Texture Classification using Fractal Geometry for the Diagnosis of Skin Cancers
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Date
2009
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
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.
Description
@inproceedings{:10.2312/LocalChapterEvents/TPCG/TPCG09/041-048,
booktitle = {Theory and Practice of Computer Graphics},
editor = {Wen Tang and John Collomosse},
title = {{Texture Classification using Fractal Geometry for the Diagnosis of Skin Cancers}},
author = {Blackledge, J. M. and Dubovitskiy, D. A.},
year = {2009},
publisher = {The Eurographics Association},
ISBN = {978-3-905673-71-5},
DOI = {/10.2312/LocalChapterEvents/TPCG/TPCG09/041-048}
}