A Tsallis-entropy Image Thresholding Method Based on Two-dimensional Histogram Obique Segmentation
Image Segmentation is one of important tasks in conventional or document image processing. Tsallis-entropy based image thresholding method has been considered one of the most efficient ways for image segmentation. At present one useful way in entropy-thresholding segmentation is based 2-D vertical segmentation, but obvious limitations exist in this approach. In this paper, a method 2-D obique segmentation is applied. Meanwhile motivate by Kullback-Leibler (KL) distance which measures the information discrepance between two different sources, a new optimization based on minimizing imitational Kullback-Leibler distance (MIKL) criterion function is proposed. It is a new technique that image threshold value by 2-D Tsallis-entropy obique segmentation based on MIKL. Some typical results show the superiorly of the proposed technique over references, achieving better effect wherever in the document or conventional image segmentation.
Tsallis-entropy obique segmentation Kullback-Leider distance
Xiaoguang Tian Xiaorong Hou
College of Automation University of Electronic Science of technology of China Chengdu, Sichuan Province
国际会议
2009 WASE International Conference on Information Engineering(2009年国际信息工程会议)(ICIE 2009)
太原
英文
164-168
2009-07-10（万方平台首次上网日期，不代表论文的发表时间）