An Automatic Classification of Dermoscopy Image with Multilayer Perceptron using Weka
PN Angel1, K. Sudhai2
1Dr. N. Angel*, Department of CSE, St. Joseph’s College of Engineering, Chennai, India.
2K. Sudha, Department of CSE, St. Joseph’s College of Engineering, Chennai, India.:
Manuscript received on September 16, 2019. | Revised Manuscript received on 24 September, 2019. | Manuscript published on October 10, 2019. | PP: 2697-2702 | Volume-8 Issue-12, October 2019. | Retrieval Number: A3912119119/2019©BEIESP | DOI: 10.35940/ijitee.L2539.1081219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Skin cancer a distressing disease (or) an abnormality. The growth starts from the human body’s epidermis. Skin cancer treatments depend primarily upon the sign and location of the tumour. Computerized image analysis influences the accurate assessment of skin cancer in an effective manner. Skin cancer affects people in various parts of the body. A computer method on the pigment skin image should be examined to diagnose the skin cancer precisely. This is the dermatologist’s pre-screening system for early diagnosis. The associated and the proposed work is compared and examined. The proposed work gives the report on the classification of lesions from the dermoscopy images with basic steps such as pre-processing and classification. Here GLCM and Multilayer Perceptron analysis is used to differentiate the features. The simulation measures the accurate diagnosis of the image of ground truth and the segmented image and confirms the accuracy values up to 98% for Classification.
Keywords: Weka, Disceretize, Multilayer Perceptron, GLCM, Training.
Scope of the Article: Classification