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Graph Cuts Segmentation by Using Local Texture Features of Multiresolution Analysis

Keita FUKUDA, Tetsuya TAKIGUCHI, Yasuo ARIKI

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Summary :

This paper proposes an approach to image segmentation using Iterated Graph Cuts based on local texture features of wavelet coefficients. Using Haar Wavelet based Multiresolution Analysis, the low-frequency range (smoothed image) is used for the n-link and the high-frequency range (local texture features) is used for the t-link along with the color histogram. The proposed method can segment an object region having not only noisy edges and colors similar to the background, but also heavy texture change. Experimental results illustrate the validity of our method.

Publication
IEICE TRANSACTIONS on Information Vol.E92-D No.7 pp.1453-1461
Publication Date
2009/07/01
Publicized
Online ISSN
1745-1361
DOI
10.1587/transinf.E92.D.1453
Type of Manuscript
PAPER
Category
Image Recognition, Computer Vision

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