Abstract
A novel real-time approach for classification or identification of objects is presented here that is suitable for visual attention system of mobile robots. The proposed method constructs convex hulls for regions found in an image using a new external scanning technique. Then a cleaning step produces refined polygons that are in turn used for extracting shape signatures for the regions. In the training phase, shape signatures are collected from test data to find a mean signature for a particular object. A small database is created for all objects related to a specific context in which classification is to be performed. In classifying phase, signatures obtained from objects found in a given image are compared with those present in the database for identification. Nearest signature from the database to a given one is taken as identity of the later. Results have proved efficiency and accuracy of this method.
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Aziz, M.Z., Mertsching, B., Munir, A. (2005). Classification Using Scale and Rotation Tolerant Shape Signatures from Convex Hulls. In: Singh, S., Singh, M., Apte, C., Perner, P. (eds) Pattern Recognition and Image Analysis. ICAPR 2005. Lecture Notes in Computer Science, vol 3687. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552499_73
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DOI: https://doi.org/10.1007/11552499_73
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28833-6
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