Abstract

Human skin detection is an important preliminary stage to improve the performance of other areas of object detection or recognition such as human face detection, hand gesture recognition, and pornography contents detection. Popular methods in this area are processing a single image pixel in HSV or YCbCr color spaces. The limitation of these approaches is they cannot address the wide range of the skin color distribution. This paper proposes a new approach by combining two model of skin color for each pixel into a vector contains color elements of H, S, Cb, and Cr. A set of experiments prove that the method produces an True Positif Rate (TPR) of 93.89% and False Positif Rate (FPR) of 10.75%.

Original languageEnglish
Title of host publicationProceedings of 2014 International Conference on Intelligent Autonomous Agents, Networks and Systems, INAGENTSYS 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages58-61
Number of pages4
ISBN (Electronic)9781479948024
DOIs
Publication statusPublished - 9 Jan 2015
Event2014 International Conference on Intelligent Autonomous Agents, Networks and Systems, INAGENTSYS 2014 - Bandung, Indonesia
Duration: 19 Aug 201421 Aug 2014

Publication series

NameProceedings of 2014 International Conference on Intelligent Autonomous Agents, Networks and Systems, INAGENTSYS 2014

Conference

Conference2014 International Conference on Intelligent Autonomous Agents, Networks and Systems, INAGENTSYS 2014
Country/TerritoryIndonesia
CityBandung
Period19/08/1421/08/14

Keywords

  • HSV
  • RGB
  • YcbCr
  • human skin detection

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