DocumentCode
1608510
Title
Improvement of texture image segmentation based on visual model
Author
Jin Ma ; Fuqing Duan ; Ping Guo
Author_Institution
Image Process. & Pattern, Recognition Lab., BNU, Beijing, China
fYear
2012
Firstpage
151
Lastpage
154
Abstract
As an important aspect of image segmentation, texture segmentation has long been one of the hot spots in segmentation field. In this paper, the human visual cognitive model is used as a new texture feature extraction method for image texture segmentation. In order to promote the effect of clustering segmentation method, spatial location information is considered to smooth the segment result. Experiments show that the proposed texture feature descriptor with visual cognitive model is more conducive than that of the Gabor feature.
Keywords
feature extraction; image segmentation; image texture; pattern clustering; Gabor feature; clustering segmentation method; human visual cognitive model; spatial location information; texture feature descriptor; texture feature extraction method; texture image segmentation; Clustering algorithms; Feature extraction; Image segmentation; Noise; Smoothing methods; Vectors; Visualization; Clustering segmentation; Small region elimination; Texture segmentation; Visual cognitive model;
fLanguage
English
Publisher
ieee
Conference_Titel
Sciences of Electronics, Technologies of Information and Telecommunications (SETIT), 2012 6th International Conference on
Conference_Location
Sousse
Print_ISBN
978-1-4673-1657-6
Type
conf
DOI
10.1109/SETIT.2012.6481904
Filename
6481904
Link To Document