Traffic sign recognition method and system with depth learning model based on compact neural network

Abstract

The invention relates to a traffic sign recognition method and system with a depth learning model based on a compact neural network, wherein the method and system are suitable for traffic sign detection and recognition in an image or video. The system comprises an image acquisition module, a picture preprocessing module, a traffic sign recognition module, and a voice prompting module. The picture preprocessing module carries out three steps of color positioning, shape detection, and picture zooming to obtain pictures with the same sizes. The traffic sign recognition module is used for classifying and identifying the pre-processed pictures, obtaining a traffic sign classification and recognition result by the trained depth learning model based on a compact neural network, and then transmitting the result to the voice prompting module for voice prompting. According to the system provided by the invention, the compact-neural-network-based depth learning model having advantages of small modules, high precision, low computing consumption, and high transportability to a mobile phone platform and the like serves as a core; and the system has advantages of many type of identified traffic signs, high precision, and good real-time performance.

Description

technical field [0001] The invention relates to a computer vision and machine learning technology, which belongs to the method of target detection and recognition, and specifically relates to a traffic sign recognition method and system based on a compact neural network deep learning model, which is suitable for traffic signs in images or videos detection and identification. Background technique [0002] In recent years, the development of unmanned driving has become more and more mature, and assisted driving has entered the practical stage. Traffic sign recognition is one of the most important modules of the current intelligent assisted driving system and an important part of unmanned driving technology. [0003] The traffic sign recognition module usually includes two aspects: location detection and classification recognition. [0004] In terms of positioning of traffic signs, it is possible to locate areas where traffic signs may exist. The existing results all adopt co...

AI Technical Summary

Problems solved by technology

[0007] The purpose of the present invention is to overcome the defects of the existing traffic sign recognition system based on traditional deep learning, such as high complexity, many parameters, and difficulty in transplanting to mobile platforms.

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