Detection, Classification, Evaluation and Compression of Pavement Information using GUI

This paper presents crack detection and evolution algorithm which describes the procedure for pavement image. The entire project is built using wavelet transform and radon transform. The application of wavelets to images gives different frequency sub-bands. And, this algorithm is based on the fact that crack pixels are darker than their surroundings. The crack detection algorithm deteriorate a pavement image into four sub-bands one low frequency sub-band called approximation and three high frequency sub-bands called detail. Cracks are clearly appear in the low frequency sub band at the first level by extended pseudo color matrix scaling. The algorithm of classification first revises and re-computes the vertical, horizontal and diagonal details at the first level using the energy conservation function, and then forms a new image by adding corresponding points in the four new sub-bands; finally it uses Radon transform to this new image. This Radon transform is used for classification and evolution of pavement image with new interface named GUI.