Journal of the Korean Society of Industry Convergence (한국산업융합학회 논문집)

The Korean Society of Industry Convergence (한국산업융합학회)
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An Effeicient Fingerprint Recognition Using Adaptive Principal Component Analysis

적응적 주요성분분석 기법을 이용한 효율적인 지문인식

  • Sung, Ju-Won (School of Computer Information and Electronics Eng., Youngdong University) ;
  • Cho, Yong-hyun (School of Computer Into. and Com. Eng., Catholic University of Daegu)
  • 성주원 (영동대학교 정보전자공학부 컴퓨터공학전공) ;
  • 조용현 (대구가톨릭대학교 컴퓨터정보통신공학부)
  • Received : 2000.11.06
  • Accepted : 2001.05.25
  • Published : 2001.05.31
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Abstract

This paper proposes an efficient method for recognizing the fingerprint using the extracted features by adaptive principal component analysis(PCA). The adaptive PCA is implemented by a single-layer neural network for extracting the linear features of fingerprint data. And, the extracted data are transformed into binary data for reducing storage space and transmission time. The proposed method has been applied to recognize the 100 fingerprint data. The simulation results show that the recognitions are all successful and capable of about ${\pm}8^{\circ}$ rotated data.

Keywords