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Human authentication based on fusion of thermal and visible face images

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Abstract

In recent past, considerable amount of research has been done to increase the performance of a face authentication system in uncontrolled environment such as illumination. However, the performance has not been improved significantly since visible face images are dependent of illumination. To overcome the limitation of visible face images, researchers are using infrared (IR) face images. However, it also does not completely independent of illumination. Image fusion of visible and thermal face images is an alternative in research community nowadays. In this work, a fusion method is introduced to fuse visible and IR images for face authentication. The proposed fusion method relies on translation invariant À-trous wavelet transform and fractal dimension using differential box counting method. Five popular fusion metrics namely, ratio of spatial frequency error, normalized mutual information, edge information, universal image quality index, extended frequency comparison index are considered to measure the effectiveness of the proposed fusion algorithm quantitatively over four state-of-the-art methods. A new similarity measure is also proposed to check how close a fused face image from others are. All the experiments are performed on three databases namely, IRIS benchmark face database, UGC-JU face database and SCface face database. All the results depict that the proposed fusion method along with similarity measure for face authentication outperforms all the four state-of-the-art methods in terms of accuracy, precision and recall.

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Acknowledgments

Ayan Seal thank to Media Lab Asia, Ministry of Electronics and Information Technology, Government of India for providing young faculty research fellowship. Portions of the research in this paper use the SCface database of facial images. Credit is hereby given to the University of Zagreb, Faculty of Electrical Engineering and Computing for providing the database of facial images. We thank the anonymous reviewers for their many insightful comments and suggestions.

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  1. PDPM Indian Institute of Information Technology, Design and Manufacturing, Jabalpur, 482005, India

    Ayan Seal & Chinmaya Panigrahy

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  1. Ayan Seal
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Correspondence to Ayan Seal.

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Seal, A., Panigrahy, C. Human authentication based on fusion of thermal and visible face images. Multimed Tools Appl 78, 30373–30395 (2019). https://doi.org/10.1007/s11042-019-7701-6

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