Document Type
Conference Paper
Rights
Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence
Disciplines
Applied mathematics, Optics, Dermatology and venereal diseases, Oncology
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.
Recommended Citation
Blackledge, Jonathan and Dubovitskiy, Dymitiy A., "Texture Classification using Fractal Geometry for the Diagnosis of Skin Cancers" (2009). Conference papers. 159.
https://arrow.tudublin.ie/engscheleart/159
Publication Details
EG UK Theory and Practice of Computer Graphics, pages: 1-8, Cardiff University, 2009