Image indexing and similarity retrieval based on a new spatial relation model

The spatial relation model is an important technique for image indexing and retrieval in image or multimedia databases. 2D strings and its variants are proposed to support the representation of spatial relationships. A novel spatial knowledge representation model named “Two Dimension Begin-End boundary string” (2D Bε-string) is proposed. The 2D Bε-string represents an icon by its MBR boundaries. By applying a number of “dummy objects”, the 2D Bε-string can intuitively and naturally represent the pictorial spatial information without any spatial operator. In addition, an image similarity evaluation method based on the modified “Longest Common Subsequence” (LCS) algorithm is presented. By using the proposed evaluation method, not only can those images for which all the icons and their spatial relationships fully agree with the query image be sifted out, but also those images whose partial icons and/or spatial relationships are similar to the query image. It resolves the problems of query targets and/or spatial relationships not being certain. Our representation model and similarity evaluation also simplify the retrieval progress of linear transformations, including image rotation and reflection