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Proceedings Paper

Gray image feature extraction and recognition based on fuzzy cluster
Author(s): Lulu Bu; Xinling Shi; Jing Zhang; Jinghua Zhang; Yanlong Wang
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Paper Abstract

Fuzzy cluster-based image processing algorithm presents numerous advantages due to their unsupervised properties and soft partition. Combining unsupervised feature and soft partition feature of fuzzy cluster algorithm, this paper presents an image feature extraction method based on fuzzy cluster. This fuzzy cluster technique deals with the problem of similarity degree for finishing an optical image feature extraction processing by using the method of similarity and statistics that is used to calculate category object by establishing fuzzy relations. The image feature extraction based on fuzzy cluster presents significant advantages to adjust system parameters for completing the selection to the image region extraction or edge detection. The image feature extraction performance of the proposed optical system is reported for various image processing applications using a simulation program.

Paper Details

Date Published: 4 February 2011
PDF: 7 pages
Proc. SPIE 7752, PIAGENG 2010: Photonics and Imaging for Agricultural Engineering, 77520A (4 February 2011); doi: 10.1117/12.887489
Show Author Affiliations
Lulu Bu, Yunnan Univ. (China)
Xinling Shi, Yunnan Univ. (China)
Jing Zhang, Yunnan Univ. (China)
Jinghua Zhang, Yunnan Univ. (China)
Yanlong Wang, Yunnan Univ. (China)


Published in SPIE Proceedings Vol. 7752:
PIAGENG 2010: Photonics and Imaging for Agricultural Engineering
Honghua Tan, Editor(s)

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