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Gingivitis Detection by Wavelet Energy Entropy and Linear Regression Classifier

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Book cover Intelligent Computing Theories and Application (ICIC 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12838))

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Abstract

Gingivitis is a high-risk disease among middle-aged and elderly people, which greatly increases the difficulty of eating. People are increasingly concerned about the subhealth of gingivitis in order to solve the daily eating problems associated with gingivitis. In the field of medical image analysis, the process of studying gingivitis detection is more challenging because of the lack and difficulty of dental image analysis. The two key points of gingivitis image detection are the extraction of major features from gingival images and the accurate classification of different features. In this paper, a gingivitis detection method based on wavelet energy entropy is proposed. The energy of the wavelet spectrum of gingival image is calculated by using the information entropy, and a new wavelet energy entropy of image feature representation is obtained. The entropy is used to segment gingival image by linear regression classifier. The segmented gingival image sieves out redundant information, preserves key feature areas, and reduces the time required for classification. This improves diagnostic time consumption and helps dentists improve the efficiency of gingivitis diagnosis.

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Author information

Authors and Affiliations

  1. School of Informatics, The University of Leicester, University Road, Leicester, LE1 7RH, UK

    Yan Yan

  2. Educational Information Center, Liming Vocational University, Quanzhou, 362000, Fujian, China

    Yan Yan

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  1. Yan Yan
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Editor information

Editors and Affiliations

  1. Tongji University, Shanghai, China

    De-Shuang Huang

  2. University of Ulsan, Ulsan, Korea (Republic of)

    Kang-Hyun Jo

  3. Shenzhen University, Shenzhen, China

    Jianqiang Li

  4. Far Eastern Branch of the Russian Academy of Sciences, Vladivostok, Russia

    Valeriya Gribova

  5. University of Wollongong, North Wollongong, NSW, Australia

    Prashan Premaratne

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Yan, Y. (2021). Gingivitis Detection by Wavelet Energy Entropy and Linear Regression Classifier. In: Huang, DS., Jo, KH., Li, J., Gribova, V., Premaratne, P. (eds) Intelligent Computing Theories and Application. ICIC 2021. Lecture Notes in Computer Science(), vol 12838. Springer, Cham. https://doi.org/10.1007/978-3-030-84532-2_17

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  • DOI: https://doi.org/10.1007/978-3-030-84532-2_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-84531-5

  • Online ISBN: 978-3-030-84532-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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