Pavement segregation detection using support vector machine

Segregation is a phenomenon of separating small and large fractions in a mixture, resulting in the presence of coarse aggregate and fine aggregate in an uneven mixture. As a result of the non-uniform distribution, the possibility of potholes, raveling, and cracks in the asphalt of the highway is very likely to occur. Therefore, we need to be able to take preventive measures as a form of minimizing the possibility of this phenomenon occurring. Segregation in asphalt is generally detected through manual visual inspection. However, using the assessment method obtained will tend to choose and take a long time. Thus, this research was conducted to provide a new solution to detect segregation areas in a more credible, faster, and economical way. This solution utilizes digital image processing methods that are still rarely used. In the process, this method will be implemented together with the Support Vector Machine method. Then, the variable that will be used as the main focus is the standard deviation. In this study, we will test the classification of segregated and non-segregated areas on the asphalt road environment at the University of Indonesia.