A METHOD OF EXTRACTING VISUAL MAIN SKELETON BASED ON COGNITION THEORY
The paper proposes a method for extracting visual main skeleton based on cognition theory about salience of visual parts, which integrates the advantages of the visual main parts reliability for object recognition and the skeletons reduced-dimension for object representation. Because it can simplify skeleton structure and curve shape and make the results of extraction and description in accord with human visual perception, the method not only has good noise elimination effect, but also can be good at solving recognition difficulties aroused by fuzzy boundaries introduced in image segmentation. At the same time, since it can reduce data complexity and quantity in image description, the method can greatly improve the speed and accuracy of automatic recognition, which are good for skeleton representation and object reconstruction based on the skeleton. The experimental results demonstrate that the method is valid.
Visual main skeleton Visual perception Salience of visual parts Discrete curve evolution Image and graphics
GANG XU YU-QING LEI
Department of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China
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
2706-2711
2008-07-12（万方平台首次上网日期，不代表论文的发表时间）