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Graph Cuts Segmentation by Using Local Texture Features of Multiresolution Analysis
Keita FUKUDA
Tetsuya TAKIGUCHI
Yasuo ARIKI
Publication
IEICE TRANSACTIONS on Information and Systems Vol.E92-D No.7 pp.1453-1461
Publication Date: 2009/07/01
Online ISSN: 1745-1361
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Image Recognition, Computer Vision
Keyword:
image segmentation,
graph cuts,
multiresolution analysis,
local texture feature,
Full Text: PDF(1.4MB)
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.
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