Shapes Matching and Indexing Using Textual Descriptors

We propose in this paper a new matching and indexing method of shapes. Models of objects silhouettes are stored in the database using their textual descriptors. As we will see, XLWDOS descriptors are sensitive to noise. We propose a “reduction technique” to process noisy shapes and match corresponding XLWDOS descriptors using only “textual transformations”. The matching algorithm we propose is an efficient way to index shapes descriptors. Experiments over real images are conducted and explained.

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