9783659690198 - optimal foreground detection methods for pixel domain video objects de devi k.suganya (5 resultados)

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    • Idioma: Inglés

      Editorial: LAP LAMBERT Academic Publishing, 2015

      3659690198 / 9783659690198

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      Librería: preigu, Osnabrück, Alemaniapreigu

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      Taschenbuch. Condición: Neu. Optimal Foreground Detection Methods For Pixel Domain Video Objects | K. Suganya Devi | Taschenbuch | 180 S. | Englisch | 2015 | LAP LAMBERT Academic Publishing | EAN 9783659690198 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

    • Idioma: Inglés

      Editorial: LAP LAMBERT Academic Publishing Mär 2015, 2015

      3659690198 / 9783659690198

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      Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.

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      Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This Book discusses different approaches for extracting or detecting the foreground video objects in a pixel domain. To tackle with the problems related with existing approaches this book gives a solution by applying the following methods sequentially thereby to improve the efficiency. First, extraction of superpixel from a video frame to reduce the number of comparisons. Second, applying the background subtraction algorithm (Gaussian background Modeling) and optical flow on those superpixels extracted from each frame of the video. This is done to detect the edges of objects in the video clearly and finally by using the SMED (Separable Morphological Edge Detector) the foreground object is segmented from background scene accurately 180 pp. Englisch.

    • Idioma: Inglés

      Editorial: LAP LAMBERT Academic Publishing, 2015

      3659690198 / 9783659690198

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      Librería: moluna, Greven, Alemaniamoluna

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      Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Devi K.SuganyaDr.K.Suganya Devi is an Asst Prof and Head (i/c) in the Department of Computer Science and Engg, University College of Engg,Panruti,India. She has 6 years of Research experience in Multimedia & Image Processing. She se.

    • Idioma: Inglés

      Editorial: LAP LAMBERT Academic Publishing Mär 2015, 2015

      3659690198 / 9783659690198

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      Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000

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      Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This Book discusses different approaches for extracting or detecting the foreground video objects in a pixel domain. To tackle with the problems related with existing approaches this book gives a solution by applying the following methods sequentially thereby to improve the efficiency. First, extraction of superpixel from a video frame to reduce the number of comparisons. Second, applying the background subtraction algorithm (Gaussian background Modeling) and optical flow on those superpixels extracted from each frame of the video. This is done to detect the edges of objects in the video clearly and finally by using the SMED (Separable Morphological Edge Detector) the foreground object is segmented from background scene accuratelyVDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 180 pp. Englisch.

    • Idioma: Inglés

      Editorial: LAP LAMBERT Academic Publishing, 2015

      3659690198 / 9783659690198

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      Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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      Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This Book discusses different approaches for extracting or detecting the foreground video objects in a pixel domain. To tackle with the problems related with existing approaches this book gives a solution by applying the following methods sequentially thereby to improve the efficiency. First, extraction of superpixel from a video frame to reduce the number of comparisons. Second, applying the background subtraction algorithm (Gaussian background Modeling) and optical flow on those superpixels extracted from each frame of the video. This is done to detect the edges of objects in the video clearly and finally by using the SMED (Separable Morphological Edge Detector) the foreground object is segmented from background scene accurately.