Determining Roads Asphalt Damage with Image Processing Algorithms in MATLAB

In recent years, a new application making image processing so significant is the use of image processing techniques (IPTs) in urban planning and road construction to facilitate work and enhance the rate of detecting asphalt damage on road surfaces using the identification of these damages and bettering them prior to further damage to these important communication infrastructures. The paper tried to reduce the existing challenges by properly training of the software and assigning tasks to the machine automatically on the one hand, and on the other tried to extract better answers from machines compared to humans by reducing human interference in identifying and determining the extent of road surface damage using extraction of various features by IPTs and proper analysis in MATLAB software. Regarding this, firstly, 824 images were taken from various places with different conditions (sunny, cloudy, shady, and so on) using a high quality camera. Then the images received in the previous step were stored in a database and the color images were converted to binary (black and white) ones. Then, after edge detection, mean filter was done with Sobel default and the images were divided into some sub-blocks, and the features were examined after applying k-means algorithm. Finally, 199 features of each image were examined and the final pattern was obtained after training the software. The results indicated that the accuracy of the output in terms of percentage was more than 85%, which based on the previous studıes, shows acceptable detection by the method presented in this study. The accuracy of the method presented in the classification output was much higher than the percentage output and in almost more than 95% of cases were placed in the correct class that the experts have identified, showing the high accuracy of the proposed method in the method in classification.