Title :
Labeling of curvilinear structure across scales by token grouping
Author_Institution :
Xerox Palo Alto Res. Center, CA, USA
Abstract :
An algorithm for labeling curvilinear structure at multiple scales in line drawings and edge images is presented. Symbolic curve-element tokens residing in a spatially indexed and scale-indexed data structure denote circular arcs fit to image data. Tokens are computed via a small-to-large scale grouping procedure using a greedy best-first strategy for choosing the support of new tokens. The resulting image description is rich and redundant in that a given segment of image contour may be described by multiple tokens at different scales, and by more than one token at any given scale. This property facilitates selection and characterization of portions of the image based on curve-element attributes
Keywords :
computational geometry; computer vision; curve fitting; feature extraction; image processing; circular arcs; curve-element attributes; curve-element tokens; curvilinear structure; curvilinear structures labeling; edge images; greedy best-first strategy; image contour; image description; line drawings; scale-indexed data structure; small-to-large scale grouping procedure; spatially indexed data structure; token grouping; Aggregates; Data structures; Ear; Histograms; Image segmentation; Labeling; Polynomials; Smoothing methods; Spline; Writing;
Conference_Titel :
Computer Vision and Pattern Recognition, 1992. Proceedings CVPR '92., 1992 IEEE Computer Society Conference on
Conference_Location :
Champaign, IL
Print_ISBN :
0-8186-2855-3
DOI :
10.1109/CVPR.1992.223266
