Texture analysis and segmentation of images using fractals

Many objects in images of natural scenes are so complex that describing them by traditional techniques is inadequate. This paper presents a family of techniques suitable for texture analysis and segmentation of objects in aerial images. Texture has been one of the most important but difficult properties for image coding and compression. It is important because it describes the entire area of a region and provides the essential structure information in regions of an image. Our goal here is to decompose an image to texturally homogenous regions. An efficient technique for computing the fractal dimension of images is used. Three different techniques; the Hurst transform, the Sobel operator and the variance are applied to two images and the results are compared. It is shown that variance dimension converts the original image to one whose texture information permits simple thresholding for texture analysis and segmentation.