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Proceedings Paper

Pyramidal edge detector based on adaptive weighted fuzzy mean filters
Author(s): Zhi-Gang Wang; Dong Wang; Wei Wang; Xiaoming Xu
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Paper Abstract

A new unsupervised multiresolution pyramidal edge detector, based on adaptive weighted fuzzy mean (AWFM) filters, is presented in this paper. The algorithm first constructs a pyramidal structure by repetitive AWFM filtering and subsampling of original image. Then it utilizes multiple heuristic linking criteria between the edge nodes of two adjacent levels and considers the linkage as a fuzzy model, which is trained offline. Through this fuzzy linking model, the boundaries detected at coarse resolution are propagated and refined to the bottom level from the coarse-to-fine edge detection. The validation experiments results demonstrate that the proposed approach has superior performance compared with standard fixed resolution detector and previous multiresolution approach, especially in impulse noise environment.

Paper Details

Date Published: 21 September 2001
PDF: 6 pages
Proc. SPIE 4550, Image Extraction, Segmentation, and Recognition, (21 September 2001); doi: 10.1117/12.441452
Show Author Affiliations
Zhi-Gang Wang, Shanghai Jiaotong Univ. (China)
Dong Wang, Shanghai Jiaotong Univ. (China)
Wei Wang, Shanghai Jiaotong Univ. (China)
Xiaoming Xu, Shanghai Jiaotong Univ. (China)

Published in SPIE Proceedings Vol. 4550:
Image Extraction, Segmentation, and Recognition
Tianxu Zhang; Bir Bhanu; Ning Shu, Editor(s)

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