DocumentCode :
1299344
Title :
Using pyramids to detect good continuation
Author :
Hong, Tsai-Hong ; Shneier, Michael O. ; Hartley, Ralph L. ; Rosenfeld, Azriel
Author_Institution :
Computer Vision Laboratory, Computer Science Center, University of Maryland, College Park, MD 20742
Issue :
4
fYear :
1983
Firstpage :
631
Lastpage :
635
Abstract :
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.
Keywords :
Cybernetics; Feature extraction; Humans; Image edge detection; Image segmentation; Libraries; Smoothing methods;
fLanguage :
English
Journal_Title :
Systems, Man and Cybernetics, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9472
Type :
jour
DOI :
10.1109/TSMC.1983.6313152
Filename :
6313152
Link To Document :
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