Abstract
Face Recognition (FR) is one of the most thriving fields of contemporary research, and despite its universal application in authentication and verification systems, ensuring its effectiveness in unconstrained scenarios has predominantly remained an on-going challenge in Computer Vision, because FR systems experience considerable loss in performance, when there exists significant variation between the test and database faces in terms of attributes such as Pose, Camera Angle, Illumination and so on. The potency of FR systems markedly declines in the presence of noise in a given face and furthermore, the performance is also determined to a large degree by the Feature Extraction technique that is employed. Hence in this paper, we propose a novel mechanism known as Fuzzy-GIST, that can proficiently perform FR by adeptly handling real-time images (which contain the aforementioned unconstrained attributes) in low-powered portable devices by employing Fuzzy Filters to eliminate extraneous noise in the facial image, prior to feature extraction using the computationally less demanding GIST descriptor. Backed by relevant mathematical defense, we will establish the efficacy of our proposed system by conducting detailed experimentations on the ORL and IIT-K databases.
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Vinay, A., Gagana, B., Shekhar, V.S., Shekar, V.S., Balasubramanya Murthy, K.N., Natarajan, S. (2018). Face Recognition Using the Novel Fuzzy-GIST Mechanism. In: Guru, D., Vasudev, T., Chethan, H., Kumar, Y. (eds) Proceedings of International Conference on Cognition and Recognition . Lecture Notes in Networks and Systems, vol 14. Springer, Singapore. https://doi.org/10.1007/978-981-10-5146-3_36
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DOI: https://doi.org/10.1007/978-981-10-5146-3_36
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