Evaluation of shape correspondence using ordinal measures

In this paper we present a novel approach to shape similarity estimation based on ordinal correlation. The proposed method operates in three steps: object alignment, contour to multilevel image transformation and similarity evaluation. This approach is suitable for use in CBIR, shape classification and performance evaluation of segmentation algorithms. The proposed technique produced encouraging results when applied on the MPEG-7 test data.

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