Diagnosis of skin cancer using machine learning techniques |
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| Affiliation: | 1. Department of Computer and Information Sciences, Annamalai University, Chidambaram, India;2. Department of CSE, Annamalai University, Chidambaram, India (Deputed to WPT Chennai);3. Department of ECE, Karpagam college of Engineering, Anna University, India;4. PG Department of Computer Science, R. V. Government Arts College, Chengalpattu, India;1. People''s Hospital of Fangzi District, Weifang, Shandong, 261200, China;2. No.1 Bone Surgery Ward, Jinan No.4 People''s Hospital, Jinan, Shandong, 250031, China;3. Department of Arthritis, Affiliated Hospital of Weifang Medical College, Weifang, Shandong, 261031, China;4. The Orthopaedic Trauma, People''s Hospital of Fangzi District, Weifang, Shandong, 261200, China;1. Department of Computer Science & Information Technology, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, India;2. Shri Shivaji Science & arts College, Chikhli Dist. Buldana., India |
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| Abstract: | Generally, skin disease is a common one in human diseases. In computer vision application, the skin color is the powerful indication for this disease. This system identifies the skin cancer disease based on the images of skin. Initially, the skin is filtered using median filter and segmented using Mean shift segmentation. Segmented images are fed as input to feature extraction. GLCM, Moment Invariants and GLRLM features are extracted in this research work. The extracted features are classified by using classification techniques like Support vector machine, Probabilistic Neural Networks and Random forest and Combined SVM+ RF classifiers. Here combined SVM+RF classifier provided better results than other classifiers. |
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