Pavement distress detection and classification with automated image processing

Nowadays, pavement distresses classification becomes more important as the computational power increases. In this article, an enhancement algorithm is initially introduced to remove uneven illumination within the pavement images. This proposed method which uses a multiplicative factor to correct the background illumination, after that use shearlet frame to filtering the pavement images. In the classification of operation, we used Radon transform for line and angle detection about pavement distress of binary images, and use scattering distance to verify the result of classification by the texture feature of pavement distress images. Experimental results demonstrate that the proposed system is an effective method for pavement distress classification. The test performances of this study show the advantages of proposed system:have simple calculation, and have High precision.