A feature extraction method for personal identification system

Hironori Takimoto, Yasue Mitsukura, Minoru Fukumi, Norio Akamatsu

Research output: Contribution to journalConference articlepeer-review

Abstract

Recently in the world, many researches for individual identification method using biometrics are widely done. Especially, personal identification using faces are used because of needless for physical contact. However, when the number of registrant of a system increase, the recognition accuracy of system will get worse certainly. Therefore, in order to improve the recognition accuracy, it is necessary to extract the feature area effectively for getting the high recognition accuracy. In this paper, we analyze and examine about the individual feature in a face using the GA and the SPCA. Thus, by removing the area which is not valuable, we think that recognition accuracy becomes high. Then, in order to show the effectiveness of the proposed method, we show computer simulations by using real image.

Original languageEnglish
Pages (from-to)601-608
Number of pages8
JournalLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
Volume2773 PART 1
DOIs
Publication statusPublished - 2003 Jan 1
Externally publishedYes
Event7th International Conference, KES 2003 - Oxford, United Kingdom
Duration: 2003 Sep 32003 Sep 5

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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