9783848437429 - optical flow based moving object detection and tracking system: development of optical flow based moving object detection and tracking system on an embedded dsp processor di basavaiah, manjunath (4 risultati)
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Da: preigu, Osnabrück, Germaniapreigu
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Taschenbuch. Condizione: Neu. Optical Flow Based Moving Object Detection and Tracking System | Development of Optical Flow Based Moving Object Detection and Tracking System on an Embedded DSP Processor | Manjunath Basavaiah | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783848437429 | Verantwortliche Person fü…r die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Paperback. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Da: moluna, Greven, Germaniamoluna
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Kartoniert / Broschiert. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Basavaiah ManjunathManjunath Basavaiah received his U.G. degree B.E. inElectronics and Communication Engineering fromGlobal Academy of Technology, Bangalore & P.G.degree M.Sc […Engg] in Real Time Embedded Systemsfrom Coventry Universi.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Moving object detection in digital image sequence involves identification of the presence of an object in consecutive frames where as object tracking is used to monitor the movements with respect to the region of interest. In this proje…ct, the motion estimation is obtained using Optical Flow. Optical Flow is the distribution of apparent velocities of movement of brightness patterns in an image. Lucas-Kanade algorithm with Sobel, Horn and Guassian smoothing techniques is used in this work for computation of Optical Flow vectors. Single and multiple object movements with respect to the computed vectors are segmented using thresholding. The extracted movements are tracked using edge and centroid information. Suitable image enhancement techniques are applied to the segmented results to avoid the unwanted information present in the image. Real and virtual image data with static and dynamic environment are used as test sequences to validate the developed algorithms. The tracking performance, in terms of their accuracy and computation time, of the different algorithms with and without image pyramid is analysed and compared in MATLAB & C on Intel Core2 Duo processor on Linux environment.
