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Diagnosis of Dermoscopy Images for the Detection of Skin Lesions Using SVM and KNN

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Proceedings of Third International Conference on Sustainable Computing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1404))

Abstract

Early detection of skin lesions is essential for effective healing. In recent times, melanoma is one of the most dangerous types of skin cancer because it spreads to other parts of the body if there is no early diagnosis and treatment. Artificial intelligence algorithms play an important role in medical image diagnostics. These techniques provide an effective tool for the analysis and diagnosis of lesions. In this study, the steps include the diagnosis of Dermoscopy images from the PH2 database. Preprocessing process for image enhancement use a Gaussian filter to enhance the input images. Segmentation of the lesion area and separation from the healthy body using active contour technique (ACT). The gray level co-occurrence matrix (GLCM) algorithm was applied to extract features from the region of interest. The lesions were classified using the support vector machine (SVM) and K nearest neighbors (KNN) classifiers. The results achieved by using SVM were accuracy 99.10%, sensitivity 100% and specificity 98.54%.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Information Technology, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, India

    Ebrahim Mohammed Senan

  2. Shri Shivaji Science and Arts College, Chikhli, Buldana, India

    Mukti E. Jadhav

Authors
  1. Ebrahim Mohammed Senan
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  2. Mukti E. Jadhav
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Editor information

Editors and Affiliations

  1. Department of Computer Science, CHRIST (Deemed to be University), Bengalore, Karnataka, India

    Ramesh Chandra Poonia

  2. Department of Computer Science and Engineering, Manipal University, Jaipur, Rajasthan, India

    Vijander Singh

  3. Faculty of Computing and Informatics, Namibia University of Science and Technology, Windhoek, Namibia

    Dharm Singh Jat

  4. Data Science Research Group, National University of La Pampa, Santa Rosa, Argentina

    Mario José Diván

  5. Department of Computing, East Tennessee State University, Johnson City, TN, USA

    Mohammed S. Khan

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Senan, E.M., Jadhav, M.E. (2022). Diagnosis of Dermoscopy Images for the Detection of Skin Lesions Using SVM and KNN. In: Poonia, R.C., Singh, V., Singh Jat, D., Diván, M.J., Khan, M.S. (eds) Proceedings of Third International Conference on Sustainable Computing. Advances in Intelligent Systems and Computing, vol 1404. Springer, Singapore. https://doi.org/10.1007/978-981-16-4538-9_13

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