Translation, rotation and scale invariant pattern recognition using spectral analysis and a hybrid genetic-neural-fuzzy networks

스펙트럴분석 및 복합 유전자-뉴로-퍼지망을 이용한 이동, 회전 및 크기 변형에 무관한 패턴인식

This paper proposes a method for pattern recognition using spectral analysis and a hybrid genetic-neural-fuzzy networks. The feature vectors using spectral analysis on contour sequences of 2-D images are extracted, and the vectors are not effected by translation, rotation and scale variance. A combined model using the advantages of conventional method is proposed, those are supervised learning BP, global searching genetic algorithm, and unsupervised learning fuzzy c-method. The proposed method is applied to 10 aircraft recognition to confirm the performance of the method. The experimental results show that the proposed method is better accuracy than conventional method using BP or fuzzy c-method, and learning speed is enhanced.