Potholes are a major defect on roads, causing damage to vehicles and putting drivers and pedestrians at risk. The usual way of identifying potholes involves manual inspections, which are time-consuming and less accurate. This paper studies a better way to find potholes by using the latest digital image processing techniques. These techniques are designed to find and check road surface problems automatically. Using Digital image processing is a smart and effective way to find potholes using a mix of computer vision and machine learning techniques. The system has a few important parts: it takes pictures using cameras mounted on vehicles, cleans up the pictures to make them clearer, and then looks for potential potholes based on certain features. The results and accuracy reported are highly promising.