Video image recognition method based on artificial intelligence and related equipment

Abstract

The invention relates to the technical field of artificial intelligence, and provides a video image recognition method based on artificial intelligence. The method comprises the steps of carrying outthe dynamic collection of the forward view angle of a vehicle in a vehicle driving process, and obtaining a plurality of collection data; performing video encoding and video decoding on the pluralityof acquired data to obtain a video image; determining a frame extraction frequency according to the front-end computing power of an embedded central processing unit CPU of the vehicle-mounted equipment; performing frame extraction on the video image according to the frame extraction frequency to obtain a plurality of video frames; sequentially identifying the plurality of video frames to obtain avehicle identification result of the vehicle and a marked line identification result of a traffic marked line passed by the vehicle; according to the vehicle identification result and the marked lineidentification result, analyzing the spatial position relationship between the vehicle and the traffic marked line to obtain a vehicle violation identification result; and uploading the vehicle violation identification result to a block chain. The method can be applied to a smart traffic scene, thereby promoting the construction of a smart city.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence, in particular to an artificial intelligence-based video image recognition method and related equipment. Background technique [0002] With the improvement of social and economic level, the number of various vehicles (such as motor vehicles and non-motor vehicles) shows a high-speed growth trend, which brings great convenience to people's travel. However, the rapid increase of vehicles has brought convenience to people's travel, but there have also been many violations of traffic rules. [0003] At present, cameras are mainly installed at various traffic intersections, and vehicles are captured through the cameras to obtain captured images, and whether the vehicles are illegal is judged through the captured images. However, in this way of forensics, since the cameras installed at each intersection are fixed, they can only capture vehicle images in a limited area, which limits the ...

AI Technical Summary

Problems solved by technology

However, in this way of forensics, since the cameras installed at each intersection are fixed, they can only capture vehicle images in a limited area, which limits the coverage of captured images and makes it difficult to conduct a comprehensive analysis of vehicle behavior.

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