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Algorithms for invariant long-wave infrared face segmentation: evaluation and comparison

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Abstract

This paper presents two methods for automatic segmentation of images of faces captured in long wavelength infrared, allowing a wide range of face rotations, expressions and artifacts (such as glasses and hats). We also present the validation of segmentation results using a recognition method to show the impact of the segmentation accuracy on the recognition. The paper presents two different approaches (one aimed at real-time performance and the other at high accuracy) and compares their performance against three other previously published methods. The proposed approaches are based on statistical modeling of pixel intensities and active contour application, although several other image processing operations are also performed. Experiments were performed on a total of 893 test images from four public available databases. The obtained results improve on previous existing methods up to 29.5 % for the first measure error (E 1) and up to 34.7 % for the second measure (E 2), depending on the method and database. Regarding the computational time, our proposals improve up to 63.32 % when compared with the other proposals. We also present the validation of the various segmentation methods that are presented by applying a face recognition method.

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Acknowledgments

We thank the anonymous reviewers for insightful comments that considerably strengthened the presentation of this work. We wish to thank Professor Cho Siu-Yeung David from the School of Computer Engineering at Nanyang Technological University (NTU) for the source code of his method [9]. We acknowledge the financial support given by ‘FCT - Fundação para a Ciência e Tecnologia’ and ‘FEDER’ in the scope of the PTDC/EIA/69106/2006 research project ‘BIOREC: Non-Cooperative Biometric Recognition’, the PTDC/EIA-EIA/103945/2008 research project ‘NECOVID: Covert Negative Biometric Identification’ and in the scope of the research grant SFRH/BD/72575/2010. We also acknowledge the support given by the IT - Instituto de Telecomunicações through ‘PEst-OE/EEI/LA0008/2013’.

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  1. IT - Instituto de Telecomunicações, Department of Computer Science, University of Beira Interior, 6200-001, Covilhã, Portugal

    Sílvio Filipe & Luís A. Alexandre

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  1. Sílvio Filipe
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  2. Luís A. Alexandre
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Correspondence to Sílvio Filipe.

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Filipe, S., Alexandre, L.A. Algorithms for invariant long-wave infrared face segmentation: evaluation and comparison. Pattern Anal Applic 17, 823–837 (2014). https://doi.org/10.1007/s10044-013-0354-6

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