A box-counting approach to color segmentation

Many texture classification schemes require an excessively large image area for texture analysis, use a large number of features to represent each texture or are computationally very demanding. In this paper we describe a segmentation method using color and fractal dimension for real time texture classification. The box-counting approach is used to estimate the fractal dimension (FD). A seed block which embodies information about color features and FD is used by a region growing method. Experimental results indicate that the proposed method is promising for color texture segmentation. This scheme is computationally very efficient and it is suited for texture image recognition