Robust gray image target recognition base on multi-channel Gabor wavelet filters

The method of low quality gray image target recognition is based on multi-channel Gabor wavelets feature. Multi-channel wavelet filters are designed by mostly Gabor wavelet. Its center frequency is the range from low frequency to high frequency, and its orientation and scale are different. Gary image is directly transformed by these wavelet filters, the feature of extracting gray image target is denoted by the coefficients of Gabor wavelet transform and its standard variance, and the wavelet feature is normalized and input improved BP neural networks to classify. Finally, imitate experimentation is made by using 4 types plane gray image. The results indicate this method can effectively extract texture feature of gray image target, and has robustness to noise and change of target shape. Neural network's training time is reduced to 10 minutes, and recognition rate is 94% in applying this method to gray image target recognition.