Vehicle Damage Evaluation For Insurance Using Computer Vision

Authors: Praveen, Dr. Sayyada Fahmeeda, Praveen MB, Om

Abstract: The paper presents an intelligent system for automatic vehicle damage assessment using deep learning and computer vision techniques. Traditional insurance claim processes often rely on manual inspections, which are time-consuming, subjective, and error-prone. To overcome these limitations, a Convolutional Neural Network (CNN) model is trained to classify vehicle damage severity into three categories: Minor, Moderate, and Severe. The model is integrated into a Flask-based web application that enables users to upload images, receive real-time predictions, and obtain repair cost estimates along with insurance recommendations. The system demonstrates high accuracy and reliability, offering a scalable solution for insurance automation, improving efficiency, consistency, and decision-making in vehicle damage evaluation.