Multi-scale edge detection and object extraction for image retrieval

A new scheme for boundary-based object extraction and description of still images, through multi-scale edge detection, is proposed in this paper. Boundary-based methods try to extract closed contours from individual edge pixels through edge-linking. Our approach is based on a connected structure of edge pixels as the initial edge-linking elements. These connected structures, the sub-segments, are extracted from the Canny edge map of an image. Multiple simplification-scales are derived from applying iterations of the Bilateral filter to the image, providing extra information about the relative importance of each sub-segment. Edge-linking towards contour closure is achieved through perceptually-driven minimum cost search. Furthermore, a shape-based description vector is derived from the extracted contours, and retrieval results are obtained via the integration of the whole scheme into MUVIS framework.