Title :
Active contour model based on LTP code for texture image segmentation
Author :
Guannan Chen ; Yao Liu ; Haiming Gong ; Yan Li ; Rong Chen
Author_Institution :
Key Lab. of Optoelectron. Sci. & Technol. for Med., Fujian Normal Univ., Fuzhou, China
Abstract :
In this paper, a novel algorithm is proposed for unsupervised segmentation that incorporates a Local Trinary Pattern (LTP) code representation of textures under a geometric active contour framework. First, by combining the gray levels of pixels with texture information of an image, this method can be used for segmentation of a texture image or a non-texture image. And then, the method is modified to avoid the additional computation problem without re-initialization repeatedly. The simulation experiments show that the proposed segmentation method is more efficient and accurate.
Keywords :
codes; image coding; image segmentation; image texture; active contour model; image texture information; local trinary pattern code; texture image segmentation; unsupervised segmentation; Active contour model; Level set method; Local Trinary Pattern; Texture image segmentation;
Conference_Titel :
Information Science, Electronics and Electrical Engineering (ISEEE), 2014 International Conference on
Conference_Location :
Sapporo
Print_ISBN :
978-1-4799-3196-5
DOI :
10.1109/InfoSEEE.2014.6948147