Paper
14 April 2010 A study of multibiometric traits of identical twins
Zhenan Sun, Alessandra A. Paulino, Jianjiang Feng, Zhenhua Chai, Tieniu Tan, Anil K. Jain
Author Affiliations +
Abstract
The increase in twin births has created a requirement for biometric systems to accurately determine the identity of a person who has an identical twin. The discriminability of some of the identical twin biometric traits, such as fingerprints, iris, and palmprints, is supported by anatomy and the formation process of the biometric characteristic, which state they are different even in identical twins due to a number of random factors during the gestation period. For the first time, we collected multiple biometric traits (fingerprint, face, and iris) of 66 families of twins, and we performed unimodal and multimodal matching experiments to assess the ability of biometric systems in distinguishing identical twins. Our experiments show that unimodal finger biometric systems can distinguish two different persons who are not identical twins better than they can distinguish identical twins; this difference is much larger in the face biometric system and it is not significant in the iris biometric system. Multimodal biometric systems that combine different units of the same biometric modality (e.g. multiple fingerprints or left and right irises.) show the best performance among all the unimodal and multimodal biometric systems, achieving an almost perfect separation between genuine and impostor distributions.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zhenan Sun, Alessandra A. Paulino, Jianjiang Feng, Zhenhua Chai, Tieniu Tan, and Anil K. Jain "A study of multibiometric traits of identical twins", Proc. SPIE 7667, Biometric Technology for Human Identification VII, 76670T (14 April 2010); https://doi.org/10.1117/12.851369
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Cited by 69 scholarly publications.
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KEYWORDS
Iris recognition

Biometrics

Iris

Databases

Facial recognition systems

Multimodal biometric systems

Image quality

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