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Issue No.04 - April (2005 vol.27)
pp: 546-561
Song Wang , IEEE
ABSTRACT
We present ratio contour, a novel graph-based method for extracting salient closed boundaries from noisy images. This method operates on a set of boundary fragments that are produced by edge detection. Boundary extraction identifies a subset of these fragments and connects them sequentially to form a closed boundary with the largest saliency. We encode the Gestalt laws of proximity and continuity in a novel boundary-saliency measure based on the relative gap length and average curvature when connecting fragments to form a closed boundary. This new measure attempts to remove a possible bias toward short boundaries. We present a polynomial-time algorithm for finding the most-salient closed boundary. We also present supplementary preprocessing steps that facilitate the application of ratio contour to real images. We compare ratio contour to two closely related methods for extracting closed boundaries: Elder and Zucker's method based on the shortest-path algorithm and Williams and Thornber's method based on spectral analysis and a strongly-connected-components algorithm. This comparison involves both theoretic analysis and experimental evaluation on both synthesized data and real images.
INDEX TERMS
Image segmentation, perceptual organization, boundary detection, edge detection, graph models.
CITATION
Toshiro Kubota, Jeffrey Mark Siskind, Song Wang, "Salient Closed Boundary Extraction with Ratio Contour", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.27, no. 4, pp. 546-561, April 2005, doi:10.1109/TPAMI.2005.84
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