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Using pyramids to detect good continuation

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4 Author(s)
Tsai-Hong Hong ; Computer Vision Laboratory, Computer Science Center, University of Maryland, College Park, MD 20742 ; Michael O. Shneier ; Ralph L. Hartley ; Azriel Rosenfeld

Pictures containing lines and curves are often perceived by humans as being composed of a smaller number of more global figures. For example, a broken set of collinear line segments is perceived as a single straight line, even in the presence of other overlapping line segments. A method of extracting such figures from images automatically in a highly parallel manner is presented in this work. A pyramid of successively lower-resolution images is used to transform the problem from one of global search to one of local good continuation. Using the pyramid, figures that are both sparse and obscured can successfully be extracted and the background clutter can be suppressed.

Published in:

IEEE Transactions on Systems, Man, and Cybernetics  (Volume:SMC-13 ,  Issue: 4 )