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Classification in BioApps pp 407–447Cite as

A Bio-application for Accident Victim Identification Using Biometrics

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Part of the book series: Lecture Notes in Computational Vision and Biomechanics ((LNCVB,volume 26))

Abstract

A unique way to identify victims is an essential requirement for maintaining health records in hospital information systems. Although significant steps have been made in medical innovation and enhanced technologies, there are still major concerns regarding identifying a victim and their blood group in the event of an emergency. Information and Communication Technology (ICT) can help in identifying the location of an accident through a global positioning system (GPS) and can send a request for the emergency need for a required blood group. This chapter presents an application and proposes a novel approach to victim identification based on an autoencoder and extreme learning machine (ELM) techniques that can enhance accuracy. An autoencoder is employed to images of a victim’s fingerprint to emphasize the spatial gradients of the edges on the finger. Application of autoencoder not only denoises the input data, but also minimizes the dimensionality of the data. An ELM is applied to a preprocessed image to extract the unique features for victim identification. An effective optimal cost region matcher (OCRM) with deep learning techniques is applied to enhance the accuracy of victim recognition. This application enables “the man in the street” to inform the family members of a victim to be informed of their status. Further, the system detects and deals with blood group aids in mitigating risk in initial treatment.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Stanley Women’s Engineering College, Hyderabad, India

    P. Vidyasree

  2. Department of IT, JNTUK, UCEV, Vizianagaram, India

    Gudavalli Madhavi

  3. Department of CSE, JNTUH CEJ, Hyderabad, India

    S. Viswanadharaju

  4. Department of ECE, K.S. Institute of Technology, Bangalore, India

    Surekha Borra

Authors
  1. P. Vidyasree
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  2. Gudavalli Madhavi
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  3. S. Viswanadharaju
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  4. Surekha Borra
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Corresponding author

Correspondence to P. Vidyasree .

Editor information

Editors and Affiliations

  1. Department of Information Technology, Techno India College of Technology, Kolkata, India

    Nilanjan Dey

  2. Faculty of Engineering, Tanta University, Tanta, Egypt

    Amira S. Ashour

  3. K.S. Institute of Technology, Bangalore, Karnataka, India

    Surekha Borra

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Vidyasree, P., Madhavi, G., Viswanadharaju, S., Borra, S. (2018). A Bio-application for Accident Victim Identification Using Biometrics. In: Dey, N., Ashour, A., Borra, S. (eds) Classification in BioApps. Lecture Notes in Computational Vision and Biomechanics, vol 26. Springer, Cham. https://doi.org/10.1007/978-3-319-65981-7_15

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  • DOI: https://doi.org/10.1007/978-3-319-65981-7_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-65980-0

  • Online ISBN: 978-3-319-65981-7

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