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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15

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Volume 9 | Issue 4

Impact factor: 8.15

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Paper Title: Skin Lession Classification Using Image Processing
Authors Name: Mr Sachin Mahadeo Bagade , Dr A M Patil , Prof O K Firke , Dr P M Mahajan
Unique Id: IJSDR2303064
Published In: Volume 8 Issue 3, March-2023
Abstract: Melanoma is a type of skin cancer with a high mortality rate. The different types of skin lesions result in an inaccurate diagnosis due to their high similarity. Accurate classification of the skin lesions in their early stages enables dermatologists to treat the patients and save their lives. This paper proposes a model for a highly accurate classification of skin lesions. The proposed model utilized the GLCM and Gabor features. Performance of SVM, KNN and Naïve Bayes Classifiers is evaluated. The latest well-known public challenge dataset, ISIC 2019, is used to test the ability of the proposed model to classify different kinds of skin lesions. The proposed model successfully classified the nine different classes of skin lesions, namely, melanoma, melanocytic nevus, basal cell carcinoma, actinic keratosis, benign keratosis, dermatofibroma, vascular lesion, and Squamous cell carcinoma. The achieved classification accuracy, using KNN and Gabor features are 96.07. The proposed model can detect images that do not belong to any one of the nine classes where these images are classified as unknown images.
Keywords: skin disease, gabor, knn
Cite Article: "Skin Lession Classification Using Image Processing", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 3, page no.412 - 417, March-2023, Available :http://www.ijsdr.org/papers/IJSDR2303064.pdf
Downloads: 000337070
Publication Details: Published Paper ID: IJSDR2303064
Registration ID:204420
Published In: Volume 8 Issue 3, March-2023
DOI (Digital Object Identifier):
Page No: 412 - 417
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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