Advanced Algorithm Partitioning of Markov and Color Image Segmentation

被引：0
|
作者：
Toure, Mohamed Lamine [1 ]
Zou Beiji [1 ]
Musau, Felix [1 ]
机构：
[1] Cent South Univ, Sch Infonnat Sci & Engn, Changsha 4100S3, Hunan, Peoples R China
来源：
PROCEEDINGS OF 2010 3RD IEEE INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND INFORMATION TECHNOLOGY, VOL 9 (ICCSIT 2010) | 2010年
基金：
中国国家自然科学基金;
关键词：
Fuzzylmage; Markov; Normalizedcut; Segmentation; Similarities;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
The color vision systems require a first step of classifying pixels in a given image into a discrete set of color classes. In this paper we introduce a new method of algorithm partitioning, and color image segmentation based on similarities or dissimilarities of the pixels. We consider fuzzy segmentation with markov, and normalized cut method. Experiments show these different processes used an effective solution on natural images, and computational efficiency. Finally, the algorithm has proven our process of experiments on gray scale, color, and texture images show promising segmentation results successful.
引用
收藏
页码：719 / 723
页数：5
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