Abstract
Human Face recognition is one of the widely used biometric techniques for face identification and verification. It includes several subproblems like illumination variation, expression changes, aging, occlusion, and rotation of face images. Varying illumination is one of the well-known and challenging problems in human face recognition applications. In this paper, we proposed a novel approach to solve varying illumination problems in face images. The different stages include adaptive histogram equalization (AHE), Gaussian filtering, Log transform, difference of AHE+Gaussian filtering+Log image, and AHE+Log image, and then, we perform normalization. We are using principle component analysis (PCA) method for face recognition. The experimental results of proposed approach are compared with existing approaches, and it shows that our approach improves the performance of recognition under varying illumination conditions on Yale Face Database B.
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Jaliya, U.K., Rathod, J.M. (2015). A Novel Preprocessing Approach for Human Face Recognition Invariant to Illumination. In: Mandal, D., Kar, R., Das, S., Panigrahi, B. (eds) Intelligent Computing and Applications. Advances in Intelligent Systems and Computing, vol 343. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2268-2_28
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DOI: https://doi.org/10.1007/978-81-322-2268-2_28
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