doi: 10.4304/jsw.9.4.902-906
Edge Extraction for Human Body Images based on ACAFCM Algorithm
- 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.
Keywords
- photography;
- human
- body
- image;
- edge
- extr
How to Cite
Xiaoning Jing, Xiaojiu Li, and Xiaojie Li, "Edge Extraction for Human Body Images based on ACAFCM Algorithm," Journal of Software, vol. 9, no. 4, pp. 902-906, 2014. https://doi.org/ 10.4304/jsw.9.4.902-906
Copyright & License
Copyright © 2014 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).