Texture Classification using Fractal Geometry for the Diagnosis of Skin Cancers

Abstract

We present an approach to object detection and recognition in a digital image using a classification method that is based on the application of a set of features that include fractal parameters such as the Lacunarity and Fractal Dimension. The principal issues associated with object recognition are presented and a self-learning procedure for designing a decision making engine using fuzzy logic and membership function theory considered. The methods discussed, and the 'system' developed, have a range of applications in 'machine vision' and in this publication, we focus on the development and implementation of a skin cancer screening system that can be used in a general practice by non-experts to 'filter' normal from abnormal cases so that in the latter case, a patient can be referred to a specialist. The paper provides an overview of the system design and includes a link from which interested readers can download and use a demonstration version of the system developed to date.