Journal of the Korean Society of Industry Convergence (한국산업융합학회 논문집)
- Volume 8 Issue 3
- /
- Pages.143-148
- /
- 2005
- /
- 1226-833X(pISSN)
- /
- 2765-5415(eISSN)
Face Recognition by Using Principal Component Anaysis and Fixed-Point Independent Component Analysis
주요성분분석과 고정점 알고리즘 독립성분분석에 의한 얼굴인식
- Cho, Yong-Hyun (School of Compter & Information Comm., CUD.)
- 조용현 (대구가톨릭대학교 컴퓨터정보통신)
- Received : 2004.12.04
- Accepted : 2005.07.20
- Published : 2005.08.31
Abstract
This paper presents a hybrid method for recognizing the faces by using principal component analysis(PCA) and fixed-point independent component analysis(FP-ICA). PCA is used to whiten the data, which reduces the effects of second-order statistics to the nonlinearities. FP-ICA is applied to extract the statistically independent features of face image. The proposed method has been applied to the problems for recognizing the 20 face images(10 persons * 2 scenes) of 324*243 pixels from Yale face database. The 3 distances such as city-block, Euclidean, negative angle are used as measures when match the probe images to the nearest gallery images. The experimental results show that the proposed method has a superior recognition performances(speed, rate). The negative angle has been relatively achieved more an accurate similarity than city-block or Euclidean.
Keywords
- Face Recognition;
- Principal Component Analysis;
- Independent Component Analysis;
- Fixed-point Algorithm;
- Feature Extractions