Method, device, electronic equipment and system for image-based vehicle damage assessment

Abstract

The embodiment of the present application discloses an image-based vehicle damage assessment method, device, electronic equipment and system. The method includes acquiring an image to be processed; detecting the image to be processed, and identifying a first vehicle part in the image to be processed; using and identifying a part containing a vehicle part in a partial image of the image to be processed that has not identified a vehicle part Perform image matching on the image to determine the second vehicle part to which the partial image belongs; detect the image to be processed, and identify the damaged part and damage type therein; according to the identified first vehicle part, the second vehicle part and the damaged part and The damage type determines the damage part in the image to be processed, the damage part and the damage type corresponding to the damage part. By using various embodiments of the present application, specific information such as damage locations and degrees of vehicle components can be quickly, accurately, and reliably detected, making damage determination results more accurate and reliable, and improving user service experience.

Description

technical field [0001] The present application belongs to the technical field of computer image data processing, and in particular relates to an image-based vehicle damage assessment method, device and electronic equipment. Background technique [0002] After a traffic accident, it is often necessary to wait for the claims adjuster of the insurance company to go to the scene to deal with it, and obtain the basis for the claim by taking pictures. With the increase in the number of motor vehicles in recent years, the number of traffic accidents per year has been at a high level. However, the processing of vehicle claims and loss determination business often needs to rely on the human on-site processing of professional insurance staff, which has high cost, long waiting period and low processing efficiency. [0003] At present, there are some processing methods in the industry that use the images of the traffic accident scene to automatically analyze and obtain the classificati...

AI Technical Summary

Problems solved by technology

In addition, its algorithm only uses CNN's general object recognition algorithm, and the final result of vehicle damage assessment still relies on manual assessment, which requires a large amount of manpower and time, and different insurance companies have inconsistent assessment standards for vehicle damage, coupled with the influence of human subjective factors. The difference in the loss assessment results is large and the reliability is low

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