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World Conference on Information Systems and Technologies

WorldCIST'18 2018: Trends and Advances in Information Systems and Technologies pp 820–830Cite as

Computer Aided Wound Area Detection System for Dermatological Images

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 746))

Abstract

Research shows that in the last decade, the focus on computer-assisted diagnoses on the skin disorders has increased significantly as a result of the improvements in skin imaging technology and the development of compatible image processing techniques. More accurate treatments provided by means of computer-assisted diagnostic systems increase the patients’ chances of recovery and survival. Image processing techniques used in these systems facilitate the detection of wound areas. In this study, a wound detection system using adaptive weighted median filter (AWMF), Otsu’s thresholding, and an implementation of the Canny edge detection algorithm using the Sobel kernel, respectively, is proposed for the detection of wound areas on dermatological images. The effectiveness of the system is tested on different dermatological datasets. Obtained values are analyzed with Peak Signal to Nose Ratio (PSNR) and Correlation Coefficient (CC) metrics and it was confirmed that the system works accurately on various datasets.

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Authors and Affiliations

  1. Department of Computer Engineering, Kocaeli University, 41380, Umuttepe, Kocaeli, Turkey

    Sümeyya İlkin, Fidan Kaya Gülağız, Fatma Selin Hangişi & Suhap Şahin

Authors
  1. Sümeyya İlkin
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  2. Fidan Kaya Gülağız
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  3. Fatma Selin Hangişi
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  4. Suhap Şahin
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Corresponding author

Correspondence to Fidan Kaya Gülağız .

Editor information

Editors and Affiliations

  1. Departamento de Engenharia Informática, Universidade de Coimbra, Coimbra, Portugal

    Álvaro Rocha

  2. College of Engineering, The Ohio State University, Columbus, Ohio, USA

    Hojjat Adeli

  3. DSI/EEUM, Universidade do Minho, Guimarães, Portugal

    Luís Paulo Reis

  4. DIMES, Universita della Calabria, Arcavacata di Rende, Italy

    Sandra Costanzo

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İlkin, S., Gülağız, F.K., Hangişi, F.S., Şahin, S. (2018). Computer Aided Wound Area Detection System for Dermatological Images. In: Rocha, Á., Adeli, H., Reis, L., Costanzo, S. (eds) Trends and Advances in Information Systems and Technologies. WorldCIST'18 2018. Advances in Intelligent Systems and Computing, vol 746. Springer, Cham. https://doi.org/10.1007/978-3-319-77712-2_77

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  • DOI: https://doi.org/10.1007/978-3-319-77712-2_77

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-77711-5

  • Online ISBN: 978-3-319-77712-2

  • eBook Packages: EngineeringEngineering (R0)

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