Recognition of the optical image based on the wavelet space feature spectrum entropy

Abstract

With consideration of the low accuracy on image recognition, the feature extraction method for optical images based on the wavelet space feature spectrum entropy is mainly studied. In this method, the principle that the energy is constant before and after the wavelet transformation is employed to construct the wavelet energy pattern matrices, and the feature spectrum entropy of singular value is extracted as the image features by singular value decomposition of the matrix. At the same time, BP neural network is also applied in image recognition. The experimental results show that high image recognition accuracy can be acquired by using the feature extraction method for optical images proposed in this paper, which proves the validity of the method.