Journal of Korea Multimedia Society (한국멀티미디어학회논문지)

Korea Multimedia Society (한국멀티미디어학회)
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A Study of Efficient Pattern Classification on Texture Feature Representation Coordinate System

텍스처 특징 표현 좌표체계에서의 효율적인 패턴 분류 방법에 대한 연구

  • 우경덕 (세종대학교 대학원 디지털콘텐츠학과) ;
  • 김성국 (세종대학교 대학원 디지털콘텐츠학과) ;
  • 백성욱 (세종대학교 컴퓨터 공학부 디지털콘텐츠학과)
  • Received : 2009.09.14
  • Accepted : 2010.02.01
  • Published : 2010.02.28
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Abstract

When scenes in the real world are perceived for the purpose of computer/robot vision fields, there are great deals of texture based patterns in them. This paper introduces a texture feature representation on a coordinate system in which many different patterns can be represented with a mathematical model (Gabor function). The representation of texture features of each pattern on the coordinate system results in the high performance/competence of texture pattern classification. A decision tree algorithm is used to classify pattern data represented on the proposed coordinate system. The experimental results for the texture pattern classification show that the proposed method is better than previous researches.

컴퓨터/로봇 비전 분야에서 실세계 장면들을 촬영할 때, 상당 부분의 텍스처 기반 패턴들이 발견되는데, 본 논문에서는 그런 다양한 패턴들을 적절하게 표현할 수 있는 수학적 모델(Gabor 함수)을 기반으로 한 특징 측정 좌표 체계를 소개한다. 그 체계를 통한 텍스처 패턴의 여러 특징들에 대한 측정값의 표현은 텍스처 패턴분류 작업을 수행하는데 보다 효율적인 성능을 가능케 한다. 또한 실험에 사용된 텍스처 이미지 데이터의 좌표 체계에서의 표현 정보가 추후 유사 연구들에 의해 활용될 수 있으며, 제안된 좌표 체계에서 표현된 패턴 데이터를 분류하는데 가장 적합한 의사결정나무 알고리듬을 사용한다. 최종적으로, 다양한 텍스처 패턴분류 실험을 통해 기존 연구 방법들에 비해 연구 결과의 개선이 있음을 보여준다.

Keywords

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