MAKERS BASED LEVEL SET METHOD FOR IMAGE SEGMENTATION
This paper presents a novel image segmentation method based on the integration of level set and marker methods. The two distinct techniques for image processing are combined in a manner to utilize the strengths of both. The internal markers obtained by extended-maxima transform bring a priori knowledge to bear on the image segmentation. The initial level set function is constructed from region of interest (ROI) on the internal markers. In this way, an automatic initialization of the level set evolution can be obtained, and the boundaries of the objects can be extracted. The cost time does not depend on the size of the image but the region of internal marker because only level set function with markers is updated instead of the level set function for each pixel. Therefore, the consumed time is greatly reduced. The efficiency and accuracy of the method are demonstrated by the experiments on the real blood vessel images and MR image.
Image Segmentation Level Set Markers Priori Knowledge Eztended-Mazima Transform
SHENG ZHENG CHANG-CAI YANG SHI-LING XIANG JIN YE
Institute of Intelligent Vision & Image Information, College of Electrical Engineering & Information Automation Department, College of Electrical Engineering & Information Technology, China Three Gorge
国际会议
2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)
昆明
英文
947-952
2008-07-12（万方平台首次上网日期，不代表论文的发表时间）