Analysis of 2-Dimensional Object Recognition Using discrete Wavelet Transform

이산 웨이브렛 변환을 이용한 2차원 물체 인식에 관한 연구

  • 박광호 (전남대 기계공학과 공학과) ;
  • 김창구 (전남대 기계공학과 공학과) ;
  • 기창두 (전남대 기계공학과)
  • Published : 1999.10.01


A method for pattern recognition based on wavelet transform is proposed in this paper. The boundary of the object to be recognized includes shape information for object of machine parts. The contour is first represented using a one-dimensional signal and normalized about translation, rotation and scale, then is used to build the wavelet transform representation of the object. Wavelets allow us to decompose a function into multi-resolution hierarchy of localized frequency bands. The recognition of 2-dimensional object based on the wavelet is described to analyze the shape of analysis technique; the discrete wavelet transform(DWT). The feature vectors obtained using wavelet analysis is classified using a multi-layer neural network. The results show that, compared with the use of fourier descriptors, recognition using wavelet is more stable and efficient representation. And particularly the performance for objects corrupted with noise is better than that of other method.