Face detection using TSK-type fuzzy cerebellar model articulation controller network

Jyun Guo Wang, Shen Chuan Tai, Cheng Jian Lin

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Face detection is a topic concerning businesses that use security surveillance 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 generalization generalizaMlity 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 problems of face variation and complex backgrounds.

Original languageEnglish
Pages (from-to)707-717
Number of pages11
JournalInternational Journal of Innovative Computing, Information and Control
Volume11
Issue number2
Publication statusPublished - 2015 Jan 1

Fingerprint

Face Detection
Fuzzy Model
Face recognition
Controller
Controllers
Surveillance
Skin
Lighting
Face
Color
Data storage equipment
Computing
Requirements
Experimental Results
Industry
Model
Background
Business
Generalization
Learning

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Information Systems
  • Computational Theory and Mathematics

Cite this

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Face detection using TSK-type fuzzy cerebellar model articulation controller network. / Wang, Jyun Guo; Tai, Shen Chuan; Lin, Cheng Jian.

In: International Journal of Innovative Computing, Information and Control, Vol. 11, No. 2, 01.01.2015, p. 707-717.

Research output: Contribution to journalArticle

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