Computer vision technology has advanced significantly in recent years, and it has the potential to automate various visual inspection tasks. Here's a general approach that could be applied to estimate PDR hail damage using a vision system:

Data Collection: Collect a large dataset of images or videos that contain vehicles withhail damage. The dataset should include a diverse range of vehicle types, dent sizes, lighting conditions, and angles.

Training: Use the annotated dataset to train a computer vision model, such as a convolutional neural network (CNN), to learn the patterns and characteristics of hail damage. The model should be trained to detect and classify different dent sizes and shapes.

Preprocessing: Before feeding the images or video frames into the trained model, it may be necessary to preprocess them to enhance the features relevant to hail damage. This preprocessing can involve techniques like contrast adjustment, edge detection, or noise reduction.

Detection and Estimation: Apply the trained model to new images or video frames to detect and localise hail damage. The model should be able to identify the dents and estimate their severity based on predefined criteria (e.g., dent size, depth, and surface area affected).

Output and Analysis: The vision system can generate a report or provide visual overlays indicating the detected hail damage and its estimated severity. This information can be used by PDR technicians or insurance adjusters to assess the repair needs and estimate the cost.

Developing an accurate and reliable vision system for estimating hail damage is a complex task. Factors such as lighting conditions, image quality, and variations in dent appearance can affect the system's performance. Elscope's vision arch scanner, through the technology of vision and AI, automatically recognises the damage to the appearance of the car body due to hail, the size and number of pits, generates a test report, and then goes through the insurance claim process. At present, more and more PDR industries are adopting the Elscope Vision Arch scanner, which plays a great role in improving work efficiency and reducing costs.