Simona Crihalmeanu

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Biometrics is the science of recognizing people based on their physical or behavioral traits such as face, fingerprints, iris, and voice. Among these characteristics, ocular biometrics has gained popularity due to the significant progress made in iris recognition. However, iris recognition is unfavorably influenced by the non-frontal gaze direction of the(More)
Besides the iris, conjunctival vasculature may also be used for ocular biometric recognition. Conjunctival vessel patterns can be easily observed in the visible spectrum and can compensate for off-angle or otherwise occluded iridial texture. In this paper, classification of conjunctival vasculature using Gray Level Co-occurrence Matrix (GLCM) is studied.(More)
Ocular biometrics has made significant strides over the past decade primarily due to the rapid advances in iris recognition. Recent literature has investigated the possibility of using conjunctival vasculature as an added ocular biometric. These patterns, observed on the sclera of the human eye, are especially significant when the iris is off-angle with(More)
Ocular biometrics has made significant progress over the past decade primarily due to advances in iris recognition. Initial research in the field of iris recognition focused on the acquisition and processing of frontal irides which may require considerable subject cooperation. However, when the iris is off-angle with respect to the acquisition device, the(More)
Vascular Similarly Measurement (VSM) is an important tool in many biomedical applications. However, designing a robust computational VSM remains a challenge. We investigate different wavelet families and their orders to find their efficacy as feature extractors for computational VSM. Using a 50-subject dataset of RGB ocular surface vasculature images, we(More)
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