A comparative study of features selection for skin lesion detection from dermoscopic images

Melanoma is rare and mainly considered as the dangerous category of skin cancer. Many researchers proposed diverse efficient techniques for melanoma detection. The main focus of this research is: (1) to discuss the traditional clinical methods for diagnosing skin cancer melanoma, and (2) to review the existing researcher's attempts in response the critical and challenging task is features selection and extraction for skin cancer melanoma detection from dermoscopy images. This research will also be helpful to recognize the research background of skin cancer melanoma detection through image processing techniques. This cannot be done without a broad literature survey. The literature survey was performed keeping the main category as skin cancer melanoma and the survey included articles, journals, and conferences papers. To perform this study, different databases are considered. All of these databases cover medical image processing and technical literature. To conclude the review, some graphs and tables are presented which perform the comparison between existing techniques.