Binary neural network license plate recognition method and system based on FPGA

Abstract

The invention relates to a binary neural network license plate recognition method and system based on FPGA, and the method comprises the steps: 1, carrying out the refinement of an input image throughan image preprocessing module, and obtaining a grey-scale map; 2, further processing the grey-scale map by using a license plate positioning and extracting module to complete positioning and extracting of the license plate; 3, segmenting the positioned and extracted license plate characters by using a license plate character segmentation module, and binarizing the segmented license plate characters to form image blocks with fixed sizes; 4, training a binary neural network in the binary neural network module; and utilizing the trained binary neural network model to identify image blocks with fixed sizes, outputting a result. The system matched with the method comprises an image preprocessing module, a license plate positioning extraction module, a license plate character segmentation module and a binary neural network module and is realized based on an FPGA platform. According to the invention, the neural network and the FPGA hardware are combined, the advantages of the neural networkand the FPGA hardware are brought into full play, and high efficiency and low power consumption are realized while the license plate recognition precision is ensured.

Description

technical field [0001] The invention relates to the technical field of machine learning, in particular to an FPGA-based binary neural network license plate recognition method and system. Background technique [0002] With the rapid development of the economy, there are more and more vehicles. Whether it is a residential area or a variety of public places, there will be a large number of vehicles. In order to facilitate management and ensure personal and property safety, the collection, identification and preservation of license plate information is becoming more and more important. . [0003] In addition, the traffic system is becoming more and more intelligent, and the collection and recognition of license plates is an important part, which is more and more widely used in intelligent traffic systems such as traffic monitoring systems, high-speed automatic toll collection systems, and traffic flow detection systems. [0004] In recent years, with the development of artifici...

AI Technical Summary

Problems solved by technology

However, the traditional neural network based on floating-point operations has a large number of parameters and a large amount of calculation, which requires a lot of computing resources.

On the other hand, the deep learning algorithm based on GPU (Graphics Processing Unit), when performing license plate recognition, uses pure software to extract the license plate outline and character outline, which will inevitably reduce the efficiency of processing large amounts of data.

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