GRAPH CUTS BY USING LOCAL TEXTURE FEATURES OF WAVELET COEFFICIENT FOR IMAGE SEGMENTATION

被引：2
|
作者：
Fukuda, Keita [1 ]
Takiguchi, Tetsuya [2 ]
Ariki, Yasuo [2 ]
机构：
[1] Kobe Univ, Grad Sch Engn, Kobe, Hyogo, Japan
[2] Kobe Univ, Org Adv Sci & Technol, Kobe, Hyogo, Japan
来源：
2008 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO, VOLS 1-4 | 2008年
关键词：
Image Segmentation; Graph Cuts; Multiresolution Analysis; Local Texture Feature;
D O I：
10.1109/ICME.2008.4607576
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
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 Wink 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.
引用
收藏
页码：881 / +
页数：2
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