A Comparative Study on Fuzzy-Clustering-Based Lip Region Segmentation Methods

被引：0

作者：

Wang, Shi-Lin ^{[1
]}

Cao, An-Jie ^{[1
]}

Chen, Chun ^{[1
]}

Wang, Ruo-Yun ^{[1
]}

Machabert, Nicolas ^{[2
]}

机构：

[1] Shanghai Jiao Tong Univ, Sch Informat Secur Engn, Shanghai, Peoples R China

[2] Univ Burgundy, Ecole Super Ingenieurs Rech Mat & Infotron ESIREM, Dijon, France

来源：

2010 INTERNATIONAL CONFERENCE ON BIO-INSPIRED SYSTEMS AND SIGNAL PROCESSING (ICBSSP 2010) | 2010年

关键词：

lip segmentation; fuzzy clustering; spatial information; temporal information; visual speech recognition; IMAGES;

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：

As the first step of many lip-reading or visual speaker authentication systems, lip region segmentation is of vital importance. And fuzzy clustering based methods have been widely used in lip segmentation. In this paper, four fuzzy clustering based lip segmentation methods have been elaborated with their underlying rationale. Experiments have been carried out evaluate their performance comparatively. From the experimental results, SFCM has the best efficiency and FCMST has the best segmentation accuracy.

引用

页码：80 / 82

页数：3

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