Moving object detection and segmentation is important for traffic surveillance and object recognition in security surveillance. Moving object detection in dynamic environment video is more complex than the static environment videos. This proposed methodology consists of background subtraction and classification modules. The absolute difference image is constructed in the background subtraction module. The features are extracted from this difference image and these extracted features are trained and classified using ANFIS classification module. The moving object detection for video surveillance is proposed using classification approach Co-Active Neuro Fuzzy Expert System (CANFES) classifier.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Moving object detection and segmentation is important for traffic surveillance and object recognition in security surveillance. Moving object detection in dynamic environment video is more complex than the static environment videos. This proposed methodology consists of background subtraction and classification modules. The absolute difference image is constructed in the background subtraction module. The features are extracted from this difference image and these extracted features are trained and classified using ANFIS classification module. The moving object detection for video surveillance is proposed using classification approach Co-Active Neuro Fuzzy Expert System (CANFES) classifier. 152 pp. Englisch. Seller Inventory # 9786206153832
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Moving object detection and segmentation is important for traffic surveillance and object recognition in security surveillance. Moving object detection in dynamic environment video is more complex than the static environment videos. This proposed methodolog. Seller Inventory # 863316555
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Taschenbuch. Condition: Neu. Certain Investigations on Moving Vehicle Detection and Classification | An Ideal Solution for Moving Vehicle Detection | Shyamala A. (u. a.) | Taschenbuch | Englisch | 2023 | LAP LAMBERT Academic Publishing | EAN 9786206153832 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 126866276
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Moving object detection and segmentation is important for traffic surveillance and object recognition in security surveillance. Moving object detection in dynamic environment video is more complex than the static environment videos. This proposed methodology consists of background subtraction and classification modules. The absolute difference image is constructed in the background subtraction module. The features are extracted from this difference image and these extracted features are trained and classified using ANFIS classification module. The moving object detection for video surveillance is proposed using classification approach Co-Active Neuro Fuzzy Expert System (CANFES) classifier.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 152 pp. Englisch. Seller Inventory # 9786206153832
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Moving object detection and segmentation is important for traffic surveillance and object recognition in security surveillance. Moving object detection in dynamic environment video is more complex than the static environment videos. This proposed methodology consists of background subtraction and classification modules. The absolute difference image is constructed in the background subtraction module. The features are extracted from this difference image and these extracted features are trained and classified using ANFIS classification module. The moving object detection for video surveillance is proposed using classification approach Co-Active Neuro Fuzzy Expert System (CANFES) classifier. Seller Inventory # 9786206153832
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