Abstract
We present a new shape descriptor for measuring the similarity between shapes and exploit it in graphical object recognition and retrieval. By statistically integrating the local length-ratio and angle constraints between contour points relative to the shape skeleton, we construct the shape descriptor capturing the global spatial distribution of the shape contour. Then, the dissimilarity between two shapes is computed as a weighted sum of matching errors between corresponding constraint histograms. Experimental results are presented for symbols and shapes data set, showing the effectiveness of our method.
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Su, F., Lu, T., Yang, R. (2010). A New Shape Descriptor for Object Recognition and Retrieval. In: Qiu, G., Lam, K.M., Kiya, H., Xue, XY., Kuo, CC.J., Lew, M.S. (eds) Advances in Multimedia Information Processing - PCM 2010. PCM 2010. Lecture Notes in Computer Science, vol 6297. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15702-8_45
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DOI: https://doi.org/10.1007/978-3-642-15702-8_45
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15701-1
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