Texture Image Optimization Segmentation Based on the SLIC Algorithm

被引：0
|
作者：
Li, Ji-chun
Zhang, En-cai
Zhang, Kun
Chen, Guan-can [1 ]
机构：
[1] Fujian Normal Univ, Key Lab OptoElecton Sci & Technol Med, Minist Educ, Fuzhou 350007, Peoples R China
来源：
INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE: TECHNIQUES AND APPLICATIONS, AITA 2016 | 2016年
关键词：
Superpixel; Segmentation; Texture image; Optimization;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The superpixels gathered by high similar pixels can effectively reduce the redundancy of the image and the complexity of the subsequent image processing. In this paper, a new method combined with SLIC (simple linear inerative clustering) algorithm and the energy optimization function to segment texture image is proposed. SLIC approach is used to obtain the initial superpixels, and optimization function can relocate new center points to creat more homogeneous superpixels. It has been shown that this method performs better adaptability in the complex texture image.
引用
收藏
页码：205 / 209
页数：5
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