대한전자공학회논문지SP (Journal of the Institute of Electronics Engineers of Korea SP)

대한전자공학회 (The Institute of Electronics and Information Engineers)
권호 표지

자동 목표물 인식 시스템을 위한 클러스터 기반 투영기법과 혼합 전문가 구조

Cluster-based Linear Projection and %ixture of Experts Model for ATR System

  • 신호철 (한국과학기술원 전자전산학과) ;
  • 최재철 (한국과학기술원 전자전산학과) ;
  • 이진성 (한국과학기술원 전자전산학과) ;
  • 조주현 (한국과학기술원 전자전산학과) ;
  • 김성대 (한국과학기술원 전자전산학과)
  • 발행 : 2003.05.01
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초록

In this paper a new feature extraction and target classification method is proposed for the recognition part of FLIR(Forwar Looking Infrared)-image-based ATR system. Proposed feature extraction method is "cluster(=set of classes)-based"version of previous fisherfaces method that is known by its robustness to illumination changes in face recognition. Expecially introduced class clustering and cluster-based projection method maximizes the performance of fisherfaces method. Proposed target image classification method is based on the mixture of experts model which consists of RBF-type experts and MLP-type gating networks. Mixture of experts model is well-suited with ATR system because it should recognizee various targets in complexed feature space by variously mixed conditions. In proposed classification method, one expert takes charge of one cluster and the separated structure with experts reduces the complexity of feature space and achieves more accurate local discrimination between classes. Proposed feature extraction and classification method showed distinguished performances in recognition test with customized. FLIR-vehicle-image database. Expecially robustness to pixelwise sensor noise and un-wanted intensity variations was verified by simulation.

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참고문헌

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