| Traffic safety is a perpetual theme in the development of automobile traffic,with the rapid increase of vehicle population,road traffic accidents,particularly the high incidence of serious accidents(such as successive rear-end collision on highway ), safety problems have become increasingly prominent.That is why the intelligent traffic emerged.As an important system,the detection and recognition of traffic signs is becoming one of the hot spots in the international research field of the Intelligent Transportation System.Which based on the technique of image processing.Although many algorithms for recognition of traffic signs are developed and they play the important roles in some Practice instances,they also have some essenlial drawbacks and deficiencies.So it is important to study the refinement algorithms with the more real-time and beter precision using the new developedt techniques and theories for their applications.At the same time,as a type problem in pattem recognition,the study of recognition of traffic signs can make Progress in the field of Pattern recognition both at the theories and techniques.The Purpose of this paper is to utilize the Predominance of the wave let neural network for the recognition of images.This paper revolves around the central task of image identification,It is mainly about collecting and preprocessing the original data of target images,methods of invariable feature extraction and the identification technology of the wavelet neural network..Image processing based on pattern recognition is one of the most importantresearch directions in the image recognition field with the computer technologydevelopment.The main content of this paper is the application of Hough transform andmoment invariants theory in pattern recognition.In this article, patternrecognition is used as theory foundation and image process technology as basictechnology.Combining with the new theory tools(neural networks). |
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