The study of the auto color image segmentation

Authors:
Jian Zhuang;Haifeng Du;Jinhua Zhang;Sun’an Wang
Affiliations:
School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China;School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China;School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China;School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China
Venue:
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part II
Year:
2005

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Abstract

Auto image segmentation can segment the image without operators interfering and is an important technique in the image processing. The Boltzmann-Color-Image-Segmentation (BCIS), which could control the degree of segmentation by adjusting the temperature parameter, is designed based on the Boltzmann-theory and the Metropolis-rule in the paper. Then the criterion function of image segmentation, which could balance between the number of segmented region and the affinity of the segmented image with the original image, is presented. Based the BCIS and Criterion function, the auto color image segmentation is schemed out by using the artificial immune algorithm. Experiments showed that the color image segmentation algorithm, which we designed in the paper, had the good capabilities.