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The Application of Mobile Devices for the Recognition of Malignant Melanoma

Robotic systems and autonomous decision making systems are increasingly becoming a significant part of our everyday routines. Object recognition is an area of computer science in which automated algorithms work behind a graphical user interface or similar vehicle for interaction with users or some other feature of the external world. From a user perspective this interaction with the underlying algorithm may not be immediately apparent. This paper presents an outline of a particular form of image interpretation via mobile devices as a method of skin cancer screening. The use of mobile hardware resources is intrinsically interconnected with the decision making engine built into the processing system. The challenging fundamental problem of computational geometry is in offering a software hardware solution for image recognition in a complex environment where not all aspects of that environment can fully be captured for use within the algorithm. The unique combination of hardware software interaction described in this paper brings image processing within such an environment to the point where accurate and stable operation is possible, offering a higher level of flexibility and automation. The Fuzzy logic classification method makes use of a set of features which include fractal parameters derived from generally understood Fractal Theory. The automated learning system is helping to develop the system into one capable of near-autonomous operation. The methods discussed potentially have a wide range of applications in ‘machine vision’. However, in this publication, we focus on the development and implementation of a skin cancer screening system that can be used by nonexperts so that in cases where cancer is suspected a patient can immediately be referred to an appropriate