Relevant bibliographies by topics / 2D images

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic '2D images'

Author: Grafiati
Published: 4 June 2021
Last updated: 13 July 2024

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Journal articles on the topic "2D images"

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Jung, Sukwoo, Seunghyun Song, Minho Chang, and Sangchul Park. "Range image registration based on 2D synthetic images." Computer-Aided Design 94 (January 2018): 16–27. http://dx.doi.org/10.1016/j.cad.2017.08.001.

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Tsalafoutas, Ioannis A., Angeliki C. Epistatou, and Konstantinos K. Delibasis. "Image Quality Comparison between Digital Breast Tomosynthesis Images and 2D Mammographic Images Using the CDMAM Test Object." Journal of Imaging 8, no. 8 (August 21, 2022): 223. http://dx.doi.org/10.3390/jimaging8080223.

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To evaluate the image quality (IQ) of synthesized two-dimensional (s2D) and tomographic layer (TL) mammographic images in comparison to the 2D digital mammographic images produced with a new digital breast tomosynthesis (DBT) system. Methods: The CDMAM test object was used for IQ evaluation of actual 2D images, s2D and TL images, acquired using all available acquisition modes. Evaluation was performed automatically using the commercial software that accompanied CDMAM. Results: The IQ scores of the TLs with the in-focus CDMAM were comparable, although usually inferior to those of 2D images acquired with the same acquisition mode, and better than the respective s2D images. The IQ results of TLs satisfied the EUREF limits applicable to 2D images, whereas for s2D images this was not the case. The use of high-dose mode (H-mode), instead of normal-dose mode (N-mode), increased the image quality of both TL and s2D images, especially when the standard mode (ST) was used. Although the high-resolution (HR) mode produced TL images of similar or better image quality compared to ST mode, HR s2D images were clearly inferior to ST s2D images. Conclusions: s2D images present inferior image quality compared to 2D and TL images. The HR mode produces TL images and s2D images with half the pixel size and requires a 25% increase in average glandular dose (AGD). Despite that, IQ evaluation results with CDMAM are in favor of HR resolution mode only for TL images and mainly for smaller-sized details.
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Plattard, Delphine, Marine Soret, Jocelyne Troccaz, Patrick Vassal, Jean-Yves Giraud, Guillaume Champleboux, Xavier Artignan, and Michel Bolla. "Patient Set-Up Using Portal Images: 2D/2D Image Registration Using Mutual Information." Computer Aided Surgery 5, no. 4 (January 2000): 246–62. http://dx.doi.org/10.3109/10929080009148893.

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Kim, Jin-Mo, Jong-Yoon Kim, and Hyung-Je Cho. "Warping of 2D Facial Images Using Image Interpolation by Triangle Subdivision." Journal of Korea Game Society 14, no. 2 (April 20, 2014): 55–66. http://dx.doi.org/10.7583/jkgs.2014.14.2.55.

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JIANG, C. F. "3D IMAGE RECONSTRUCTION OF OVARIAN TUMOR IN THE ULTRASONIC IMAGES." Biomedical Engineering: Applications, Basis and Communications 13, no. 02 (April 25, 2001): 93–98. http://dx.doi.org/10.4015/s1016237201000121.

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The prevalence of ovarian tumor malignancy can be monitored by the degree of irregularity in the ovarian contour and by the septal structure inside the tumor observed in ultrasonic images. However the 2D ultrasonic images can not integrate 3D information form the ovarian tumor. In this paper, we present an algorithm that can render the 3D image of an ovarian tumor by reconstructing the 2D ultrasonic images into a 3D data set. This is based on sequentially boundary detection in a series of 2D images to form a 3D tumor contour. This contour is then used as a barrier to remove the data containing the other tissue adhering to the tumor surface. The final 3D image rendered by the isolated data provides a clear view of both the surface and inner structure of the ovarian tumor.
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KOVALEVSKY, VLADIMIR. "CURVATURE IN DIGITAL 2D IMAGES." International Journal of Pattern Recognition and Artificial Intelligence 15, no. 07 (November 2001): 1183–200. http://dx.doi.org/10.1142/s0218001401001283.

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The paper presents an analysis of sources of errors when estimating derivatives of numerical or noisy functions. A method of minimizing the errors is suggested. When being applied to the estimation of the curvature of digital curves, the analysis shows that under the conditions typical for digital image processing the curvature can rarely be estimated with a precision higher than 50%. Ways of overcoming the difficulties are discussed and a new method for estimating the curvature is suggested and investigated as to its precision. The method is based on specifying boundaries of regions in gray value images with subpixel precision. The method has an essentially higher precision than the known methods.
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Kohnen, James B. "Images of Organization. 2d ed." Quality Management Journal 5, no. 2 (January 1998): 117. http://dx.doi.org/10.1080/10686967.1998.11918859.

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Kaczmarek, K., B. Walczak, S. de Jong, and B. G. M. Vandeginste. "Matching 2D Gel Electrophoresis Images." Journal of Chemical Information and Computer Sciences 43, no. 3 (May 2003): 978–86. http://dx.doi.org/10.1021/ci0256337.

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Bae, Kitae, and Hyoungjin Kim. "Optimal Point Correspondence for Image Registration in 2D Images." International Journal of Multimedia and Ubiquitous Engineering 8, no. 6 (November 30, 2013): 127–40. http://dx.doi.org/10.14257/ijmue.2013.8.6.13.

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Wang, Yong Sheng. "Fast 3D Human Face Modeling Method Based on Multiple View 2D Images." Applied Mechanics and Materials 273 (January 2013): 796–99. http://dx.doi.org/10.4028/www.scientific.net/amm.273.796.

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This paper presents a novel approach to model 3D human face from multiple view 2D images in a fast mode. Our proposed method mainly includes three steps: 1) Face Recognition from 2D images, 2) Converting 2D images to 3D images, 3) Modeling 3D human face. To extract visual features of both 2D and 3D images, visual features adopted in 3D are described by Point Signature, and visual features utilized in 2D is represented by Gabor filter responses. Afterwards, 3D model is obtained by combining multiple view 2D images through calculating projections vector and translation vector. Experimental results show that our method can model 3D human face with high accuracy and efficiency.
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Dissertations / Theses on the topic "2D images"

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Truong, Michael Vi Nguyen. "2D-3D registration of cardiac images." Thesis, King's College London (University of London), 2014. https://kclpure.kcl.ac.uk/portal/en/theses/2d3d-registration-of-cardiac-images(afef93e6-228c-4bc7-aab0-94f1e1ecf006).html.

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This thesis describes two novel catheter-based 2D-3D cardiac image registration algorithms for overlaying preoperative 3D MR or CT data onto intraoperative fluoroscopy, and fusing electroanatomical data onto clinical images. The work is intended for use in cardiac catheterisation procedures. To fulfil this objective, the algorithms must be accurate, robust and minimally disruptive to the clinical workflow. The first algorithm relies on the catheterisation of vessels of the heart and registers by minimising a vessel-radius-weighted distance between the catheters and corresponding vessel centrelines. A novelty here is a global-fit search strategy that considers all vessel branches during registration, adding robustness and avoiding manual branch selection. Another contribution to knowledge is an analysis of catheter configurations for registration. Results show that accuracy is highly dependent on the catheter configuration, and that using a coronary vessel (CV) with the aorta (Ao) was most accurate, yielding mean 3D target registration errors (TRE) between 0.55 and 7.0 mm with phantom data. Using two large-diameter vessels was least accurate, with TRE between 10 and 43 mm, and should be avoided. When applied to clinical data, registrations with the CV/Ao configuration resulted an estimated mean 2D-TRE of 5.9 mm, on average. The second 2D-3D registration algorithm extends the novelty of exploring catheter configurations by registering using catheters looped inside chambers of the heart. In phantom experiments, two-view registration yielded an average accuracy of 4.0 mm 3D-TRE (7.8-mm capture range). Using a single view, average reprojection distance was 2.7 mm (6.0-mm capture range). Application of the algorithm to a clinical dataset resulted in an estimated average 2D-TRE of 10 mm. Single view registrations are ideal when biplane X-ray acquisition is undesirable and for correcting bulk patient motion. In current practice, registration is performed manually. The algorithms in this thesis can register with comparable accuracy to manual registration, but are automated and can therefore fit better with the clinical workflow.
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Jones, Jonathan-Lee. "2D and 3D segmentation of medical images." Thesis, Swansea University, 2015. https://cronfa.swan.ac.uk/Record/cronfa42504.

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Cardiovascular disease is one of the leading causes of the morbidity and mortality in the western world today. Many different imaging modalities are in place today to diagnose and investigate cardiovascular diseases. Each of these, however, has strengths and weaknesses. There are different forms of noise and artifacts in each image modality that combine to make the field of medical image analysis both important and challenging. The aim of this thesis is develop a reliable method for segmentation of vessel structures in medical imaging, combining the expert knowledge of the user in such a way as to maintain efficiency whilst overcoming the inherent noise and artifacts present in the images. We present results from 2D segmentation techniques using different methodologies, before developing 3D techniques for segmenting vessel shape from a series of images. The main drive of the work involves the investigation of medical images obtained using catheter based techniques, namely Intra Vascular Ultrasound (IVUS) and Optical Coherence Tomography (OCT). We will present a robust segmentation paradigm, combining both edge and region information to segment the media-adventitia, and lumenal borders in those modalities respectively. By using a semi-interactive method that utilizes "soft" constraints, allowing imprecise user input which provides a balance between using the user's expert knowledge and efficiency. In the later part of the work, we develop automatic methods for segmenting the walls of lymph vessels. These methods are employed on sequential images in order to obtain data to reconstruct the vessel walls in the region of the lymph valves. We investigated methods to segment the vessel walls both individually and simultaneously, and compared the results both quantitatively and qualitatively in order obtain the most appropriate for the 3D reconstruction of the vessel wall. Lastly, we adapt the semi-interactive method used on vessels earlier into 3D to help segment out the lymph valve. This involved the user interactive method to provide guidance to help segment the boundary of the lymph vessel, then we apply a minimal surface segmentation methodology to provide segmentation of the valve.
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Guarnera, Giuseppe Claudio. "Shape Modeling and Description from 2D Images." Doctoral thesis, Università di Catania, 2013. http://hdl.handle.net/10761/1365.

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L'abilità di vedere degli umani e degli animali è il risultato di una complessa interazione della luce con gli occhi ed il cervello. Non siamo coscienti di quanto estremamente complessa sia l'analisi delle forme degli oggetti che viene svolta dal nostro cervello, poiché questa viene prevalentemente svolta a livello subconscio, senza la necessità di richiedere l'intervento di più elevato livelli cognitivi. Pertanto, sebbene "vedere e comprendere" sembri semplice e naturale, la realizzazione di un sistema di Computer Vision versatile e robusto è un compito difficile. Nell'era dei computer, il tentativo di imitare l'abilità umana di comprendere le forme ha portato alla nascita dei campi della Computer Vision e Pattern Recognition, motivato da importanti applicazioni in diversi campi. Coerentemente con la grande varietà di applicazioni, esiste un ampio spettro di possibili "occhi" che permettono ad un computer di "vedere", molto diversi dall'occhio umano (apparecchiature per tomografia, sensori ultrasonici, ecc.). Il ruolo predominante della forma degli oggetti, rispetto alle altre caratteristiche visuali, verrà enfatizzato nel corso di questa dissertazione, mostrando come tale caratteristica può essere utilizzata per risolvere una vasta gamma di problemi aperti nei campi della Computer Vision, Pattern Recognition e Computer Graphics. In quasi tutti i casi analizzati i dati in input sono costituiti da immagini bidimensionali, dimostrando che queste ultime contengo una quantità sufficiente di informazioni sulla forma degli oggetti raffigurati. I dispositivi tramite i quali le immagini sono state acquisite spaziano dalle Digital Still Cameras sino ai dispositivi per Risonanza Magnetica, con notevoli differenze quindi sia nelle tecnologie che nella qualità delle immagini prodotte. A partire da tali dati di input, nel corso di questa dissertazione verrà mostrato come modellare accuratamente la superficie 3D di un oggetto a partire da una analisi della polarizzazione della luce riflessa o come parametrizzare le forme usando dei descrittori di forma allo stato dell'arte, basati su proprietà statistiche delle classi di oggetti o semplicemente sulle singole superfici 3D o contorni degli oggetti.
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Sdiri, Bilel. "2D/3D Endoscopic image enhancement and analysis for video guided surgery." Thesis, Sorbonne Paris Cité, 2018. http://www.theses.fr/2018USPCD030.

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Grâce à l’évolution des procédés de diagnostiques médicaux et les développements technologiques, la chirurgie mini-invasive a fait des progrès remarquables au cours des dernières décennies surtout avec l’innovation de nouveaux outils médicaux tels que les systèmes chirurgicaux robotisés et les caméras endoscopiques sans fil. Cependant, ces techniques souffrent de quelques limitations liées essentiellement l’environnement endoscopique telles que la non uniformité de l’éclairage, les réflexions spéculaires des tissus humides, le faible contraste/netteté et le flou dû aux mouvements du chirurgien et du patient (i.e. la respiration). La correction de ces dégradations repose sur des critères de qualité d’image subjective et objective dans le contexte médical. Il est primordial de développer des solutions d’amélioration de la qualité perceptuelle des images acquises par endoscopie 3D. Ces solutions peuvent servir plus particulièrement dans l’étape d’extraction de points d’intérêts pour la reconstruction 3D des organes, qui sert à la planification de certaines opérations chirurgicales. C’est dans cette optique que cette thèse aborde le problème de la qualité des images endoscopiques en proposant de nouvelles méthodes d’analyse et de rehaussement de contraste des images endoscopiques 2D et 3D.Pour la détection et la classification automatique des anomalies tissulaires pour le diagnostic des maladies du tractus gastro-intestinal, nous avons proposé une méthode de rehaussement de contraste local et global des images endoscopiques 2D classiques et pour l’endoscopie capsulaire sans fil.La méthode proposée améliore la visibilité des structures locales fines et des détails de tissus. Ce prétraitement a permis de faciliter le processus de détection des points caractéristiques et d’améliorer le taux de classification automatique des tissus néoplasiques et tumeurs bénignes. Les méthodes développées exploitent également la propriété d’attention visuelle et de perception de relief en stéréovision. Dans ce contexte, nous avons proposé une technique adaptative d’amélioration de la qualité des images stéréo endoscopiques combinant l’information de profondeur et les contours des tissues. Pour rendre la méthode plus efficace et adaptée aux images 3Dl e rehaussement de contraste est ajusté en fonction des caractéristiques locales de l’image et du niveau de profondeur dans la scène tout en contrôlant le traitement inter-vues par un modèle de perception binoculaire.Un test subjectif a été mené pour évaluer la performance de l’algorithme proposé en termes de qualité visuelle des images générées par des observateurs experts et non experts dont les scores ont démontré l’efficacité de notre technique 3D d’amélioration du contraste. Dans cette même optique,nous avons développé une autre technique de rehaussement du contraste des images endoscopiques stéréo basée sur la décomposition en ondelettes.Ce qui offre la possibilité d’effectuer un traitement multi-échelle et d’opérer une traitement sélectif. Le schéma proposé repose sur un traitement stéréo qui exploite à la fois l’informations de profondeur et les redondances intervues,ainsi que certaines propriétés du système visuel humain, notamment la sensibilité au contraste et à la rivalité/combinaison binoculaire. La qualité visuelle des images traitées et les mesures de qualité objective démontrent l’efficacité de notre méthode qui ajuste l’éclairage des images dans les régions sombres et saturées et accentue la visibilité des détails liés aux vaisseaux sanguins et les textures de tissues
Minimally invasive surgery has made remarkable progress in the last decades and became a very popular diagnosis and treatment tool, especially with the rapid medical and technological advances leading to innovative new tools such as robotic surgical systems and wireless capsule endoscopy. Due to the intrinsic characteristics of the endoscopic environment including dynamic illumination conditions and moist tissues with high reflectance, endoscopic images suffer often from several degradations such as large dark regions,with low contrast and sharpness, and many artifacts such as specular reflections and blur. These challenges together with the introduction of three dimensional(3D) imaging surgical systems have prompted the question of endoscopic images quality, which needs to be enhanced. The latter process aims either to provide the surgeons/doctors with a better visual feedback or improve the outcomes of some subsequent tasks such as features extraction for 3D organ reconstruction and registration. This thesis addresses the problem of endoscopic image quality enhancement by proposing novel enhancement techniques for both two-dimensional (2D) and stereo (i.e. 3D)endoscopic images.In the context of automatic tissue abnormality detection and classification for gastro-intestinal tract disease diagnosis, we proposed a pre-processing enhancement method for 2D endoscopic images and wireless capsule endoscopy improving both local and global contrast. The proposed method expose inner subtle structures and tissues details, which improves the features detection process and the automatic classification rate of neoplastic,non-neoplastic and inflammatory tissues. Inspired by binocular vision attention features of the human visual system, we proposed in another workan adaptive enhancement technique for stereo endoscopic images combining depth and edginess information. The adaptability of the proposed method consists in adjusting the enhancement to both local image activity and depth level within the scene while controlling the interview difference using abinocular perception model. A subjective experiment was conducted to evaluate the performance of the proposed algorithm in terms of visual qualityby both expert and non-expert observers whose scores demonstrated the efficiency of our 3D contrast enhancement technique. In the same scope, we resort in another recent stereo endoscopic image enhancement work to the wavelet domain to target the enhancement towards specific image components using the multiscale representation and the efficient space-frequency localization property. The proposed joint enhancement methods rely on cross-view processing and depth information, for both the wavelet decomposition and the enhancement steps, to exploit the inter-view redundancies together with perceptual human visual system properties related to contrast sensitivity and binocular combination and rivalry. The visual qualityof the processed images and objective assessment metrics demonstrate the efficiency of our joint stereo enhancement in adjusting the image illuminationin both dark and saturated regions and emphasizing local image details such as fine veins and micro vessels, compared to other endoscopic enhancement techniques for 2D and 3D images
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Meng, Ting, and Yating Yu. "Deconvolution algorithms of 2D Transmission Electron Microscopy images." Thesis, KTH, Optimeringslära och systemteori, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-110096.

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The purpose of this thesis is to develop a mathematical approach and associated software implementation for deconvolution of two-dimensional Transmission Electron Microscope (TEM) images. The focus is on TEM images of weakly scattering amorphous biological specimens that mainly produce phase contrast. The deconvolution is to remove the distortions introduced by the TEM detector that are modeled by the Modulation Transfer Function (MTF). The report tests deconvolution of the TEM detector MTF by Wiener _ltering and Tikhonov regularization on a range of simulated TEM images with varying degree of noise.The performance of the two deconvolution methods are quanti_ed by means of Figure of Merits (FOMs) and comparison in-between methods is based on statistical analysis of the FOMs.
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Huang, Hui. "Efficient reconstruction of 2D images and 3D surfaces." Thesis, University of British Columbia, 2008. http://hdl.handle.net/2429/2821.

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The goal of this thesis is to gain a deep understanding of inverse problems arising from 2D image and 3D surface reconstruction, and to design effective techniques for solving them. Both computational and theoretical issues are studied and efficient numerical algorithms are proposed. The first part of this thesis is concerned with the recovery of 2D images, e.g., de-noising and de-blurring. We first consider implicit methods that involve solving linear systems at each iteration. An adaptive Huber regularization functional is used to select the most reasonable model and a global convergence result for lagged diffusivity is proved. Two mechanisms---multilevel continuation and multigrid preconditioning---are proposed to improve efficiency for large-scale problems. Next, explicit methods involving the construction of an artificial time-dependent differential equation model followed by forward Euler discretization are analyzed. A rapid, adaptive scheme is then proposed, and additional hybrid algorithms are designed to improve the quality of such processes. We also devise methods for more challenging cases, such as recapturing texture from a noisy input and de-blurring an image in the presence of significant noise. It is well-known that extending image processing methods to 3D triangular surface meshes is far from trivial or automatic. In the second part of this thesis we discuss techniques for faithfully reconstructing such surface models with different features. Some models contain a lot of small yet visually meaningful details, and typically require very fine meshes to represent them well; others consist of large flat regions, long sharp edges (creases) and distinct corners, and the meshes required for their representation can often be much coarser. All of these models may be sampled very irregularly. For models of the first class, we methodically develop a fast multiscale anisotropic Laplacian (MSAL) smoothing algorithm. To reconstruct a piecewise smooth CAD-like model in the second class, we design an efficient hybrid algorithm based on specific vertex classification, which combines K-means clustering and geometric a priori information. Hence, we have a set of algorithms that efficiently handle smoothing and regularization of meshes large and small in a variety of situations.
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Henrichsen, Arne. "3D reconstruction and camera calibration from 2D images." Master's thesis, University of Cape Town, 2000. http://hdl.handle.net/11427/9725.

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A 3D reconstruction technique from stereo images is presented that needs minimal intervention from the user. The reconstruction problem consists of three steps, each of which is equivalent to the estimation of a specific geometry group. The first step is the estimation of the epipolar geometry that exists between the stereo image pair, a process involving feature matching in both images. The second step estimates the affine geometry, a process of finding a special plane in projective space by means of vanishing points. Camera calibration forms part of the third step in obtaining the metric geometry, from which it is possible to obtain a 3D model of the scene. The advantage of this system is that the stereo images do not need to be calibrated in order to obtain a reconstruction. Results for both the camera calibration and reconstruction are presented to verify that it is possible to obtain a 3D model directly from features in the images.
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Agerskov, Niels, and Gabriel Carrizo. "Application for Deriving 2D Images from 3D CT Image Data for Research Purposes." Thesis, KTH, Skolan för teknik och hälsa (STH), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-190881.

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Karolinska University Hospital, Huddinge, Sweden, has long desired to plan hip prostheses with Computed Tomography (CT) scans instead of plain radiographs to save time and patient discomfort. This has not been possible previously as their current software is limited to prosthesis planning on traditional 2D X-ray images. The purpose of this project was therefore to create an application (software) that allows medical professionals to derive a 2D image from CT images that can be used for prosthesis planning. In order to create the application NumPy and The Visualization Toolkit (VTK) Python code libraries were utilised and tied together with a graphical user interface library called PyQt4. The application includes a graphical interface and methods for optimizing the images for prosthesis planning. The application was finished and serves its purpose but the quality of the images needs to be evaluated with a larger sample group.
På Karolinska universitetssjukhuset, Huddinge har man länge önskat möjligheten att utföra mallningar av höftproteser med hjälp av data från datortomografiundersökningar (DT). Detta har hittills inte varit möjligt eftersom programmet som används för mallning av höftproteser enbart accepterar traditionella slätröntgenbilder. Därför var syftet med detta projekt att skapa en mjukvaru-applikation som kan användas för att generera 2D-bilder för mallning av proteser från DT-data. För att skapa applikationen användes huvudsakligen Python-kodbiblioteken NumPy och The Visualization Toolkit (VTK) tillsammans med användargränssnittsbiblioteket PyQt4. I applikationen ingår ett grafiskt användargränssnitt och metoder för optimering av bilderna i mallningssammanhang. Applikationen fungerar men bildernas kvalitet måste utvärderas med en större urvalsgrupp.
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Srinivasan, Nirmala. "Cross-Correlation Of Biomedical Images Using Two Dimensional Discrete Hermite Functions." University of Akron / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=akron1341866987.

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Bowden, Nathan Charles. "Camera based texture mapping: 3D applications for 2D images." Texas A&M University, 2005. http://hdl.handle.net/1969.1/2407.

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This artist??s area of research is the appropriate use of matte paintings within the context of completely computer generated films. The emphasis of research is the adaptation of analog techniques and paradigms into a digital production workspace. The purpose of this artist??s research is the development of an original method of parenting perspective projections to three-dimensional (3D) cameras, specifically tailored to result in 3D matte paintings. Research includes the demonstration of techniques combining two-dimensional (2D) paintings, 3D props and sets, as well as camera projections onto primitive geometry to achieve a convincing final composite.
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Books on the topic "2D images"

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Jones, Alun Gwyn. Recovering 3D shape from 2D images. Manchester: University of Manchester, 1995.

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Edexcel, ed. Art and Design.GNVQ Intermediate.Unit 1:2D and 3D Visual Language.Student Preparatory Work (Pre-seen Images). January 2003. London: Edexcel, 2001.

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Cappellini, Vito, ed. Electronic Imaging & the Visual Arts. EVA 2013 Florence. Florence: Firenze University Press, 2013. http://dx.doi.org/10.36253/978-88-6655-372-4.

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Important Information Technology topics are presented: multimedia systems, data-bases, protection of data, access to the content. Particular reference is reserved to digital images (2D, 3D) regarding Cultural Institutions (Museums, Libraries, Palace – Monuments, Archaeological Sites). The main parts of the Conference Proceedings regard: Strategic Issues, EC Projects and Related Networks & Initiatives, International Forum on “Culture & Technology”, 2D – 3D Technologies & Applications, Virtual Galleries – Museums and Related Initiatives, Access to the Culture Information. Three Workshops are related to: International Cooperation, Innovation and Enterprise, Creative Industries and Cultural Tourism.
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Cappellini, Vito, ed. Electronic Imaging & the Visual Arts. EVA 2015 Florence. Florence: Firenze University Press, 2015. http://dx.doi.org/10.36253/978-88-6655-759-3.

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Information Technologies of interest for Culture Heritage are presented: multimedia systems, data-bases, data protection, access to digital content, Virtual Galleries. Particular reference is reserved to digital images (Electronic Imaging & the Visual Arts), regarding Cultural Institutions (Museums, Libraries, Palace – Monuments, Archaeological Sites). The International Conference includes the following Sessions: Strategic Issues; New Technologies & Applications; New 2D-3D Technical Developments & Applications; Virtual Galleries – Museums and Related Initiatives; Access to the Culture Information. Two Workshops regard: International Cooperation; Innovation and Enterprise.
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Cappellini, Vito, ed. Electronic Imaging & the Visual Arts. EVA 2014 Florence. Florence: Firenze University Press, 2014. http://dx.doi.org/10.36253/978-88-6655-573-5.

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Information Technologies of interest for Culture Heritage are presented: multimedia systems, data-bases, data protection, access to digital content, Virtual Galleries. Particular reference is reserved to digital images (Electronic Imaging & the Visual Arts), regarding Cultural Institutions (Museums, Libraries, Palace - Monuments, Archaeological Sites). The International Conference includes the following Sessions: Strategic Issues; EC Projects and Related Networks & Initiatives; 2D - 3D Technologies and Applications; Virtual Galleries - Museums and Related Initiatives; Access to the Culture Information. Three Workshops regard: International Cooperation; Innovation and Enterprise; e.Culture Cloud.
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Flusser, Jan, Tomáš Suk, and Barbara Zitová. 2D and 3D Image Analysis by Moments. Chichester, UK: John Wiley & Sons, Ltd, 2016. http://dx.doi.org/10.1002/9781119039402.

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Watson, Kenneth. A 2D FFT filtering program for image processing with examples. [Denver, CO]: U.S. Dept. of the Interior, Geological Survey, 1992.

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Wosnitza, Matthias Werner. High precision 1024-point FFT processor for 2D object detection. Hartung-Gorre: Konstanz, 1999.

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Kumar, Sandeep, Shilpa Rani, and K. Ramya Laxmi. Artificial Intelligence and Machine Learning in 2D/3D Medical Image Processing. Edited by Rohit Raja. First edition. | Boca Raton: CRC Press, 2021.: CRC Press, 2020. http://dx.doi.org/10.1201/9780429354526.

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Jamie, Oliff, ed. Thinking animation: Bridging the gap between 2D and CG. Boston, MA: Thomson Course Technology, 2007.

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Book chapters on the topic "2D images"

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Arheit, Marcel, Daniel Castaño-Díez, Raphaël Thierry, Bryant R. Gipson, Xiangyan Zeng, and Henning Stahlberg. "Image Processing of 2D Crystal Images." In Methods in Molecular Biology, 171–94. Totowa, NJ: Humana Press, 2012. http://dx.doi.org/10.1007/978-1-62703-176-9_10.

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Nakanishi, Tomoko M. "3D Images." In Novel Plant Imaging and Analysis, 191–96. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4992-6_6.

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AbstractSpatial (3D) image construction from imaging plate (IP) images and the development of the microautography (MAR) method were presented. A rice grain was sliced every 5 μm, IP images were taken for successive slices, and the series of 2D images acquired by an IP were used to construct 3D images. In the case of 109Cd and 137Cs, the spatial distributions in the grain showed that the concentrations increased at the surface of the grain during the maturing process.
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Kimmel, Ron. "2D and 3D Image Segmentation." In Numerical Geometry of Images, 123–40. New York, NY: Springer New York, 2004. http://dx.doi.org/10.1007/978-0-387-21637-9_9.

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Kovalevsky, Vladimir. "Edge Detection in 2D Images." In Image Processing with Cellular Topology, 113–38. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-5772-6_6.

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Muresan, Lucian. "2D → 2D geometric transformation invariant to arbitrary translations, rotations and scales." In Computer Analysis of Images and Patterns, 90–97. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/3-540-63460-6_104.

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Liu, Chuan, Jiaqi Shen, Yue Ren, and Hao Zheng. "Pipes of AI – Machine Learning Assisted 3D Modeling Design." In Proceedings of the 2020 DigitalFUTURES, 17–26. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4400-6_2.

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AbstractStyle transfer is a design technique that is based on Artificial Intelligence and Machine Learning, which is an innovative way to generate new images with the intervention of style images. The output image will carry the characteristic of style image and maintain the content of the input image. However, the design technique is employed in generating 2D images, which has a limited range in practical use. Thus, the goal of the project is to utilize style transfer as a toolset for architectural design and find out the possibility for a 3D modeling design. To implement style transfer into the research, floor plans of different heights are selected from a given design boundary and set as the content images, while a framework of a truss structure is set as the style image. Transferred images are obtained after processing the style transfer neural network, then the geometric images are translated into floor plans for new structure design. After the selection of the tilt angle and the degree of density, vertical components that connecting two adjacent layers are generated to be the pillars of the structure. At this stage, 2D style transferred images are successfully transformed into 3D geometries, which can be applied to the architectural design processes. Generally speaking, style transfer is an intelligent design tool that provides architects with a variety of choices of idea-generating. It has the potential to inspire architects at an early stage of design with not only 2D but also 3D format.
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Takayama, Natsuki, Shubing Meng, and Takahashi Hiroki. "Choshi Design System from 2D Images." In Lecture Notes in Computer Science, 358–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15399-0_38.

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Bruijn, Norbert P., and Fiona M. Clements. "Quantitative Analysis of 2D Echocardiography Images." In Transesophageal Echocardiography, 85–118. Boston, MA: Springer US, 1987. http://dx.doi.org/10.1007/978-1-4613-2025-8_5.

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Yang, Chuan-Kai, and Chia-Ning Kuo. "Automatically Extracting Hairstyles from 2D Images." In Advances in Visual Computing, 406–15. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41939-3_39.

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Korres, Georgios, and Mohamad Eid. "Touching 2D Images Using Haptogram System." In Lecture Notes in Electrical Engineering, 71–73. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4157-0_12.

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Conference papers on the topic "2D images"

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Brown, Michael S., and W. Brent Seales. "Beyond 2D images." In the fifth ACM conference. New York, New York, USA: ACM Press, 2000. http://dx.doi.org/10.1145/336597.336623.

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Sikander Hayat Khiyal, Malik, Aihab Khan, and Amna Bibi. "Modified Watershed Algorithm for Segmentation of 2D Images." In InSITE 2009: Informing Science + IT Education Conference. Informing Science Institute, 2009. http://dx.doi.org/10.28945/3349.

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With the repaid advancement of computer technology, the use of computer-based technologies is increasing in different fields of life. Image segmentation is an important problem in different fields of image processing and computer vision. Image segmentation is the process of dividing images according to its characteristic e.g., color and objects present in the images. Different methods are presented for image segmentation. The focus of this study is the watershed segmentation. The tool used in this study is MATLAB. Good result of watershed segmentation entirely relay on the image contrast. Image contrast may be degraded during image acquisition. Watershed algorithm can generate over segmentation or under segmentation on badly contrast images. In order to reduce these deficiencies of watershed algorithm a preprocessing step using Random Walk method is performed on input images. Random Walk method is a probabilistic approach, which improves the image contrast in the way image is degraded.
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S, Vaishnavi A., and Sumana M. "Evolution of 3D images from 2D images." In 2021 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT). IEEE, 2021. http://dx.doi.org/10.1109/conecct52877.2021.9622698.

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Rasool, Shahzad, and Alexei Sourin. "Haptic interaction with 2D images." In the 10th International Conference. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/2087756.2087758.

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Erturk, Rumeysa Ashhan, and Mustafa Ersel Karnasak. "Anthropometric Measurements with 2D Images." In 2022 7th International Conference on Computer Science and Engineering (UBMK). IEEE, 2022. http://dx.doi.org/10.1109/ubmk55850.2022.9919504.

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Sabharwal, Chaman L. "Recovering 3D image parameters from corresponding two 2D images." In the 1993 ACM/SIGAPP symposium. New York, New York, USA: ACM Press, 1993. http://dx.doi.org/10.1145/162754.162948.

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Santos Ferrer, Juan C., David González Chévere, and Vidya Manian. "Photorealistic image synthesis and camera validation from 2D images." In SPIE Sensing Technology + Applications, edited by Bahram Javidi, Jung-Young Son, Osamu Matoba, Manuel Martínez-Corral, and Adrian Stern. SPIE, 2014. http://dx.doi.org/10.1117/12.2050916.

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Son, Minjung, Henry Kang, Yunjin Lee, and Seungyong Lee. "Abstract Line Drawings from 2D Images." In 15th Pacific Conference on Computer Graphics and Applications (PG'07). IEEE, 2007. http://dx.doi.org/10.1109/pg.2007.63.

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Widanagamaachchi, W. N., and A. T. Dharmaratne. "3D Face Reconstruction from 2D Images." In 2008 Digital Image Computing: Techniques and Applications. IEEE, 2008. http://dx.doi.org/10.1109/dicta.2008.83.

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Li Yuan and Zhi-chun Mu. "Ear Recognition based on 2D Images." In 2007 First IEEE International Conference on Biometrics: Theory, Applications, and Systems. IEEE, 2007. http://dx.doi.org/10.1109/btas.2007.4401941.

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Reports on the topic "2D images"

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Basri, Ronen, and Daphna Weinshall. Distance Metric between 3D Models and 2D Images for Recognition and Classification. Fort Belvoir, VA: Defense Technical Information Center, July 1992. http://dx.doi.org/10.21236/ada260069.

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Hanson, Allen R. Recognizing 3 D Objects from 2D Images Using Structural Knowledge Base of Genetic Views. Fort Belvoir, VA: Defense Technical Information Center, August 1988. http://dx.doi.org/10.21236/ada207875.

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Arroyo, Marcos, Riccardo Rorato, Marco Previtali, and Matteo Ciantia. 2D Image-based calibration of rolling resistance in 3D discrete element models of sand. University of Dundee, December 2021. http://dx.doi.org/10.20933/100001229.

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Contact rolling resistance is the most widely used method to incorporate particle shape effects in the discrete element method (DEM). The main reason for this is that such approach allows for using spherical particles hence offering substantial computational benefits compared to non-spherical DEM models. This paper shows how rolling resistance parameters for 3D DEM models can be easily calibrated with 2D sand grain images.
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Riedel, Michael, Jörg Bialas, Elisa Klein, Cord Papenberg, and Janine Berndt. Technical Report for Raw 2D MCS Reflection Data, R/V Sonne Cruise 294, Vancouver (Canada) – Port Hueneme (USA), 13/09/22 – 27/10/23. GEOMAR Helmholtz Centre for Ocean Research Kiel, Germany, 2024. http://dx.doi.org/10.3289/tr_2d-mcs_so294.

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The raw 2D multichannel seismic reflection data in this project were acquired during expedition SO294 offshore Vancouver Island, Canada, using two different sources, i.e., a single GI Gun and a GGun array. The data were recorded with an 184-channel streamer. The objectives of expedition SO294 were twofold: provision of geophysical images to constrain the hazard potential of the Cascadia subduction zone, and to constrain the geophysical properties of the oceanic crust to assess its storage potential for carbon capture and storage (CCS). The data comprise 1660 line kilometers and are provided in raw format (SEG-D) and associated standardized metadata. Detailed information on the acquisition can be found in the SO294 cruise report (https://doi.org/10.48433/cr_so294). In addition, this technical report is provided with the 2D multichannel seismic reflection data set.
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Decroux, Agnes, Kassem Kalo, and Keith Swinden. PR-393-205100-R01 IRIS X-Ray CT Qualification for Flexible Pipe Inspection (Phase 1). Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), March 2021. http://dx.doi.org/10.55274/r0012068.

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There are several techniques available to inspect single wall carbon steel pipelines including; Magnetic flux leakage (MFL), ultrasonic testing (UT), Electro-Magnetic Acoustic Transducer (EMAT), Phased Array, guide wave testing (GWT), etc. However, for more complex structures such as flexible pipelines the technology available to inspect them is far more limited. PRCI commissioned a program (SPIM 2-1) under the Subsea TC (2017-2020) to evaluate all known and suspected technologies that could be used to provide a detailed subsea inspection of a flexible riser. PRCI produced four samples of flexible pipe containing pre-manufactured cracks and corrosion defects which were located in; the outer armour layer, inner armour layer, pressure vault and carcass. The samples were used for blind testing of all identified inspection technologies. On conclusion of the SPIM 2-1 program, HR-XCT was identified as the technology showing the most promise and a follow-on program (SPIM 2-2) was commissioned to further explore the capabilities. This report will show the way in which high resolution image clarity and image manipulation was extracted from the HR-XCT system when used on the PRCI flexible pipe samples. The XCT results from SPIM 2-2 will be presented to show the initial setup of the experiment and 2D and 3D high resolution sectioned images from the testing. These images clearly identify and characterize 100% of the pre-manufactured defects introduced into the samples in all layers.
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Midak, Liliia Ya, Ivan V. Kravets, Olga V. Kuzyshyn, Khrystyna V. Berladyniuk, Khrystyna V. Buzhdyhan, Liliia V. Baziuk, and Aleksandr D. Uchitel. Augmented reality in process of studying astronomic concepts in primary school. [б. в.], November 2020. http://dx.doi.org/10.31812/123456789/4411.

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The objective of the research is development a mobile application (on the Android platform) designed for visualization of the Solar System with the AR technology and the alphabet study, applying the astronomic definitions, which can be used by the teacher and the students for an effective training for studying the subjects of the astronomic cycle in primary school. Augmented Reality cards with the images of the Solar System planets and other celestial bodies were developed, as well as the “Space alphabet” was created. In the developed alphabet every letter of the alphabet becomes a certain celestial body or a different astronomic definition. Augmented Reality gives the opportunity to visualize images of the Solar System as much as possible, in other words to convert 2D images into 3D, as well as “make them alive”. Applying this tool of ICT while studying new data gives the ability to develop and improve the pupils’ spatial thinking, “to see” the invisible and to understand the perceived information in a deeper way, which will be beneficial for its better memorizing and development of computer skills. Studying the alphabet in the offered mobile app will definitely help nail the achieved knowledge and get interesting information about celestial bodies that are invisible and superior for kids; to make a journey into the space, prepare a project on “The Space Mysteries” subject; to stimulate the development of curiosity, cognitive motivation and learning activity; the development of imagination, creative initiative, including speaking out.
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Creighton, Dan. X-ray diffraction, x-ray fluorescence, pyrolysis, source rock analysis, 2D SEM images from cuttings for wells: Malguk 1, Merak 1, Pipeline State 1, West Kavik 1, and Wolfbutton 25-6-9. Alaska Division of Geological & Geophysical Surveys, July 2020. http://dx.doi.org/10.14509/30533.

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WEHLBURG, JOSEPH C., CHRISTINE M. WEHLBURG, JODY L. SMITH, OLGA B. SPAHN, MARK W. SMITH, and CRAIG M. BONEY. High Speed 2D Hadamard Transform Spectral Imager. Office of Scientific and Technical Information (OSTI), February 2003. http://dx.doi.org/10.2172/808596.

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Anderson, Gerald L., and Kalman Peleg. Precision Cropping by Remotely Sensed Prorotype Plots and Calibration in the Complex Domain. United States Department of Agriculture, December 2002. http://dx.doi.org/10.32747/2002.7585193.bard.

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This research report describes a methodology whereby multi-spectral and hyperspectral imagery from remote sensing, is used for deriving predicted field maps of selected plant growth attributes which are required for precision cropping. A major task in precision cropping is to establish areas of the field that differ from the rest of the field and share a common characteristic. Yield distribution f maps can be prepared by yield monitors, which are available for some harvester types. Other field attributes of interest in precision cropping, e.g. soil properties, leaf Nitrate, biomass etc. are obtained by manual sampling of the filed in a grid pattern. Maps of various field attributes are then prepared from these samples by the "Inverse Distance" interpolation method or by Kriging. An improved interpolation method was developed which is based on minimizing the overall curvature of the resulting map. Such maps are the ground truth reference, used for training the algorithm that generates the predicted field maps from remote sensing imagery. Both the reference and the predicted maps are stratified into "Prototype Plots", e.g. 15xl5 blocks of 2m pixels whereby the block size is 30x30m. This averaging reduces the datasets to manageable size and significantly improves the typically poor repeatability of remote sensing imaging systems. In the first two years of the project we used the Normalized Difference Vegetation Index (NDVI), for generating predicted yield maps of sugar beets and com. The NDVI was computed from image cubes of three spectral bands, generated by an optically filtered three camera video imaging system. A two dimensional FFT based regression model Y=f(X), was used wherein Y was the reference map and X=NDVI was the predictor. The FFT regression method applies the "Wavelet Based", "Pixel Block" and "Image Rotation" transforms to the reference and remote images, prior to the Fast - Fourier Transform (FFT) Regression method with the "Phase Lock" option. A complex domain based map Yfft is derived by least squares minimization between the amplitude matrices of X and Y, via the 2D FFT. For one time predictions, the phase matrix of Y is combined with the amplitude matrix ofYfft, whereby an improved predicted map Yplock is formed. Usually, the residuals of Y plock versus Y are about half of the values of Yfft versus Y. For long term predictions, the phase matrix of a "field mask" is combined with the amplitude matrices of the reference image Y and the predicted image Yfft. The field mask is a binary image of a pre-selected region of interest in X and Y. The resultant maps Ypref and Ypred aremodified versions of Y and Yfft respectively. The residuals of Ypred versus Ypref are even lower than the residuals of Yplock versus Y. The maps, Ypref and Ypred represent a close consensus of two independent imaging methods which "view" the same target. In the last two years of the project our remote sensing capability was expanded by addition of a CASI II airborne hyperspectral imaging system and an ASD hyperspectral radiometer. Unfortunately, the cross-noice and poor repeatability problem we had in multi-spectral imaging was exasperated in hyperspectral imaging. We have been able to overcome this problem by over-flying each field twice in rapid succession and developing the Repeatability Index (RI). The RI quantifies the repeatability of each spectral band in the hyperspectral image cube. Thereby, it is possible to select the bands of higher repeatability for inclusion in the prediction model while bands of low repeatability are excluded. Further segregation of high and low repeatability bands takes place in the prediction model algorithm, which is based on a combination of a "Genetic Algorithm" and Partial Least Squares", (PLS-GA). In summary, modus operandi was developed, for deriving important plant growth attribute maps (yield, leaf nitrate, biomass and sugar percent in beets), from remote sensing imagery, with sufficient accuracy for precision cropping applications. This achievement is remarkable, given the inherently high cross-noice between the reference and remote imagery as well as the highly non-repeatable nature of remote sensing systems. The above methodologies may be readily adopted by commercial companies, which specialize in proving remotely sensed data to farmers.
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Habib, Ayman, Darcy M. Bullock, Yi-Chun Lin, and Raja Manish. Road Ditch Line Mapping with Mobile LiDAR. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317354.

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Maintenance of roadside ditches is important to avoid localized flooding and premature failure of pavements. Scheduling effective preventative maintenance requires mapping of the ditch profile to identify areas requiring excavation of long-term sediment accumulation. High-resolution, high-quality point clouds collected by mobile LiDAR mapping systems (MLMS) provide an opportunity for effective monitoring of roadside ditches and performing hydrological analyses. This study evaluated the applicability of mobile LiDAR for mapping roadside ditches for slope and drainage analyses. The performance of alternative MLMS units was performed. These MLMS included an unmanned ground vehicle, an unmanned aerial vehicle, a portable backpack system along with its vehicle-mounted version, a medium-grade wheel-based system, and a high-grade wheel-based system. Point cloud from all the MLMS units were in agreement in the vertical direction within the ±3 cm range for solid surfaces, such as paved roads, and ±7 cm range for surfaces with vegetation. The portable backpack system that could be carried by a surveyor or mounted on a vehicle and was the most flexible MLMS. The report concludes that due to flexibility and cost effectiveness of the portable backpack system, it is the preferred platform for mapping roadside ditches, followed by the medium-grade wheel-based system. Furthermore, a framework for ditch line characterization is proposed and tested using datasets acquired by the medium-grade wheel-based and vehicle-mounted portable systems over a state highway. An existing ground filtering approach is modified to handle variations in point density of mobile LiDAR data. Hydrological analyses, including flow direction and flow accumulation, are applied to extract the drainage network from the digital terrain model (DTM). Cross-sectional/longitudinal profiles of the ditch are automatically extracted from LiDAR data and visualized in 3D point clouds and 2D images. The slope derived from the LiDAR data was found to be very close to highway cross slope design standards of 2% on driving lanes, 4% on shoulders, as well as 6-by-1 slope for ditch lines. Potential flooded regions are identified by detecting areas with no LiDAR return and a recall score of 54% and 92% was achieved by the medium-grade wheel-based and vehicle-mounted portable systems, respectively. Furthermore, a framework for ditch line characterization is proposed and tested using datasets acquired by the medium-grade wheel-based and vehicle-mounted portable systems over a state highway. An existing ground filtering approach is modified to handle variations in point density of mobile LiDAR data. Hydrological analyses, including flow direction and flow accumulation, are applied to extract the drainage network from the digital terrain model (DTM). Cross-sectional/longitudinal profiles of the ditch are automatically extracted from LiDAR data, and visualized in 3D point clouds and 2D images. The slope derived from the LiDAR data was found to be very close to highway cross slope design standards of 2% on driving lanes, 4% on shoulder, as well as 6-by-1 slope for ditch lines. Potential flooded regions are identified by detecting areas with no LiDAR return and a recall score of 54% and 92% was achieved by the medium-grade wheel-based and vehicle-mounted portable systems, respectively.
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