Abstract
Abstract: This paper presents algorithms for pothole detection on roads. We have collected a vast dataset from various sources and organized it into a structured format. Data preprocessing techniques were applied to reduce algorithm time and space complexity. The refined dataset was used for training, leading to the development of different models using color segmentation. The results obtained from these models demonstrated an impressive accuracy of 91% using color segmentation. The creation of this pothole detection system can significantly enhance safety for both you and others. Moreover, it has the potential to be widely integrated into Google Maps by extracting coordinates from Geographical Information System (GIS) data and incorporating them into the platform.
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