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Author: Hansoo Kim

Affiliation: Department of Information Security, Seowon University, 377-3, Mushimseoro, Seowongu, Cheongjusi, Choongbuk and Korea

ISBN: 978-989-758-378-0

Keyword(s): Skin Diagnosis, Lesion Recognition, Image Processing, Contactless Skin Diagnosis Device.

Related Ontology Subjects/Areas/Topics: Biomedical Applications ; Biometrics and Pattern Recognition ; Image and Video Processing, Compression and Segmentation ; Multimedia ; Multimedia Signal Processing ; Multimedia Systems and Applications ; Semantic Analysis of Multimedia Data ; Telecommunications

Abstract: An image analysis procedure for recognizing various skin lesions under contactless skin diagnosis environment is proposed. The proposed procedure is composed of five stages, and experimental results show that issues such as uneven distribution of light are properly addressed, and various skin lesions are effectively discriminated according to their characteristics using the image processing technology and the shadow analysis.

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Paper citation in several formats:
Kim, H. (2019). Effective Image Processing Procedure for Skin Lesion Recognition in Contactless Skin Diagnosis Devices.In Proceedings of the 16th International Joint Conference on e-Business and Telecommunications - Volume 1: SIGMAP, ISBN 978-989-758-378-0, pages 337-342. DOI: 10.5220/0007948403370342

@conference{sigmap19,
author={Hansoo Kim.},
title={Effective Image Processing Procedure for Skin Lesion Recognition in Contactless Skin Diagnosis Devices},
booktitle={Proceedings of the 16th International Joint Conference on e-Business and Telecommunications - Volume 1: SIGMAP,},
year={2019},
pages={337-342},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007948403370342},
isbn={978-989-758-378-0},
}

TY - CONF

JO - Proceedings of the 16th International Joint Conference on e-Business and Telecommunications - Volume 1: SIGMAP,
TI - Effective Image Processing Procedure for Skin Lesion Recognition in Contactless Skin Diagnosis Devices
SN - 978-989-758-378-0
AU - Kim, H.
PY - 2019
SP - 337
EP - 342
DO - 10.5220/0007948403370342

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