Extracting and Labelling the Objects from an Image by Using the Fuzzy Clustering Algorithm and a New Cluster Validity

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Title:	Extracting and Labelling the Objects from an Image by Using the Fuzzy Clustering Algorithm and a New Cluster Validity
Authors:	Chou, Chien-Hsing;Hsieh, Yi-Zeng;Su, Mu-Chun;Chu, Yung-Long
Contributors:	淡江大學電機工程學系
Keywords:	extract object;cluster validity;clustering algorithm;line symmetry;similarity measure
Date:	2013-02-25
Issue Date:	2013-03-07 16:53:53 (UTC+8)
Publisher:	IACSIT Press
Abstract:	Many real-world and man-made objects are line symmetry. To detection the line-symmetry objects from an image, in this paper, a new cluster validity measure which adopts a non-metric distance measure based on the idea of "line symmetry" is presented. The thresholding technique is first applied to extract the objects from the original image; and the object pixels are transferred to be the data patterns. Then the fuzzy clustering algorithm is applied to label the object pixels; and the proposed validity measure is used in determining the number of objects. Simulation results are used to illustrate the performance of the proposed measure.
Relation:	2013 2nd International Conference on Information Computer Application (ICICA 2013), 3p.
Appears in Collections:	[Graduate Institute & Department of Electrical Engineering] Proceeding

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