Combined color and texture segmentation based on fibonacci lattice sampling and mean shift

Authors:
Chang Yuchou;Zhou Yue;Wang Yonggang
Affiliations:
Institute of Image Processing and Pattern Recognition, Shanhai Jiaotong University, Shanghai, China;Institute of Image Processing and Pattern Recognition, Shanhai Jiaotong University, Shanghai, China;Institute of Image Processing and Pattern Recognition, Shanhai Jiaotong University, Shanghai, China
Venue:
ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
Year:
2005

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Abstract

A novel segmentation algorithm for natural color image is proposed. Fibonacci Lattice-based Sampling is used to get the color labels of image so as to take advantage of the traditional approaches developed for gray-scale images. Using local fuzzy homogeneity derived from color labels, texture component is calculated to characterize spatial information. Color component is obtained by peer group filtering. To avoid over-segmentation of texture areas in a color image, these color and texture components are jointly employed to group the pixels into homogenous regions by the mean shift based clustering. Finally, experiments show very promising results.