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Token-based extraction of straight lines

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3 Author(s)
M. Boldt ; Dept. of Comput. & Inf. Sci., Massachusetts Univ., Amherst, MA, USA ; R. Weiss ; E. Riseman

The authors present a computational approach to the extraction of straight lines based on the principles of perceptual organization. In particular, they consider how local information that is spatially distributed can be organized into a large-scale geometric structure in a computationally efficient manner. Symbolic tokens representing line segments and relations which are primarily geometric in nature and used to control a hierarchical grouping process. The relational measures on pairs of lines are based on collinearity, proximity, and similarity in contrast. The algorithm is implemented within a local, parallel, hierarchical framework for symbolic grouping that involves a cycle of linking, optimization, and replacement steps. Experimental results on a variety of natural scene images demonstrate effectiveness of the filtering and optimization stages in the extraction of straight lines. Issues in the development of a more general framework for symbolic grouping are also discussed

Published in:

IEEE Transactions on Systems, Man, and Cybernetics  (Volume:19 ,  Issue: 6 )