Face recognition using vector quantization histogram method

Koji Kotani, Chen Qiu, Tadahiro Ohmi

Research output: Contribution to conferencePaperpeer-review

26 Citations (Scopus)

Abstract

We have developed a very simple yet highly reliable face recognition method called VQ histogram method. A codevector referred (or matched) count histogram, which is obtained by Vector Quantization (VQ) processing of the facial image, is utilized as a very effective personal feature. By applying appropriate low pass filtering and VQ processing to a facial image, useful features for face recognition can be extracted. Experimental results show a recognition rate of 95.6% for 400 images of 40 persons (10 images per person), which contain variations in lighting, posing, and expressions, form publicly available ORL database. Equal Error Rate (ERR) of 2.6% is obtained for the verification experiment. By combining multiple low pass filtering procedures, the recognition rate increases up to 97% or higher.

Original languageEnglish
Publication statusPublished - 2002 Jan 1
EventInternational Conference on Image Processing (ICIP'02) - Rochester, NY, United States
Duration: 2002 Sep 222002 Sep 25

Other

OtherInternational Conference on Image Processing (ICIP'02)
CountryUnited States
CityRochester, NY
Period02/9/2202/9/25

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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