A Comparative Analysis on Image Enhancement and Filtering Techniques for Efficient Melanoma Skin Cancer Detection
Skin cancers are becoming more prevalent worldwide due to the shortage of awareness on the symptoms and skin safety measures. The use of computer-aided diagnosis systems for melanoma detection can aid the doctors and technicians. Pre-processing an image plays a crucial role in separating the lesion from the skin and identifying the region of interest (ROI). As a result, in this proposed study of work, a thorough analysis is done on various image enhancement and filtering techniques. Most prominent image enhancing and filtering techniques are reviewed with a detailed result analysis. The analysis demonstrates that by eliminating the undesirable hair particles from the skin lesion, the dull razor algorithm for image improvement works effectively. Then, gaussian image smoothing works well for noise filtering. According to the findings summarised in this research work, the two strategies stated above performed the best, with a 96.25% accuracy rate.