  In this paper, a novel method for edge detection of microcalcification
clusters in mammogram images is presented using the concept of Fractal
Dimension and Hurst co-efficient that enables to locate the microcalcifications
in the mammograms. This technique detects the edges accurately than the ones
obtained by the conventional Sobel method. Generally, Sobel method detects the
edges of the regions/objects in an image using the Fudge factor that assumes
its value as 0.5, by default. In this proposed technique, the Fudge factor is
suitably replaced with Hurst Co-efficient, which is computed as the difference
of Fractal dimension and the topological dimension of a given input image.
These two dimensions are image-dependent, and hence the respective Hurst
co-efficient too varies with respect to images. Hence, the image-dependent
Hurst co-efficient based Sobel method is proved to produce better results than
the Fudge factor based Sobel method. The results of the proposed method
substantiate the merit of the proposed technique.
