Dermoscopic image enhancement and hair artifact removal using Gabor wavelet

Skin cancer is one of the most prevalent types of cancer in our world. Diagnosis of skin cancer needs specialized equipment, doctors and continuous monitoring. Patients living in remote areas normally cannot access such facilities. To overcome these barriers of access, Computer Aided Diagnostics, an emerging field in computer science, often called telemedicine, is being considered a promising approach. Image processing for Computer Aided Diagnostics has three key steps, i.e. Segmentation, Feature Extraction and Classification. In this research, preprocessing and hair artifact removal experiment was performed on dermatoscope images by using Morphological and Gabor wavelet-based techniques. It has been found that, in some cases, wavelet transformations provide better results as compared to other techniques like gel, water bubbles and dark hair around the surface affected by cancer, i.e. these artifacts are removed with less effort. Experiments also showed that images with Blue channel from RGB are better as compared to other grayscale conversion techniques.