Potholes Asphalt Road Classification by Shape and Area Feature

Abstract

Background of the study: Generally, during the rainy season, many potholes asphalt road are found. The high rainfall results in the fragile contour of the asphalt road and triggers a traffic accident. In the last decade, the development of potholes asphalt road detection has various method approaches. Purpose: The research used precision to get a performance of the system. Method: In this study, the development system can classify potholes asphalt road by a simple algorithm. It also considers the time and space complexity. Findings: The algorithms as possible and only uses the handy-camera device to capture data which the level of performance as good as the results of previous research. Capturing data is also various distances with 450 point angles. For classification steps, the system applied two main features, area and shape feature of the object. The used parameters for these features are the length of major and minor axis object. It used to calculate area and eccentricity values. Conclusion: In conclusion, the experiment result reaches 81.696% of the 1125 frames used.