Graph Cuts Segmentation by Using Local Texture Features of Multiresolution Analysis

被引：2
|
作者：
Fukuda, Keita [1 ]
Takiguchi, Tetsuya [2 ]
Ariki, Yasuo [2 ]
机构：
[1] Kobe Univ, Grad Sch Engn, Kobe, Hyogo 6578501, Japan
[2] Kobe Univ, Org Adv Sci & Technol, Kobe, Hyogo 6578501, Japan
来源：
IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS | 2009年 / E92D卷 / 07期
关键词：
image segmentation; graph cuts; multiresolution analysis; local texture feature; IMAGE SEGMENTATION;
D O I：
10.1587/transinf.E92.D.1453
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper proposes an approach to image segmentation using Iterated Graph Cuts based on local texture features of wavelet co-efficients. 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.
引用
收藏
页码：1453 / 1461
页数：9
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