Detection of Pothole using Image Processing (Open CV)
This project focuses on improving road maintenance through efficient and accurate pothole detection using imaging techniques. Utilizing the Canny edge detection algorithm and applied contour detection in Open CV, we analyze high-resolution images captured from vehicle-mounted cameras. The preprocessing steps include color space transformation and noise reduction to enhance image quality. The algorithm then identifies potential pothole locations and distinguishes real from false positives using similarity functions. This approach aims to enhance road safety by alerting the vehicle driver the presence of potholes and contribute to smart city infrastructure by updating the municipal authorities. Future improvements may integrate additional sensors and machine learning for even more robust detection.
Tools used are: Python OpenCV