in a Rat Model of Total Brachial Plexus Avulsion from Behavior to Brain Metabolism." Pain Physician 3, no. 22;3 (2019): E215—E224. http://dx.doi.org/10.36076/ppj/2019.22.e215.

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Background: Approximately 30% to 80% of patients with brachial plexus avulsion (BPA) developed neuropathic pain. It is an intolerable neuropathic pain, which brings heavy burden to family and society. In addition to motor and sensory deficits, neuropathic pain can be another serious sequela that equally influences the patient. The development of a microsurgical technique has promoted the treatment and rehabilitation of brachial plexus injury, but pain relief after BPA is still a difficult problem. Objectives: The present study aimed to semi-quantify changes in the behavior, spinal cord and cer

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Mustafa, O., C. Braun, J. Esefeld, et al. "DETECTING ANTARCTIC SEALS AND FLYING SEABIRDS BY UAV." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-2/W5 (May 29, 2019): 141–48. http://dx.doi.org/10.5194/isprs-annals-iv-2-w5-141-2019.

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<p><strong>Abstract.</strong> In recent years Unmanned Aerial Vehicles (UAVs) became a fast-developing technology with manifold fields of application. In the field of wildlife biology, it offers the opportunity to quantify populations, to map the spatial distribution of species and to observe the behavior of animals with no or low disturbance. Moreover, UAV based mapping allows to obtain data from sites which are hardly or not accessible and to cover much larger areas than by traditional ground based methods. The advantages of UAV based mapping are of particular relevance und

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Can, Gulsum Nurdan, and Helin Dutagaci. "Human detection from still depth images." Electronic Imaging 2016, no. 21 (2016): 1–9. http://dx.doi.org/10.2352/issn.2470-1173.2016.21.3dipm-046.

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Tseng, J. K., P. C. Tang, and J. C. Ju. "357 CALCIUM RELEASE INDUCED BY THIMEROSAL AND INOSITOL 1,4,5-TRIPHOSPHATE IN HEAT-SHOCKED PORCINE OOCYTES." Reproduction, Fertility and Development 19, no. 1 (2007): 294. http://dx.doi.org/10.1071/rdv19n1ab357.

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Elevated ambient temperature has been known to be deleterious to the developmental competence of mammalian oocytes and embryos, although the mechanism is still unclear. The objective of this study was to determine the effect of heat shock (HS) on the alteration of intracellular calcium concentrations ([Ca2+]i) of matured pig oocytes by two different calcium releasing agents. Porcine cumulus–oocyte complexes were aspirated from the follicles (3–6 mm) and subjected to standard in vitro maturation procedure for 42 h. Matured oocytes were then randomly allocated to different heat treatments at 41.

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Bergboer, N. H., E. O. Postma, and H. J. van den Herik. "Context-based object detection in still images." Image and Vision Computing 24, no. 9 (2006): 987–1000. http://dx.doi.org/10.1016/j.imavis.2006.02.024.

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Zhang, Mingji. "Adaptive Skin-Color Detection in Still Images." Journal of Computer Research and Development 43, no. 9 (2006): 1674. http://dx.doi.org/10.1360/crad20060927.

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Chen, Zhe, Jian Qiang Gao, Jie Shen, and Hui Bin Wang. "Spectral Residual Based Underwater Animal Detection." Advanced Materials Research 850-851 (December 2013): 970–73. http://dx.doi.org/10.4028/www.scientific.net/amr.850-851.970.

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In this paper, the spectral residual method is applied in the underwater image data for detecting the animals. The system is designed to assist the underwater monitor system survey operations, specialized to the task of animal detection. Firstly, the regularity for the frequency spectrum of the images collected in the underwater world is discovered by the statistical analysis. Then we transform the input image into the spatial frequency domain and singularities including in the frequency curve is extracted by average filtering. Finally, these singularities are inverse transformed from the freq

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Jothi Shri, S., and S. Jothilakshmi. "Pedestrian Detection and Counting in Still Images for Crowd Monitoring." Journal of Computational and Theoretical Nanoscience 16, no. 4 (2019): 1356–59. http://dx.doi.org/10.1166/jctn.2019.8044.

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Rajagopalan, Ambasamudram N., and Rama Chellappa. "Higher-order-statistics-based detection of vehicles in still images." Journal of the Optical Society of America A 18, no. 12 (2001): 3037. http://dx.doi.org/10.1364/josaa.18.003037.

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Hamadi, Abdelkader, Hafsa Lattar, Mohamed El Bachir Khoussa, and Bahjat Safadi. "Using semantic context for multiple concepts detection in still images." Pattern Analysis and Applications 23, no. 1 (2018): 27–44. http://dx.doi.org/10.1007/s10044-018-0761-9.

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Khan, Rehan Ullah, Khalil Khan, Waleed Albattah, and Ali Mustafa Qamar. "Image-Based Detection of Plant Diseases: From Classical Machine Learning to Deep Learning Journey." Wireless Communications and Mobile Computing 2021 (June 2, 2021): 1–13. http://dx.doi.org/10.1155/2021/5541859.

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Plant disease automation in agriculture science is the primary concern for every country, as the food demand is increasing at a fast rate due to an increase in population. Moreover, the increased use of technology today has increased the efficacy and accuracy of detecting diseases in plants and animals. The detection process marks the beginning of a series of activities to fight the diseases and reduce their spread. Some diseases are also transmitted between animals and human beings, making it hard to fight them. For many years, scientists have researched how to deal with the common diseases t

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Uddin, Machbah, Hira Lal Gope, Md Sayeed Iftekhar Yousuf, Dilshad Islam, and Mohammad Khairul Islam. "Crowd Detection in Still Images Using Combined HOG and SIFT Feature." Indonesian Journal of Electrical Engineering and Computer Science 4, no. 2 (2016): 447. http://dx.doi.org/10.11591/ijeecs.v4.i2.pp447-458.

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<p>Person detection and tracking in crowd is a challenging task. We detect the head region and based on this head region we can detect people from crowd. Individual object detection has been improved significantly in recent times but the crowd detection and tracking contains some challenges. Crowd analysis is a highly focused area for law enforcement, urban engineering and traffic management. There are a lot of incident occurred in crowd area during some fabulous event. In this research low resolution and verities of image orientation is a key factor as well as overlapping person images

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Perko, Roland, and Aleš Leonardis. "A framework for visual-context-aware object detection in still images." Computer Vision and Image Understanding 114, no. 6 (2010): 700–711. http://dx.doi.org/10.1016/j.cviu.2010.03.005.

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Kumar, Ashu, Munish Kumar, and Amandeep Kaur. "Face detection in still images under occlusion and non-uniform illumination." Multimedia Tools and Applications 80, no. 10 (2021): 14565–90. http://dx.doi.org/10.1007/s11042-020-10457-9.

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Oishi, Yu, Hiroyuki Oguma, Ayako Tamura, Ryosuke Nakamura, and Tsuneo Matsunaga. "Animal Detection Using Thermal Images and Its Required Observation Conditions." Remote Sensing 10, no. 7 (2018): 1050. http://dx.doi.org/10.3390/rs10071050.

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Cuevas, Erik, and Mauricio González. "Multi-circle detection on images inspired by collective animal behavior." Applied Intelligence 39, no. 1 (2012): 101–20. http://dx.doi.org/10.1007/s10489-012-0396-2.

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Cuevas, Erik, Mauricio González, Daniel Zaldívar, and Marco Pérez-Cisneros. "Multi-ellipses detection on images inspired by collective animal behavior." Neural Computing and Applications 24, no. 5 (2013): 1019–33. http://dx.doi.org/10.1007/s00521-012-1332-4.

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Zotin, A. G., and A. V. Proskurin. "ANIMAL DETECTION USING A SERIES OF IMAGES UNDER COMPLEX SHOOTING CONDITIONS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W12 (May 9, 2019): 249–57. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w12-249-2019.

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<p><strong>Abstract.</strong> Camera traps providing enormous number of images during a season help to observe remotely animals in the wild. However, analysis of such image collection manually is impossible. In this research, we develop a method for automatic animal detection based on background modeling of scene under complex shooting. First, we design a fast algorithm for image selection without motions. Second, the images are processed by modified Multi-Scale Retinex algorithm in order to align uneven illumination. Finally, background is subtracted from incoming image usin

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Zhu, Weina, Jan Drewes, and Karl R. Gegenfurtner. "Animal Detection in Natural Images: Effects of Color and Image Database." PLoS ONE 8, no. 10 (2013): e75816. http://dx.doi.org/10.1371/journal.pone.0075816.

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Feng, Wenzhao, Junguo Zhang, Chunhe Hu, Yuan Wang, Qiumin Xiang, and Hao Yan. "A Novel Saliency Detection Method for Wild Animal Monitoring Images with WMSN." Journal of Sensors 2018 (June 6, 2018): 1–11. http://dx.doi.org/10.1155/2018/3238140.

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We proposed a novel saliency detection method based on histogram contrast algorithm and images captured with WMSN (wireless multimedia sensor network) for practical wild animal monitoring purpose. Current studies on wild animal monitoring mainly focus on analyzing images with high resolution, complex background, and nonuniform illumination features. Most current visual saliency detection methods are not capable of completing the processing work. In this algorithm, we firstly smoothed the image texture and reduced the noise with the help of structure extraction method based on image total varia

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Fourie, Jaco. "Robust Circle Detection Using Harmony Search." Journal of Optimization 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/9710719.

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Automatic circle detection is an important element of many image processing algorithms. Traditionally the Hough transform has been used to find circular objects in images but more modern approaches that make use of heuristic optimisation techniques have been developed. These are often used in large complex images where the presence of noise or limited computational resources make the Hough transform impractical. Previous research on the use of the Harmony Search (HS) in circle detection showed that HS is an attractive alternative to many of the modern circle detectors based on heuristic optimi

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Tzes, Anthony, and William R. McShane. "Development of Prototype Video-Based Sensor for Vehicle Detection from Stand-Still Images." Transportation Research Record: Journal of the Transportation Research Board 1570, no. 1 (1997): 202–10. http://dx.doi.org/10.3141/1570-23.

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The design, development, and testing of a prototype wide-area traffic detection system are described. The video-based sensor computes the approximate number of vehicles present within an a priori defined observation area from stand-still images. This sensor is mostly oriented toward the traffic detection in congested intersections, in which sensors using existing radar, acoustic, and video-based technology are faced with critical obstacles caused by the automobile stoppage. The prototype system has been tested and found to perform satisfactorily in field studies.

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Li, Meng, Yi Zhan, and Lidan Zhang. "Nonlocal Variational Model for Saliency Detection." Mathematical Problems in Engineering 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/518747.

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We present a nonlocal variational model for saliency detection from still images, from which various features for visual attention can be detected by minimizing the energy functional. The associated Euler-Lagrange equation is a nonlocalp-Laplacian type diffusion equation with two reaction terms, and it is a nonlinear diffusion. The main advantage of our method is that it provides flexible and intuitive control over the detecting procedure by the temporal evolution of the Euler-Lagrange equation. Experimental results on various images show that our model can better make background details dimin

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Yu, Yin Dong, Xu Bo Yang, Shuang Jiu Xiao, and Jia Le Lin. "Automated Ship Detection from Optical Remote Sensing Images." Key Engineering Materials 500 (January 2012): 785–91. http://dx.doi.org/10.4028/www.scientific.net/kem.500.785.

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Automatic ship detection from remote sensing images is very important as a variant of applications such as harbor management, cargo shipping, marine rescue and naval warfare will call for the aids of the analysis of these images. This paper focuses on the processing of space-born optical images (SDSOI). With the continuous development of photography technology, high-resolution remote sensing images are produced with extremely high speed, but still lack of an effective and swift method to automatically process them and get an applicable result. The whole work flow is based on three modules. Fir

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Vajda, Peter, Ivan Ivanov, Lutz Goldmann, Jong-Seok Lee, and Touradj Ebrahimi. "Robust Duplicate Detection of 2D and 3D Objects." International Journal of Multimedia Data Engineering and Management 1, no. 3 (2010): 19–40. http://dx.doi.org/10.4018/jmdem.2010070102.

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In this paper, the authors analyze their graph-based approach for 2D and 3D object duplicate detection in still images. A graph model is used to represent the 3D spatial information of the object based on the features extracted from training images to avoid explicit and complex 3D object modeling. Therefore, improved performance can be achieved in comparison to existing methods in terms of both robustness and computational complexity. Different limitations of this approach are analyzed by evaluating performance with respect to the number of training images and calculation of optimal parameters

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Verma, Gyanendra K., and Pragya Gupta. "Wild Animal Detection from Highly Cluttered Images Using Deep Convolutional Neural Network." International Journal of Computational Intelligence and Applications 17, no. 04 (2018): 1850021. http://dx.doi.org/10.1142/s1469026818500219.

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Monitoring wild animals became easy due to camera trap network, a technique to explore wildlife using automatically triggered camera on the presence of wild animal and yields a large volume of multimedia data. Wild animal detection is a dynamic research field since the last several decades. In this paper, we propose a wild animal detection system to monitor wildlife and detect wild animals from highly cluttered natural images. The data acquired from the camera-trap network comprises of scenes that are highly cluttered that poses a challenge for detection of wild animals bringing about low reco

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Lal Gope, Hira, Machbah Uddin, Shohag Barman, Dilshad Islam, and Mohammad Khairul Islam. "Fire Detection in Still Image Using Color Model." Indonesian Journal of Electrical Engineering and Computer Science 3, no. 3 (2016): 618. http://dx.doi.org/10.11591/ijeecs.v3.i3.pp618-625.

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Fire incidence is one of the major disasters of human society. This paper proposes a still image-based fire detection system. It has many advantages like lower cost, faster response, and large coverage. The existing methods are not able to detect fire region adequately. The proposed method overcome and addresses the issue. A binary contour image of flame that is capable of classifying fire or no fire in image for fire detection is proposed in this study. The color of fire area can range from red yellow to almost white. So, here it is challenges the detected area is actually fire or no fire. Ou

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Nishimura, Junichi, Jun Nishikawa, Munetaka Nakamura, et al. "Efficacy of i-Scan Imaging for the Detection and Diagnosis of Early Gastric Carcinomas." Gastroenterology Research and Practice 2014 (2014): 1–6. http://dx.doi.org/10.1155/2014/819395.

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We determined comparative efficacy of i-Scan for detection and diagnosis of gastric cancer. Ten patients diagnosed with early gastric cancer based on histopathological findings were analyzed. White light and i-Scan moving images recorded from these patients in twin mode were separated into white light and i-Scan. Twelve endoscopists (three different skill levels) blinded to patient information evaluated the images. Correlation between demarcation accuracy and lesion brightness on still images was investigated. No significant differences were found in diagnostic accuracy between white light and

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Yan, Shiyang, Yizhang Xia, Jeremy S. Smith, Wenjin Lu, and Bailing Zhang. "Multiscale Convolutional Neural Networks for Hand Detection." Applied Computational Intelligence and Soft Computing 2017 (2017): 1–13. http://dx.doi.org/10.1155/2017/9830641.

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Unconstrained hand detection in still images plays an important role in many hand-related vision problems, for example, hand tracking, gesture analysis, human action recognition and human-machine interaction, and sign language recognition. Although hand detection has been extensively studied for decades, it is still a challenging task with many problems to be tackled. The contributing factors for this complexity include heavy occlusion, low resolution, varying illumination conditions, different hand gestures, and the complex interactions between hands and objects or other hands. In this paper,

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CHANG, CHIN-CHEN, KUO-FENG HWANG, and MIN-SHIANG HWANG. "A FEATURE-ORIENTED COPYRIGHT OWNER PROVING TECHNIQUE FOR STILL IMAGES." International Journal of Software Engineering and Knowledge Engineering 12, no. 03 (2002): 317–30. http://dx.doi.org/10.1142/s0218194002000937.

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This paper presents a copyright owner detection technique for images and graphics. A digital time-stamped signature for this copyright identification technique is also introduced in this work. The secret key, used to compute the watermark, is generated from the extracted features of the host images in the proposed scheme. The proposed algorithm enables the successful revealing of watermarks under several attacks, such as filtering, lossy compression, cropping, rotating, and so on. In particular, our method is not only suitable for ordinary natural images, but can also be applied to cartoon gra

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Malinski, Lukasz, Krystian Radlak, and Bogdan Smolka. "Is large improvement in efficiency of impulsive noise removal in color images still possible?" PLOS ONE 16, no. 6 (2021): e0253117. http://dx.doi.org/10.1371/journal.pone.0253117.

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The substantial improvement in the efficiency of switching filters, intended for the removal of impulsive noise within color images is described. Numerous noisy pixel detection and replacement techniques are evaluated, where the filtering performance for color images and subsequent results are assessed using statistical reasoning. Denoising efficiency for the applied detection and interpolation techniques are assessed when the location of corrupted pixels are identified by noisy pixel detection algorithms and also in the scenario when they are already known. The results show that improvement i

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Song, Fengyi, Xiaoyang Tan, Xue Liu, and Songcan Chen. "Eyes closeness detection from still images with multi-scale histograms of principal oriented gradients." Pattern Recognition 47, no. 9 (2014): 2825–38. http://dx.doi.org/10.1016/j.patcog.2014.03.024.

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Soora, Narasimha Reddy, and Parag S. Deshpande. "Color, Scale, and Rotation Independent Multiple License Plates Detection in Videos and Still Images." Mathematical Problems in Engineering 2016 (2016): 1–14. http://dx.doi.org/10.1155/2016/9306282.

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Most of the existing license plate (LP) detection systems have shown significant development in the processing of the images, with restrictions related to environmental conditions and plate variations. With increased mobility and internationalization, there is a need to develop a universal LP detection system, which can handle multiple LPs of many countries and any vehicle, in an open environment and all weather conditions, having different plate variations. This paper presents a novel LP detection method using different clustering techniques based on geometrical properties of the LP character

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Wu, Wei-Hung, Jen-Chun Lee, and Yi-Ming Wang. "A Study of Defect Detection Techniques for Metallographic Images." Sensors 20, no. 19 (2020): 5593. http://dx.doi.org/10.3390/s20195593.

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Metallography is the study of the structure of metals and alloys. Metallographic analysis can be regarded as a detection tool to assist in identifying a metal or alloy, to evaluate whether an alloy is processed correctly, to inspect multiple phases within a material, to locate and characterize imperfections such as voids or impurities, or to find the damaged areas of metallographic images. However, the defect detection of metallography is evaluated by human experts, and its automatic identification is still a challenge in almost every real solution. Deep learning has been applied to different

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Tang, Guihua, Lei Sun, Xiuqing Mao, Song Guo, Hongmeng Zhang, and Xiaoqin Wang. "Detection of GAN-Synthesized Image Based on Discrete Wavelet Transform." Security and Communication Networks 2021 (June 15, 2021): 1–10. http://dx.doi.org/10.1155/2021/5511435.

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Recently, generative adversarial networks (GANs) and its variants have shown impressive ability in image synthesis. The synthesized fake images spread widely on the Internet, and it is challenging for Internet users to identify the authenticity, which poses huge security risk to the society. However, compared with the powerful image synthesis technology, the detection of GAN-synthesized images is still in its infancy and face a variety of challenges. In this study, a method named fake images discriminator (FID) is proposed, which detects that GAN-synthesized fake images use the strong spectral

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