Bibliografías temáticas / Image processing

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Literatura académica sobre el tema "Image processing"

Autor: Grafiati
Publicado: 4 de junio de 2021
Última modificación: 25 de julio de 2025

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Artículos de revistas sobre el tema "Image processing"

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Shete, S. G., and Nagnath G. Ghadge. "Image Processing in MATLAB 9.3." International Journal of Trend in Scientific Research and Development 2, no. 2 (2018): 925–29. https://doi.org/10.31142/ijtsrd9545.

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In this paper we introduce how to handle different kinds of image formats in MATLAB 9.3 by using Matlab Workspace and its Various Commands. Also we illustrated example of processing the images. Shete S. G. | Ghadge Nagnath G. "Image Processing in MATLAB 9.3" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-2 , February 2018, URL: https://www.ijtsrd.com/papers/ijtsrd9545.pdf
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Mohamed Y Abdallah, Yousif, Mohamed MO Yousef, and Eltayeb W Eltayeb. "Automated Enhancement of Myocardium Images using Image Processing Methods." International Journal of Science and Research (IJSR) 10, no. 7 (2021): 557–64. https://doi.org/10.21275/sr21709185141.

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Peng, Er Bao, and Guo Tong Zhang. "Image Processing Technology Research of On-Line Thread Processing." Advanced Materials Research 908 (March 2014): 555–58. http://dx.doi.org/10.4028/www.scientific.net/amr.908.555.

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The paper introduced image processing technology based on image segmentation about on-line threads images, and describes in detail image processing technology from image preprocessing, image gmentation,and threaded parameter test. Threaded images of on-line processing parts obtained are introduced as the key technology, Target edge extraction process from the segmented image are also recounted. At last, this article shows a comparison between actual machining parameters of screw thread and the standard parameter , provides the criterion for error compensation.
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Legland, David, and Marie-Françoise Devaux. "ImageM: a user-friendly interface for the processing of multi-dimensional images with Matlab." F1000Research 10 (April 30, 2021): 333. http://dx.doi.org/10.12688/f1000research.51732.1.

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Modern imaging devices provide a wealth of data often organized as images with many dimensions, such as 2D/3D, time and channel. Matlab is an efficient software solution for image processing, but it lacks many features facilitating the interactive interpretation of image data, such as a user-friendly image visualization, or the management of image meta-data (e.g. spatial calibration), thus limiting its application to bio-image analysis. The ImageM application proposes an integrated user interface that facilitates the processing and the analysis of multi-dimensional images within the Matlab env
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Goto, Mitsunori. "8. Image Processing Using ImageJ." Japanese Journal of Radiological Technology 75, no. 7 (2019): 688–92. http://dx.doi.org/10.6009/jjrt.2019_jsrt_75.7.688.

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Arti Verma. "Digital Image Processing of SEM image of Polymer Nanocomposite Thin Film Using Java Based Program Image J." Power System Technology 43, no. 2 (2019): 44–46. https://doi.org/10.52783/pst.1135.

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Various images obtain from TEM; SEM can be analyzed with the help of computer image analysis software. Image processing is used to describe the size, shape, surface topography of micro or nano structure materials. In the present paper the characterization analysis is being reported qualitatively by using digital image processing of SEM/TEM image of some nanomaterials. This novel technique is an effective experimental tool for the detailed structural characterization. For image processing Java based software ImageJ is used in the present study.
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Patel, Bindiya, Dr Pankaj Kumar Mishra, and Prof Amit Kolhe. "Lung Cancer Detection on CT Images by using Image Processing." International Journal of Trend in Scientific Research and Development Volume-2, Issue-3 (2018): 2525–31. http://dx.doi.org/10.31142/ijtsrd11674.

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x, Priyanka. "Review Paper on Identifying Fake Images by Digital Image Processing." International Journal of Scientific Engineering and Research 5, no. 5 (2017): 169–71. https://doi.org/10.70729/ijser151486.

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Naz, Najia, Abdul Haseeb Malik, Abu Bakar Khurshid, et al. "Efficient Processing of Image Processing Applications on CPU/GPU." Mathematical Problems in Engineering 2020 (October 10, 2020): 1–14. http://dx.doi.org/10.1155/2020/4839876.

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Heterogeneous systems have gained popularity due to the rapid growth in data and the need for processing this big data to extract useful information. In recent years, many healthcare applications have been developed which use machine learning algorithms to perform tasks such as image classification, object detection, image segmentation, and instance segmentation. The increasing amount of big visual data requires images to be processed efficiently. It is common that we use heterogeneous systems for such type of applications, as processing a huge number of images on a single PC may take months o
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Ulkar Huseynova, Anakhanim Mutallimova, Ulkar Huseynova, Anakhanim Mutallimova. "DIGITAL IMAGE PROCESSING." PAHTEI-Procedings of Azerbaijan High Technical Educational Institutions 36, no. 01 (2024): 179–88. http://dx.doi.org/10.36962/pahtei36012024-179.

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Digital processing and subsequent picture identification are one of the scientific fields that is now experiencing rapid development. Currently, a lot of technology is focused on developing systems that use graphical images as information, including receiving, processing, storing, and transmitting information. Two primary areas of use for digital image processing methods are of interest: 1. Increasing image quality to enhance human visual perception. 2. Image processing for use in autonomous machine vision systems, including storage, transmission, and presentation. The fundamentals of digital
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Tesis sobre el tema "Image processing"

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Murphy, Brian P. "Image processing techniques for acoustic images." Thesis, Monterey, California. Naval Postgraduate School, 1991. http://hdl.handle.net/10945/26585.

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Approved for public release; distribution is unlimited<br>The primary goal of this research is to test the effectiveness of various image processing techniques applied to acoustic images generated in MATLAB. The simulated acoustic images have the same characteristics as those generated by a computer model of a high resolution imaging sonar. Edge Detection and Segmentation are the two image processing techniques discussed in this study. The two methods tested are a modified version of the Kalman filtering and median filtering
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Khan, Preoyati. "Cluster Based Image Processing for ImageJ." Kent State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=kent1492164847520322.

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Sahandi, Reza. "Image Processing." Thesis, University of Bradford, 1987. http://eprints.bournemouth.ac.uk/9884/.

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Ouellet, Michel. "Image processing architectures." Thesis, University of Ottawa (Canada), 1986. http://hdl.handle.net/10393/5068.

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Gardiner, Bryan. "Hexagonal image processing." Thesis, University of Ulster, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.535794.

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Hu, Nan. "SECURE IMAGE PROCESSING." UKnowledge, 2007. http://uknowledge.uky.edu/gradschool_theses/448.

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In todays heterogeneous network environment, there is a growing demand for distrusted parties to jointly execute distributed algorithms on private data whose secrecy needed to be safeguarded. Platforms that support such computation on image processing purposes are called secure image processing protocols. In this thesis, we propose a new security model, called quasi information theoretic (QIT) security. Under the proposed model efficient protocols on two basic image processing algorithms linear filtering and thresholding are developed. For both problems we consider two situations: 1) only tw
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Zhang, Yi. "Blur Image Processing." University of Dayton / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1448384360.

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Kim, Younhee. "Towards lower bounds on distortion in information hiding." Fairfax, VA : George Mason University, 2008. http://hdl.handle.net/1920/3403.

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Thesis (Ph.D.)--George Mason University, 2008.<br>Vita: p. 133. Thesis directors: Zoran Duric, Dana Richards. Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Science. Title from PDF t.p. (viewed Mar. 17, 2009). Includes bibliographical references (p. 127-132). Also issued in print.
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Yallop, Marc Richard. "Image processing techniques for passive millimetre wave images." Thesis, University of Reading, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.409545.

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Baabd, A., M. Y. Tymkovich, and О. Г. Аврунін. "Image Processing of Panoramic Dental X-Ray Images." Thesis, ХГУ, 2018. http://openarchive.nure.ua/handle/document/6204.

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The panoramic image allows to clearly see the state of the teeth, the dental rudiments, which are located in the jaw, temporomandibular joints, as well as the maxillary sinuses. It is noted that this type of study has a small dose of radiation. Indications for this type of study are dental implantation, bite correction, suspicion of bone tissue inflammation, control of the growth and development of the teeth, as well as the diagnosis of other dental problems.
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Libros sobre el tema "Image processing"

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Kayyali, Mohamed S. Digital image processing. Facultad de Ingenieria y Arquitectura de la Universidad de San Martin de Porres, 2002.

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Acharya, Tinku, and Ajoy K. Ray. Image Processing. John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471745790.

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Petrou, Maria, and Pedro García Sevilla. Image Processing. John Wiley & Sons, Ltd, 2006. http://dx.doi.org/10.1002/047003534x.

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E, Pearson D., ed. Image processing. McGraw-Hill, 1991.

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National Institutes of Health (U.S.). Division of Computer Research and Technology., ed. Image processing. Division of Computer Research and Technology, National Institutes of Health, 1985.

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Henri, Maître, ed. Image processing. ISTE Ltd., 2008.

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Acharya, Tinku. Image Processing. John Wiley & Sons, Ltd., 2005.

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National Institutes of Health (U.S.). Division of Computer Research and Technology, ed. Image processing. Division of Computer Research and Technology, National Institutes of Health, 1985.

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Leberl, Franz W. Radargrammetric image processing. Artech House, 1990.

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Burger, Wilhelm, and Mark J. Burge. Digital Image Processing. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-05744-1.

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Capítulos de libros sobre el tema "Image processing"

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Wolff, Robert S., and Larry Yaeger. "Images and Image Processing." In Visualization of Natural Phenomena. Springer US, 1993. http://dx.doi.org/10.1007/978-1-4684-0646-7_1.

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Corke, Peter. "Images and Image Processing." In Springer Tracts in Advanced Robotics. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54413-7_12.

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Corke, Peter, Witold Jachimczyk, and Remo Pillat. "Images and Image Processing." In Springer Tracts in Advanced Robotics. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-07262-8_11.

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Corke, Peter. "Images and Image Processing." In Springer Tracts in Advanced Robotics. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-06469-2_11.

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Corke, Peter. "Images and Image Processing." In Robotic Vision. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79175-9_4.

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Hamann, Sabine, Hauke Hell, Detlef Pankow, and Robert Wunderer. "Image Processing." In DigiScript™. Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-46829-2_39.

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Ortega-Alcalde, D. "Image processing." In Developments in Cardiovascular Medicine. Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-1984-9_2.

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Klette, Reinhard. "Image Processing." In Undergraduate Topics in Computer Science. Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-6320-6_2.

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van der Heijden, Ferdi, and Luuk Spreeuwers. "Image Processing." In Multimedia Retrieval. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-72895-5_5.

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Greenberg, Richard. "Image Processing." In Internet Links for Science Education. Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-5909-2_13.

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Actas de conferencias sobre el tema "Image processing"

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Jariwala, Devanshi, and Ruchi Gajjar. "Image Processing Based Texture Transfer Between Images." In 2024 International Conference on Electrical Electronics and Computing Technologies (ICEECT). IEEE, 2024. http://dx.doi.org/10.1109/iceect61758.2024.10739041.

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Alu, Andrea. "Metasurfaces for Image Processing and Analog Computing." In Laser Science. Optica Publishing Group, 2024. https://doi.org/10.1364/ls.2024.lw7f.2.

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I discuss our recent progress in demonstrating ultrathin engineered surfaces that perform image processing and computing on optical signals and images, and the opportunities for photonic technologies. Full-text article not available; see video presentation
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K, Thilagavathi, Aldrick Peter T, Hariram TS, et al. "Image Pixelization Using Image Processing Algorithms." In 2025 3rd International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA). IEEE, 2025. https://doi.org/10.1109/icaeca63854.2025.11012246.

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Meinel, Edward S. "Origins of linear and nonlinear recursive restoration algorithms." In Quantum-Limited Imaging and Image Processing. Optica Publishing Group, 1986. http://dx.doi.org/10.1364/qlip.1986.wb2.

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In a recent paper Frieden1 unified the theory behind many nonlinear image restoration methods. He proposed that these methods be implemented using the Newton-Raphson iterative approach. Although this approach is fast, exhibiting quadratic convergence, it requires complex programming and large core storage capabilities even for modest image sizes, unless the problem can be reduced to line-by-line processing2. By contrast, recursive or replacement formulas permit interactive processing with modest storage requirements, albeit with slower convergence. They can also be implemented on a specialized
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Prachetaa, R., and B. P. C. Rao. "Image processing for NDT images." In 2010 International Conference on Signal and Image Processing (ICSIP). IEEE, 2010. http://dx.doi.org/10.1109/icsip.2010.5697463.

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Hoffmann, Rolf. "A High Quality Image Stitching Process for Industrial Image Processing and Quality Assurance." In OCM 2021 - 5th International Conference on Optical Characterization of Materials. KIT Scientific Publishin, 2021. http://dx.doi.org/10.58895/ksp/1000128686-18.

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The size of the recording area of a camera is limited. The resolution of a camera image is also limited. To capture larger areas, a wide angle lens can be used, for example. However, the image resolution per unit area decreases. The decreased image resolution can be compensated by image sensors with a higher number of pixels. However, the use of a high pixel number of image sensors is limited to the current state of the art and availability of real image sensors. Furthermore the use of a wide angle lens has the disadvantage of a stronger distortion of the image scene. Also the viewing directio
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Shagalova, P. A., E. S. Sokolova, and S. N. Ryndov. "Automation of Blood Microscopy Image Processing." In 32nd International Conference on Computer Graphics and Vision. Keldysh Institute of Applied Mathematics, 2022. http://dx.doi.org/10.20948/graphicon-2022-1157-1164.

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Automation of medical image processing aims to create a universal tool for the purposes of medical diagnostics in the field of microscopy of cells and tissues. The authors of the paper have collected large databases of various digital microscopy images that allow to automate the processes of medical research using computer vision technologies, improve the quality of image analysis and provide a set of diagnostic information for decision making. For this purpose, a software package with a user-friendly interface has been developed that allows visualizing the results of detection of microobjects
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"Image processing." In 2015 International Symposium on Advanced Computing and Communication (ISACC). IEEE, 2015. http://dx.doi.org/10.1109/isacc.2015.7377338.

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Belousov, O. I., and Z. M. Albekova. "Image processing." In Научные тенденции: Вопросы точных и технических наук. ЦНК МОАН, 2018. http://dx.doi.org/10.18411/spc-12-08-2018-03.

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Skelton, Jerry P., Anthony P. Cavallo, and Julie Peternick. "Document Image Processing The New Image Processing Frontier." In 33rd Annual Techincal Symposium, edited by Andrew G. Tescher. SPIE, 1990. http://dx.doi.org/10.1117/12.962346.

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Informes sobre el tema "Image processing"

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Meitzler, Thomas, Grant Gerhart, Harpreet Singh, et al. Image Processing. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada597230.

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Rosenfeld, Azriel. Parallel Image Processing and Image Understanding. Defense Technical Information Center, 1986. http://dx.doi.org/10.21236/ada183223.

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Rosenfeld, A. Parallel Image Processing and Image Understanding. Defense Technical Information Center, 1985. http://dx.doi.org/10.21236/ada159029.

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Van Eeckhout, E., P. Pope, and L. Balick. Image processing technology. Office of Scientific and Technical Information (OSTI), 1996. http://dx.doi.org/10.2172/262986.

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Chartrand, Rick. Image processing and reconstruction. Office of Scientific and Technical Information (OSTI), 2012. http://dx.doi.org/10.2172/1044085.

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Khoury, Jehad, and Mark Cronin-Golomb. Real Time Holographic Image Processing. Defense Technical Information Center, 1996. http://dx.doi.org/10.21236/ada408111.

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Giardina, Charles R., and Edward R. Dougherty. Image Processing Language. Phase 1. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada204232.

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George, Nicholas, and David M. Berfanger. Halftoning and Image Processing Algorithms. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada369915.

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Winkler, Robert P., and Chris Schlesiger. Image Processing REST Web Services. Defense Technical Information Center, 2013. http://dx.doi.org/10.21236/ada577345.

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Allard, Anthony, Edward Dugan, and Alan Jacobs. Image Processing Techniques for Lateral Migration Radiography Land Mine Images. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada384546.

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