Illumination invariant face recognition using convolutional neural networks

N, Pattabhi Ramaiah and Ijjina, E P and C, Krishna Mohan (2015) Illumination invariant face recognition using convolutional neural networks. In: Signal Processing, Informatics, Communication and Energy Systems (SPICES), 2015, 19-21, February 2015, Kozhikode , India.

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Face is one of the most widely used biometric in security systems. Despite its wide usage, face recognition is not a fully solved problem due to the challenges associated with varying illumination conditions and pose. In this paper, we address the problem of face recognition under non-uniform illumination using deep convolutional neural networks (CNN). The ability of a CNN to learn local patterns from data is used for facial recognition. The symmetry of facial information is exploited to improve the performance of the system by considering the horizontal reflections of the facial images. Experiments conducted on Yale facial image dataset demonstrate the efficacy of the proposed approach.

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Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: biometrics, convolutional neural networks, facial recognition, non-uniform illumination,
Subjects: Computer science > Big Data Analytics
Depositing User: Team Library
Date Deposited: 31 Jul 2015 11:31
Last Modified: 01 Sep 2017 09:19
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