Blackledge, J. M.Dubovitskiy, D. A.Wen Tang and John Collomosse2014-01-312014-01-312009978-3-905673-71-5https://doi.org/10.2312/LocalChapterEvents/TPCG/TPCG09/041-048We 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.Categories and Subject Descriptors (according to ACM CCS): F.2.2; I.5.4 [Analysis of Algorithms and problem complexity, Pattern Recognition]: Pattern matching, Computer vision