International Journal of Applied Mathematics and Machine LearningAuthor's: Qi Hu, Shuang Zhang, Xiaofeng Dong, Xiuyi Sun, Xinwen Wang and Shuaiqi Liu
Pages: [1] - [11]
Received Date: November 24, 2017
Submitted by: Jianqiang Gao
DOI: http://dx.doi.org/10.18642/ijamml_7100121899
Infrared image is widely used in medicine, military field and people’s daily life. Infrared image segmentation is the basis of infrared image processing. In order to analyze other infrared images better, we propose a new segmentation algorithm of infrared image based on local statistical active contour and mathematical morphology. Firstly, the infrared image is processed to enhance the edge and smooth noise of the image; secondly, a novel locally statistical active contour model (ACM) is applied to infrared image segmentation; finally, we combine with mathematical morphology method to study the target and interference body adhesion problem of infrared image in the segmentation. The experiments show that this algorithm can be effectively used for infrared image segmentation.
level set, infrared image segmentation, local statistical active countour.
