COMPREHENSIVE POTHOLE DETECTION SYSTEM FOR ROAD MAINTENANCE AND SAFETY USING IMAGE PROCESSING AND STEREO VISION

Abstract

This paper introduces a systematic approach to pothole detection, emphasizing its significance in road maintenance and safety. The proposed system is comprised of meticulously designed modules that collectively contribute to achieving accurate and effective results. Commencing with data collection through cameras capturing road areas of interest, the images undergo manual cropping and resizing for standardization. The core principle of the system revolves around image enhancement, involving grayscale conversion, application of blurring techniques, and adjustments to brightness and contrast. Automatic thresholding extracts essential information encoded within pixels, paving the way for precise edge detection refined through morphological operations. The focus then shifts to pothole detection, incorporating a stereo camera setup to calculate depth and disparity of road surfaces. Critical steps, including image rectification, correspondence matching, and disparity calculations, contribute to the accurate identification and delineation of potholes using depth thresholds. Subsequent modules employ K-Means clustering to segregate regions of interest from the image background, and post-processing steps, including filtering, masking, and refinement, fine-tune the images. Utilizing the HSV color space for grayscale image refinement and the connected component method to isolate white pixel objects further enhance the system's capability. The final step involves the addition of bounding boxes around identified potholes, streamlining their identification process. This comprehensive methodology ensures effective image processing, precise pothole detection, and contributes significantly to road safety and maintenance efforts.