Electrooptic pattern recognition system by the use of line-orientation and eigenvector features

방향선소와 고유벡터 특징을 이용한 전기광학적 패턴인식 시스템

  • 신동학 (부경대학교 정보통신공학과) ;
  • 장주석 (부경대학교 정보통신공학과)
  • Published : 1997.10.01


We proposed a system that can perform pattern recognition based on parrallel optical feature extraction and performed experiments on this. The feature to be extracted are both 6 simple line orientations and two eigenvectors of the covariance matrix of the patterns that cannot be distinguished with the line orientation features alone. Our system consists of a feature-extraction part and a pattern-recognition part. The former that extracts the features in parallel with the multiplexed Vander Lugt filters was implemented optically, while the latter that performs the pattern recognition by the use of the extracted features was implemented in a computer. In the pattern recognition part, two methods are tested;one is to use an artificial neural network, which is trained to recognize the features directly, the other is to count the numbers of specific features simply and then to compare them with the stored reference feature numbers. We report the preliminary experimental results tested for 15 alpabet patterns with only straight line segments.



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