Abstract
Biometric verification techniques are increasingly being used in mobile devices these days with the aim of keeping private data secure and impregnable. In our approach, we propose to use the inbuilt capacitive touchscreen of mobile devices as an image sensor to collect the image of ear (earprint) and use it as biometrics. The technique produces a precision of 0.8761 and recall of 0.596 on the acquired data. Since most of the touch screens are capacitive sensing, our proposed technique presents a reliable biometric solution for a vast number of mobile devices.
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Maheshwari, M., Arora, S., Srivastava, A.M., Agrawal, A., Garg, M., Prakash, S. (2018). Earprint Based Mobile User Authentication Using Convolutional Neural Network and SIFT. In: Huang, DS., Bevilacqua, V., Premaratne, P., Gupta, P. (eds) Intelligent Computing Theories and Application. ICIC 2018. Lecture Notes in Computer Science(), vol 10954. Springer, Cham. https://doi.org/10.1007/978-3-319-95930-6_87
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DOI: https://doi.org/10.1007/978-3-319-95930-6_87
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