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Graph cuts by using local texture features of wavelet coefficient for image segmentation

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3 Author(s)
Keita Fukuda ; Graduate School of Engineering, Kobe University, Japan ; Tetsuya Takiguchi ; Yasuo Ariki

This paper proposes an approach to image segmentation using iterated graph cuts based on local texture features of wavelet coefficient. Using multiresolution analysis based on Haar wavelet, low-frequency range (smoothed image) is used for n-link and high-frequency range (local texture features) is used for t-link along with color histogram. The proposed method can segment the object region with noisy edges and colors similar to the background, but heavy texture change. Experimental results illustrate the validity of our method.

Published in:

2008 IEEE International Conference on Multimedia and Expo

Date of Conference:

June 23 2008-April 26 2008