A neural network approach to mammogram image classification using fractal features

This paper presents a novel method based on fractal features for the classification of mammogram images. For recognition of regions and objects in the natural scenes, there is always a need for features, which are invariant, and they provide a good set of descriptive values for the region. There are numerous methods available to estimate parameters from the images of the fractal surface. In this paper we perform mammogram image classification based on fractal dimension and fractal signature. The result has shown the potential usefulness of the fractal features for image analysis. A trainable multilayer feed forward neural network has been designed for the classification of images. Experimental results shown that the proposed system can well perform a classification rate of 98%.