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Comparison of feature extraction methods for head recognition

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Feature extraction plays an important role in head recognition. It transforms an original image into a specific vector to be fed into a classifier. An original image cannot be further processed directly. Raw information in an original image does not represent a specific pattern and a machine cannot understand that information.

Original languageEnglish
Title of host publicationProceedings - 2015 International Electronics Symposium
Subtitle of host publicationEmerging Technology in Electronic and Information, IES 2015
EditorsHendhi Hermawan, Ahmad Zainudin, Syechu Dwitya Nugraha, Erik Tridianto, Hendy Briantoro, Desy Intan Permatasari
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages118-122
Number of pages5
ISBN (Electronic)9781467393454
DOIs
Publication statusPublished - 12 Jan 2016
Event17th International Electronics Symposium, IES 2015 - Surabaya, Indonesia
Duration: 29 Sept 201530 Sept 2015

Publication series

NameProceedings - 2015 International Electronics Symposium: Emerging Technology in Electronic and Information, IES 2015

Conference

Conference17th International Electronics Symposium, IES 2015
Country/TerritoryIndonesia
CitySurabaya
Period29/09/1530/09/15

Keywords

  • Head recognition
  • histogram of transition
  • HOG
  • LBP
  • transition feature

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