基于小波预处理的神经网络字符识别方法

Character Recognition Based on Wavelet Preconditioning and Neural Network

提出了一种基于小波变换预处理的神经网络法的字符识别法,利用小波变换对字符进行了预处理,提取文字字符的主要能量特征,减少了字符特征识别的维数,与直接采用神经网络方法进行字符识别相比,所用的神经网络规模小,收敛速度快,能有效识别含有噪声的低质量模糊文字字符.

A new method of character recognition based on the wavelet precondifioning and neural network is introduced. Character is preconditioned by wavelet transfore, and the energy characteristics are drawn. This method reduces the dimension number of character recognition, has higher rate of convergency and smaller network size than the neural network way without wavelet preconditioning, and exhibits a better and more effective recognition of the fuzzy noise-containing characters.