Distributed license plate recognition method, system and device based on multi-attribute fusion

Abstract

The invention belongs to the fields of computer vision, pattern recognition and intelligent transportation, and specifically relates to a distributed license plate recognition method, system and device based on multi-attribute fusion, aiming to further improve the accuracy, effectiveness and credibility of license plate recognition results in natural scenes Spend. The system method includes obtaining the license plate image to be recognized; extracting the features of the license plate image as initial features; performing deep encoding on the initial features to obtain the type features related to the type of the license plate image, and obtaining the type prediction result through the image type classifier; The initial features are deeply encoded to obtain the color features related to the license plate color, and the color prediction result is obtained through the image color classifier; the initial features, type features, and color features are fused to perform deep encoding to obtain the text features related to the license plate image. And get the license plate number recognition result through the pre-built character sequence generator. The invention improves the recognition accuracy, effectiveness and reliability.

Description

technical field [0001] The invention belongs to the fields of computer vision, pattern recognition and intelligent transportation, and in particular relates to a distributed license plate recognition method, system and device based on multi-attribute fusion. Background technique [0002] With the rapid development of intelligent transportation systems, the demand for identification and analysis of vehicle information is increasing. Among them, the license plate can most directly and effectively reflect the information of the vehicle, and accurate and efficient identification of license plate information is of great significance to intelligent traffic management. However, due to the complexity and changeability of natural scenes, it is extremely challenging to accurately detect and recognize license plate information. [0003] When the prior art recognizes the license plate information on the road, it first relies on detecting the license plate in a natural scene, and then p...

AI Technical Summary

Problems solved by technology

Since the vehicle is not always at a standstill or moving at a low speed, motion blur will inevitably be caused when it is moving at a high speed; in addition, there will be parts caused by artificially occluded license plates, objects (such as leaves) or too close distances between vehicles Occlusion, which greatly increases the difficulty of license plate recognition

The license plate information is determined only by recognizing the license plate number in the image, without considering the interference caused by changes in the natural environment and the vehicle's own conditions, the error rate of license plate recognition will be high

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