Investigating Skin Cancer Diagnosis Using a Webcam-based Microcontroller System

Abstract

Skin cancer can spread fast to nearby tissue and other parts of the human body if it's not diagnosed early. Most are curable only if skin cancer is found and treated in the early stages. Therefore, it's essential to seek a casual way of early diagnosis. This paper assesses a prototype system for skin cancer detection using an Arduino with an ArduCam Mega 5MP, benchmarked against smartphone diagnosis. Bandpass filters capture skin images at red (650 nm), green (532 nm), and blue (450 nm) wavelengths, measuring reflectance values. The approach aims to quantitatively determine skin melanin, oxyhemoglobin, and deoxyhemoglobin levels, aiding in various skin lesions' diagnosis. Evaluation involves comparing pixel reflectance values of images taken by smartphones and the prototype using a 3D mesh grid. Applying the modified Lambert-Beer law to reflectance values of moles, pimples, scars, scabs, and traces predicts relative levels of skin components. The system shows an 87% match with the smartphone standard, demonstrating high reliability. Further study might be needed to clarify the confirmation with clinical cases.