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A Review of Biometrics Modalities and Data Mining Algorithms

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Ambient Communications and Computer Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 696))

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Abstract

In order to generate meaningful information from the large datasets, mining algorithms have been used. Mining algorithms are used to abstract the unknown pattern from the immense database. The medical domain contains large databases, so to extract the information about the particular disease, mining algorithms can be applied on it. The human diseases can be predicted using predictive data mining algorithms. According to the recent trends data mining algorithms has been applied on biometric modalities like face, iris and tongue to predict the human age and gender. To archive better accuracy, fusion can be performed on biometric traits. The fusion uses the concept of the multimodal system. This paper is the review of different predictive mining algorithm, biometric traits, multimodal system, and the performance parameters of the predictive systems and biometric systems.

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Author information

Authors and Affiliations

  1. MPSTME, Mumbai, India

    Avani Shah & Dhirendra Mishra

Authors
  1. Avani Shah
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  2. Dhirendra Mishra
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Corresponding author

Correspondence to Dhirendra Mishra .

Editor information

Editors and Affiliations

  1. University of Murcia, Murcia, Spain

    Gregorio Martinez Perez

  2. Department of Computer Science and Engineering, ABES Engineering College, Ghaziabad, Uttar Pradesh, India

    Shailesh Tiwari

  3. Department of Computer Science and Engineering, ABES Engineering College, Ghaziabad, Uttar Pradesh, India

    Munesh C. Trivedi

  4. Department of Computer Science and Engineering, Motilal Nehru National Institute of Technology, Allahabad, Uttar Pradesh, India

    Krishn K. Mishra

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Shah, A., Mishra, D. (2018). A Review of Biometrics Modalities and Data Mining Algorithms. In: Perez, G., Tiwari, S., Trivedi, M., Mishra, K. (eds) Ambient Communications and Computer Systems. Advances in Intelligent Systems and Computing, vol 696. Springer, Singapore. https://doi.org/10.1007/978-981-10-7386-1_51

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  • DOI: https://doi.org/10.1007/978-981-10-7386-1_51

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-7385-4

  • Online ISBN: 978-981-10-7386-1

  • eBook Packages: EngineeringEngineering (R0)

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