The image classification using a neural network by Zernike moment

A method of image classification using a neural network, which is a three-layer perceptron, is described. The image features are obtained by using a Zernike moment. The following conclusions are drawn from a large number of experiments about the 26 alphabets: The accuracy of the classification of the neural network is high. For various images without noise, the classical accuracy can reach 100%; for images with noises, the effect is also very good. When the ratio of the signal to noise is down to 12 dB, the classification accuracy is still 95%, with greater decrease of the ratio, the classification declines quickly. The neural network does not require many trained samples. For conditions of fewer learned samples, the effect of detection is good