Melanoma classification using texture and wavelet analysis

Akhiyar Waladi, Nanda Maulina Firdaus, Aniati Murni Arymurthy

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Melanoma is the deadliest skin cancer that develops in melanocytes cell that produces melanin. This cancer is caused by ultraviolet light (UV) radiation. We use wavelet method (Discrete Wavelet Packet Transform (DWPT)) and texture feature extraction (Gray-Level Co-occurrence Matrix (GLCM), and Local Binary Pattern (LBP)) as feature extraction in this study to classify melanoma cancer. We divided this research into 4 phases. First, we used hair removal data and hair removal data with augmentation for 3 classes. Second, we used combination data with and without hair removal for three classes. Third, we used hair removal data and hair removal data with augmentation for 2 classes, and the last we used combination data with and without hair removal for two classes. The classification results of 2 classes (Melanoma and Non-Melanoma) were better than the results of the classification of 3 classes (Atypical Nevus, Common Nevus, and Melanoma). The system cannot distinguish between Atypical Nevus and Common Nevus, that's why the classification results of 2 classes were better than three classes. These two classes have characteristics that are almost similar to color and texture. When these two classes are combined, the classification results are better because the classes Nevus and Melanoma, have quite clear differences in terms of color and texture.

Original languageEnglish
Title of host publicationProceeding - 2019 International Conference of Artificial Intelligence and Information Technology, ICAIIT 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages336-343
Number of pages8
ISBN (Electronic)9781538684481
DOIs
Publication statusPublished - 1 Mar 2019
Event1st International Conference of Artificial Intelligence and Information Technology, ICAIIT 2019 - Yogyakarta, Indonesia
Duration: 13 Mar 201915 Mar 2019

Publication series

NameProceeding - 2019 International Conference of Artificial Intelligence and Information Technology, ICAIIT 2019

Conference

Conference1st International Conference of Artificial Intelligence and Information Technology, ICAIIT 2019
Country/TerritoryIndonesia
CityYogyakarta
Period13/03/1915/03/19

Keywords

  • augmentation
  • hair removal
  • Melanoma
  • texture
  • wavelet

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