Contour Continuity in Region Based Image Segmentation

Region-based image segmentation techniques make use of similarity in intensity, color and texture to determine the partitioning of an image. The powerful cue of contour continuity is not exploited at all. In this paper, we provide a way of incorporating curvilinear grouping into region-based image segmentation. Soft contour information is obtained through orientation energy. Weak contrast gaps and subjective contours are completed by contour propagation. The normalized cut approach proposed by Shi and Malik is used for the segmentation. Results on a large variety of images are shown.

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