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 partspsila reliability for object recognition and the skeletonpsilas 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.