Face Detection Using TSK-type Fuzzy Cerebellar Model Articulation Controller Network

Please use this identifier to cite or link to this item: http://ir.lib.ncut.edu.tw/handle/987654321/5971

Title:	Face Detection Using TSK-type Fuzzy Cerebellar Model Articulation Controller Network
Authors:	Jyun-Guo Wang, Shen-Chuan Tai, and Cheng-Jian Lin
Contributors:	圖書館
Keywords:	skin tone Color transformation Lighting compensation TsK-type cere- bellar model articulation controller Fuzzy system
Date:	2015-04
Issue Date:	2016-10-20 15:47:18 (UTC+8)
Abstract:	Face detection is a topic concerning businesses that use security surveil- lance systems, and accurate detection is critical for the subsequent analysis of images used in facial recognition. In this study, we propose a face-detection method that involves using lighting compensation, skin-color analysis, and a TSK-type fuzzy cerebellar model articulation controller (TSK-type FCMAC) network. The proposed TSK-type FCMAC network has some advantages, such as include its fast rapid learning property, good gen- eralization generalizability capability, easy to ease of implementation, and small lower required computing computer-memory requirements. Our experimental results confirm that the proposed method outperforms other models and effectively overcomes the prob- lems of face variation and complex backgrounds
Relation:	International Journal of Innovative Computing, Information and Control, 11(4)
Appears in Collections:	[Department of Computer Science and Information Engineering] 【資訊工程系所】期刊論文

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