Robust region segmentation based on a pseudo-distance map

Abstract

We present a robust region segmentation method based on a pseudo-distance map (PDM) that uses a watershed algorithm as a segmentation tool. The PDM is a regularized version of a Euclidean distance map (EDM) directly computed from the edge-strength function (ESF) of an input image without edge detection, which involves a thresholding operation. This unavoidably causes useful region boundary information loss from the original image. We show that applying the watershed algorithm to the PDM significantly reduces oversegmentation, and the final segmentation results obtained by a simple region-merging process are more accurate and meaningful and less sensitive to noise than those of the gradient-based or EDM-based methods. We also propose a simple and efficient region-merging criterion that considers both boundary strengths and inner intensities of regions to be merged. We tested and verified the robustness of our method with a variety of synthetic and real images. (C) 2004 SPIE and IST.