Identification method of mobile number plate based on three-channel parallel artificial nerve network

Abstract

The invention relates to a floating number plates discriminating method, which is based on the three-road parallel manmade nerve-net. The identify steps are that adopting the video burst mode to catch the video automatically for the collection of video pictures of the moving vehicle, character cutting the part of pictures of the number plates and then being the input signal of the nerve-net; said nerve-net adopts three standard self-adapt vibrate net each of which has its own work, the three nets are the Chinese characters identify net, the English characters identify net and the data identify net, all of which identify the inputted vector signals at one time, and outputs the most similar sort unity respectively, through controlling the property of the Territory value and the identify accurately according to the number plates and filter, at last add a color property of number plates as the output of the discriminating results. Adopting the method of the invention can identify the number plates of vehicle fast and accurately under the largest driving speed of the vehicles.

Description

Technical field: [0001] The invention relates to a number plate recognition method, more specifically to a method for recognizing a target number plate for a running vehicle. Background technique: [0002] As the object to be managed and controlled, the identity of the moving car must be confirmed. At present, various intelligent transportation application systems based on video recognition of automobile license plates mainly include: automatic identification system for running red lights at intersections, on-site penalty system for vehicle speeding, vehicle identification system at checkpoints, automatic toll payment system for vehicles, automatic management system for parking lots, mobile electronic police system, etc., as the key sensor device of the above-mentioned system, the automatic license plate recognition system must have the characteristics of fast, accurate and easy to obtain, so as to achieve the practical purpose. [0003] At present, there are mainly three m...

AI Technical Summary

Problems solved by technology

From the perspective of specific applications, there are only related applications in BP network technology at present, but BP network has long training period, slow clustering convergence, poor adaptability, and extreme value problems may occur

Regarding the ART network technology, no practical application has been found in number plate recognition. At the same time, the existing ART network has the problem of contradiction between accuracy and class diffusion.

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