• Jan 04, 2024 News!IJFCC will adopt Article-by-Article Work Flow
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General Information
    • ISSN: 2010-3751 (Print)
    • Frequency: Quarterly
    • DOI: 10.18178/IJFCC
    • Editor-in-Chief: Prof. Pascal Lorenz
    • Executive Editor: Ms. Yoyo Y. Zhou
    • Abstracting/ Indexing: Crossref, Electronic Journals LibraryINSPEC(IET), Google Scholar, EBSCO, etc.
    • E-mail:  ijfcc@ejournal.net 
    • Article Processing Charge: 500 USD

Prof. Pascal Lorenz
University of Haute Alsace, France
It is my honor to be the editor-in-chief of IJFCC. The journal publishes good papers in the field of future computer and communication. Hopefully, IJFCC will become a recognized journal among the readers in the filed of future computer and communication.

IJFCC 2019 Vol.8(4): 114-118 ISSN: 2010-3751
DOI: 10.18178/ijfcc.2019.8.4.551

Classification of Melanoma Considering the Adaptive Additional Shape Feature

K. Chaiyakhan, P. Chujai, R. Chanklan, and N. Kerdprasop

Abstract—Skin cancer is the rapid growth of abnormal skin tissues. There are several types of skin cancer, and the deadliest being melanoma. The most important warning sign for melanoma is a lesion on the skin that keeps on developing in shape, color or size. Melanoma must be detected in the initial stage, for early medical treatment. In this research, we propose and approach to automatically classify melanoma. Otsu method was used to get the lesion region. A feature that is usually used in melanoma classification in visual checking was use. The additional feature that we also use is adaptive additional shape feature (ADPS) to specific changing of curve. In classification process we use deep neural networks for skin lesions classification. We also compare deep neural networks with support vector machine. The experimental results of classification demonstrated that ADPS with other features using deep neural network as classifier provided good classification in evaluation process.

Index Terms—Image segmentation, feature extraction, melanoma detection, skin cancer.

K. Chaiyakhan is with the Computer Engineering Department, Rajamangala University of Technology Isan, Muang, Nakhon Ratchasima, Thailand (e-mail: kedkarnc@hotmail.com).
P. Chujai is with the Electrical Technology Education Department, Faculty of Industrial Education and Technology, King Mongkut’s University of Technology Thonburi, Bangkok, Thailand (e-mail: pasapitchchujai@gmail.com).
R. Chanklan and N. Kerdprasop are with the School of Computer Engineering, Suranaree University of Technology, Nakhon Ratchasima, Thailand (e-mail: arc_angle@hotmail.com, nittaya.k@gmail.com).


Cite: K. Chaiyakhan, P. Chujai, R. Chanklan, and N. Kerdprasop, "Classification of Melanoma Considering the Adaptive Additional Shape Feature," International Journal of Future Computer and Communication vol. 8, no. 4, pp. 114-118, 2019.

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