Journal of the Korean Institute of Intelligent Systems (한국지능시스템학회논문지)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Genetic Programming based Illumination Robust and Non-parametric Multi-colors Detection Model

밝기변화에 강인한 Genetic Programming 기반의 비파라미터 다중 컬러 검출 모델

  • 김영균 (서경대학교 전자공학과) ;
  • 권오성 (서경대학교 전자공학과) ;
  • 조영완 (서경대학교 컴퓨터공학과) ;
  • 서기성 (서경대학교 전자공학과)
  • Received : 2010.10.21
  • Accepted : 2010.11.26
  • Published : 2010.12.25
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Abstract

This paper introduces GP(Genetic Programming) based color detection model for an object detection and tracking. Existing color detection methods have used linear/nonlinear transformatin of RGB color-model and improved color model for illumination variation by optimization or learning techniques. However, most of cases have difficulties to classify various of colors because of interference of among color channels and are not robust for illumination variation. To solve these problems, we propose illumination robust and non-parametric multi-colors detection model using evolution of GP. The proposed method is compared to the existing color-models for various colors and images with different lighting conditions.

본 논문은 물체인식이나 영상추적에 사용되는 컬러검출을 위한 GP(Genetic Programming) 기반의 컬러검출 모델을 제안한다. 기존의 컬러검출은 기본적인 RGB 모델에 대한 선형, 비선형 함수의 변환을 사용하거나, 최적화 기법이나 학습기법에 의해 조명 변화에 개선된 컬러 모델을 사용하고 있다. 하지만 대부분의 경우 색상 채널간의 간섭에 의해 다양한 색상에 대한 분류가 어렵고, 조명변화에 강인하지 못하다. 본 연구에서는 GP의 최적화된 학습기법과 모델 생성 기법을 통해 조명변화에 강인하고, 다중의 색상 검출이 가능하며, 파라미터 설정이 필요 없는 컬러 모델을 제안한다. 제안된 방법을 다양한 색상과 조명환경이 다른 영상에 대해서 기존 컬러모델과 비교 분석하였다.

Keywords

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