Abstract
A moment-based approach is developed to constructing tree-structured descriptions of patterns given by region-based shapes with grayscale attributes. The proposed representation is approximately invariant with respect to the pattern rotation, translation, scale, and level of brightness. The tree-like structure of the pattern representations provides their independent encoding into prefix code words. Due to this fact, a pattern recognition procedure amounts to decoding a code word of the pattern by the nearest code word from a tree of the code words of selected templates. Efficient application of the pattern representation technique is illustrated by experimental results on signature and hand gesture recognition.
This work is supported by the Russian Foundation for Basic Research, project 06-01-00524.
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Lange, M., Ganebnykh, S., Lange, A. (2007). Moment-Based Pattern Representation Using Shape and Grayscale Features. In: Martí, J., Benedí, J.M., Mendonça, A.M., Serrat, J. (eds) Pattern Recognition and Image Analysis. IbPRIA 2007. Lecture Notes in Computer Science, vol 4477. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72847-4_67
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DOI: https://doi.org/10.1007/978-3-540-72847-4_67
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