Infrared Image Transition Region Extraction and Segmentation Based on Local Definition Cluster Complexity
According to the problem of extracting transition region inaccurately based on typical local complexity method, due to its excessively low complexity measurement and deficient detail representation, we propose an improved infrared image transition region extraction algorithm. By constructing local definition cluster function and calculating its complexity, we improve the complexity measurement of the image to a great extent, which is able to represent more detail information. Experiments validate this algorithm. The results show that our method based on local definition cluster complexity can extract the transition region more accurate, and segments the image much better compared to typical local complexity method.
transition region extraction definition cluster complexity image segmentation
Chen Cong-ping Qin Wu Fang Zi-fan Zhang Yi
School of Mechanical & Materials Engineering China Three Gorges University Yichang, China
国际会议
太原
英文
50-54
2010-10-22（万方平台首次上网日期，不代表论文的发表时间）