Human Face Detection System by Kenzan NET with preprocess analyzing hyperspectral image

Takakazu Chashikawa, Keizo Fujii, Yoshiyasu Takefuji

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes a neural network system to detect human faces. Our scheme is composed of a preprocess and KenzanNET. Preprocessing analyzes hyperspectral images by using a hybrid self-organizing classification model to extract skin area and making a facial candidate pattern based on the extracted skin area. KenzanNET discriminate a face from other body parts. KenzanNET is a kind of feed forward neural network and is made from CombNET [ I[ improved by an additional learning function. Under the various conditions in terms of background and brightness in a room and the distance between people and camera, our system can detect human face with 76.9% accuracy.

Original languageEnglish
Title of host publicationProceedings of the 2nd International Conference on Intelligent Processing and Manufacturing of Materials, IPMM 1999
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages453-458
Number of pages6
Volume1
ISBN (Electronic)0780354893, 9780780354890
DOIs
Publication statusPublished - 1999 Jan 1
Event2nd International Conference on Intelligent Processing and Manufacturing of Materials, IPMM 1999 - Honolulu, United States
Duration: 1999 Jul 101999 Jul 15

Other

Other2nd International Conference on Intelligent Processing and Manufacturing of Materials, IPMM 1999
CountryUnited States
CityHonolulu
Period99/7/1099/7/15

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Materials Science (miscellaneous)

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