IMPROVED FRACTAL GEOMETRY BASED TEXTURE SEGMENTATION TECHNIQUE

The problem of natural texture segmentation is considered. The techniq ue is based on four texture features derived using the fractal geometr y of images. These four features are fractal dimension (FD) of the ori ginal image, FD of above average (high) gray level image, FD of below (low) gray level image, and multifractal of order two. A modified box- counting approach is proposed to estimate the FD and computed features all are normalised in the same range [0, 1]. A feature domain smoothi ng is activated to reduce the spurious segmentation. Next, a nonsuperv ised clustering approach is used to segment a scene into the desired n umber of classes. Some supervised techniques like minimum distance cla ssifier and k-nearest neighbour classifier are also considered. Mosaic s of various natural textures are generated and the segmentation resul ts are presented to show the efficiency of the technique.