Fractal features analysis and classification for texture of pavement surfaces

Presents a method for texture analysis of pavement surfaces. Normalized fractal Brownian motion model is applied to describe the pavement surfaces. The Normalized fractal Brownian motion vectors(NFBV) are taken to be fractal features for the classification. The image of pavement surfaces is divided into nonoverlapping pixel blocks, and the attribute vectors are obtained by computing the NFBV of each pixel block. By using k-means clustering classifier, the experimental results of classification among pixel blocks of healthy pavement and distress pavement show the method is efficient.