Method and system for providing vehicle exterior damage determination service

An electronic system, the system comprising:

• a camera mounted on a mobile terminal;
• an output device configured to output guide information to guide a capture of a predetermined area via the camera;
• and
• a processor configured to:
• input a first exterior image of a vehicle captured based on the output guide information and a second exterior image of the vehicle stored in advance to a deep learning model;
• match the first exterior image and the second exterior image to acquire a matched image;
• masking a detected area based on a match between the predetermined area and the matched image as a masked area;
• and
• determine whether an exterior of the vehicle has been damaged and a type of damage based on the masked area,
• wherein the determining of whether the exterior of the vehicle has been damaged and the type of damage further comprises:
• generating a probability map from the matched image via image segmentation;
• determining whether the exterior of the vehicle has been damaged via the generated probability map;
• and
• performing masking in pixel units for each type of damage to extract the masking result as damage characteristics information.

A processor-implemented method, the method comprising:

• outputting guide information to direct a motion of a camera of a mobile terminal including the processor to capture an of a predetermined area via;
• training a machine learning model on a first exterior image of a vehicle, the first exterior image being captured based on the output guide information and a second exterior image of the vehicle, the second image being of an undamaged version of the vehicle;
• masking an area from the first image that matches the second image;
• and
• determining whether an exterior of the vehicle has been damaged and a type of damage based on the masked area, wherein the determining of whether the exterior of the vehicle has been damaged and the type of damage further comprises:
• generating a probability map from the matched image via image segmentation;
• determining whether the exterior of the vehicle has been damaged via the generated probability map;
• and
• performing masking in pixel units for each type of damage to extract the masking result as damage characteristics information.