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A Medial Axis Transformation for Grayscale Pictures
April 1982 (vol. 4 no. 4)
pp. 419-421
Shyuan Wang, Computer Vision Laboratory, Computer Science Center, University of Maryland, College Park, MD 20742.
Azriel Rosenfeld, Computer Vision Laboratory, Computer Science Center, University of Maryland, College Park, MD 20742.
Angela Y. Wu, Computer Vision Laboratory, Computer Science Center, University of Maryland, College Park, MD 20742; Department of Mathematics, Statistics, and Computer Science, American Universit
Blum's medial axis transformation (MAT) for binary pictures yields medial axis points that lie midway between opposite borders of a region or along angle bisectors. This note discusses a generalization of the MAT in which a score is computed for each point P of a grayscale picture based on the gradient magnitudes at pairs of points that have P as their midpoint. These scores are high at points that lie midway between pairs of antiparallel edges or along angle bisectors, so that they define a MAT-like ``skeleton,'' which we may call the GRADMAT. However, this skeleton is rather sensitive to the presence of noise edges or to irregularities in the region edges, and it also is subject to artifacts created by pairs of edges belonging to different objects.
Citation:
Shyuan Wang, Azriel Rosenfeld, Angela Y. Wu, "A Medial Axis Transformation for Grayscale Pictures," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 4, no. 4, pp. 419-421, April 1982, doi:10.1109/TPAMI.1982.4767274
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