Research On Parts Recognition Application Using Wavelet And BP Neural Network

Mechanical parts auto-test is an important segment of manufacture system. Modern manufacture technology has been widely use the auto-test and product-recognize technology to ensure the quality of product and even to make manufacture system run in more reliable. It is a key segment in the process of manufacturing industry information. So the computer vision test technology has very important use in test of product's quality and of manufacture process of manufacturing industry.If we want to realize the auto-test of mechanical part, first of all, we should get the image of part through certain testing and collecting equipment, and make the part digitalize. And then we can get the type of part by pattern recognition.This paper revolves around the central task of image identification. It is mainly about the basic principle of Machine vision recognition system, collecting and preproeessing the original data of target images, methods of invariable feature extraction and the identification technology of the artificial neural network. According to the disadvantage of speed and precision in parts recognition system, this paper carries on the contrast research to research result result of study and present conditions at home and abroad, put forward a parts recognition technology based on wavelet and BP neural network. This method combine together the thought of wavelet transform theories and the BP nerve network, completed the on-line parts recognition finally.The purpose of this thesis is to utilize the predominance of the wavelet transform and artificial neural network for the recognition of images.Results prove that this method can not only improve veracity but also can improve antinoise ability.