Bus lane occupation vehicle-mounted snapshot processing system based on 5G communication

Abstract

The embodiment of the invention provides a bus lane occupation vehicle-mounted snapshot processing system based on 5G communication, and the system is characterized in that an image collection unit collects an original image; an image analysis unit analyzes a first target image from the original image; a license plate recognition unit recognizes complete license plate information from the first target image; the image analysis unit analyzes a second target image from the original image; and the license plate recognition unit recognizes complete license plate information from the second target image. According to the embodiment of the invention, the license plate information of the social vehicles occupying the bus lane is identified as little as possible, the data volume of the snapshot processing of the social vehicles is reduced, and the consumption of system resources is reduced. In addition, under the condition that license plate information of social vehicles occupying bus lanes is recognized as little as possible, the license plate recognition range can be expanded to non-bus lanes, and therefore the integrity of license plate information recognition is improved.

Description

Technical field [0001] The present invention relates to the field of image processing, and in particular, to a 5G communication, an occupied bus trapping processing system. Background technique [0002] Bus Tao (Bus Special Road) has been adopted by major cities due to its characteristics of their investment provinces, fast effectiveness and low technical requirements. However, bus channels are often occupied by social vehicles, affecting the normal driving of the bus. Therefore, it is especially necessary to establish a capture processing system that occupies a bus lane based on the establishment of a bus lane. [0003] At present, the capture treatment scheme of the bus lane is mainly used in a fixed mode, that is, capturing social vehicles occupying bus lanes on the roadside installation monitoring system. However, due to the position of the monitoring system is fixed, the driver of social vehicles is easy to identify, thereby bypassing the monitoring area, resulting in the pr...

AI Technical Summary

Problems solved by technology

However, the images collected by the camera installed on the front of the bus contain a large number of social vehicles, and the capture and processing of a large number of social vehicles will consume huge system resources

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