Multimodal Biometrics Recognition for Newborns

Multimodal Biometrics Recognition for Newborns

Shrikant Tiwari, Sanjay Kumar Singh
DOI: 10.4018/978-1-4666-4868-5.ch002
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Identification of newborns at birth is a critical issue for hospitals, birthing centers, and other institutions where multiple births occur. With approximately 300,000 infants born worldwide each day, a large hospital may experience over one hundred new births every day. Correct identification of infants is essential to ensure that each mother travels home with her own child. Mixing, abduction, and illegal adoption of newborns is a global problem, and the research done to solve this problem is minimal. In this chapter, the authors present a multimodal biometric framework for the recognition of newborns.
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Biometric System

A biometric system is basically a pattern recognition system that recognizes a person by classifying the binary code of a uniquely specific biological or physical characteristic to the binary code of the stored characteristic. Samples are taken from individuals to see if there is a similarity to biometric references previously taken from known individuals.

Biometric system involves four aspects (Jain et al., 2000, 1999) data acquisition and preprocessing feature extraction, similarity computation and decision making. The digital representation recorded in the system database, which describes the characteristics or features of a physical trait is defines as a template. It is obtained by a feature extraction algorithm and is generated through an enrolment or training process, which is depicted in Figure 1. The recognition process can be performed in two modes by a biometric system (Karthik Nandakumar, 2008).

Figure 1.

The core components of a single biometric system


Before considering multi-modal biometrics, it is important to understand the core features of a conventional (uni-modal) biometric system. Brief description about four components is given below:

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