Volume 9 Number 4 (Apr. 2014)
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JSW 2014 Vol.9(4): 902-906 ISSN: 1796-217X
doi: 10.4304/jsw.9.4.902-906

Edge Extraction for Human Body Images based on ACAFCM Algorithm

Xiaoning Jing, Xiaojiu Li, Xiaojie Li
Tianjin Polytechnic University, Tianjin 300387, China

Abstract—Image edge extraction is an important process in obtaining anthropometric information from human body images captured by ordinary cameras. Depending on the characteristics of the large pixel matrix and the fuzzy edge of the image, the ant colony and fuzzy C-means clustering (ACAFCM) algorithm is used to get a clear and complete edge contour of the human body. This Canny algorithm is used to preprocess image segmentation, binarization, and de-noising by simplifying the image color and noise. The ant colony algorithm determines the initial center and number of clusters, and it distinguishes the pixels, based on the target, background, edge, and noise of the pretreated image. The FCM algorithm clusters the pixels with the same attributes into one class, and it extracts a clear and complete edge contour of the body image.

Index Terms—photography; human body image; edge extraction; ACAFCM algorithm

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Cite: Xiaoning Jing, Xiaojiu Li, Xiaojie Li, "Edge Extraction for Human Body Images based on ACAFCM Algorithm," Journal of Software vol. 9, no. 4, pp. 902-906, 2014.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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