Title :
An axiomatic approach to clustering line-segments
Author :
Jonk, Arnold ; Smeulders, Arnold W M
Author_Institution :
Dept. of Math. & Comput. Sci., Amsterdam Univ., Netherlands
Abstract :
In this paper we consider the problem of clustering line-segments into new ones. The clustering-hierarchy gives an answer to the question what original line segments are combined into larger ones. Such a clustering is defined as a hierarchical ordering of a set of line-segments. Criteria on a clustering-method are presented. The difference between edges and lines in relation to scale-invariant clustering is demonstrated. Existing approaches are evaluated using the presented criteria. It is shown that these approaches do not meet desirable criteria such as scale-invariance. A new method is described that adheres the formulated criteria. Finally an experiment is presented that illustrates the usefulness of the new method
Keywords :
computer vision; pattern recognition; axiomatic approach; clustering-hierarchy; edges; hierarchical ordering; line-segments clustering; lines; scale-invariance; scale-invariant clustering; Clustering methods; Computer science; Computer vision; Image converters; Image edge detection; Image segmentation; Mathematics; Robustness; Shape;
Conference_Titel :
Document Analysis and Recognition, 1995., Proceedings of the Third International Conference on
Conference_Location :
Montreal, Que.
Print_ISBN :
0-8186-7128-9
DOI :
10.1109/ICDAR.1995.599019