  Melanoma spreads through metastasis, and therefore it has been proven to be
very fatal. Statistical evidence has revealed that the majority of deaths
resulting from skin cancer are as a result of melanoma. Further investigations
have shown that the survival rates in patients depend on the stage of the
infection; early detection and intervention of melanoma implicates higher
chances of cure. Clinical diagnosis and prognosis of melanoma is challenging
since the processes are prone to misdiagnosis and inaccuracies due to doctors
subjectivity. This paper proposes an innovative and fully functional
smart-phone based application to assist in melanoma early detection and
prevention. The application has two major components; the first component is a
real-time alert to help users prevent skin burn caused by sunlight; a novel
equation to compute the time for skin to burn is thereby introduced. The second
component is an automated image analysis module which contains image
acquisition, hair detection and exclusion, lesion segmentation, feature
extraction, and classification. The proposed system exploits PH2 Dermoscopy
image database from Pedro Hispano Hospital for development and testing
purposes. The image database contains a total of 200 dermoscopy images of
lesions, including normal, atypical, and melanoma cases. The experimental
results show that the proposed system is efficient, achieving classification of
the normal, atypical and melanoma images with accuracy of 96.3%, 95.7% and
97.5%, respectively.
