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Biometric access control systems often employ fingerprint recognition based on the analysis of ridge patterns and minutiae. The inclusion of finer details, such as sweat pores, increases the accuracy of fingerprint identification. However, the distribution of sweat pores is difficult to extract from conventional fingerprint images, where image quality is susceptible to variations in fingertip surface conditions. Furthermore, a fingertip surface can be routinely counterfeited with a variety of techniques. We propose a more reliable biometric technology using spectral domain optical coherence tomography (SD-OCT) to image the subsurface of a fingertip. Experiments demonstrate high repeatability in clearly visualizing the distribution of sweat (eccrine) glands in live fingertips. Experiments on artificial fingertips confirm this is a spoof-proof approach. We believe these encouraging results demonstrate the value of SD-OCT as a robust fingerprint identification technology for biometric recognition.
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Liu et al. (2010) studied this question.
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