Token-based extraction of straight lines
作者： M. Boldt , R. Weiss , E. Riseman
DOI: 10.1109/21.44073
关键词: Collinearity 、 Similarity (geometry) 、 Line segment 、 Computer science 、 Pattern recognition (psychology) 、 Security token 、 Algorithm 、 Theoretical computer science 、 Structure (mathematical logic) 、 Process (computing) 、 Image processing
摘要: The authors present a computational approach to the extraction of straight lines based on principles perceptual organization. In particular, they consider how local information that is spatially distributed can be organized into large-scale geometric structure in computationally efficient manner. Symbolic tokens representing line segments and relations which are primarily nature used control hierarchical grouping process. relational measures pairs collinearity, proximity, similarity contrast. algorithm implemented within local, parallel, framework for symbolic involves cycle linking, optimization, replacement steps. Experimental results variety natural scene images demonstrate effectiveness filtering optimization stages lines. Issues development more general also discussed. >
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