Face recognition by fusing thermal infrared and visible imagery

Bebis, George; Gyaourova, Aglika; Singh, Saurabh; Pavlidis, Ioannis

doi:10.1016/j.imavis.2006.01.017

Cited by 145 publications

(68 citation statements)

References 41 publications

(65 reference statements)

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“…Bhowmick et al [3] have shown that thermal imagery can be used for face-recognition based on facial vein-patterns. Bebis et al [2] explore the fusion of visible and thermal imagery for face-recognition applications. Although they use face-recognition performance as a metric, the main focus of their work is on evaluating different methods for fusing the data from the two modalities.…”

Section: Related Workmentioning

confidence: 99%

What You Can't See Can Help You - Extended-Range Imaging for 3D-Mask Presentation Attack Detection

Bhattacharjee

Marcel

2017

2017 International Conference of the Biometrics Special Interest Group (BIOSIG)

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Abstract-High-quality custom-made 3D masks are increasing becoming a serious threat to face-recognition systems. This threat is driven, in part, by the falling cost of manufacturing such masks. Research in face presentation-attack detection (PAD) in general, and also specifically for 3D-mask based attacks, has mostly concentrated on imagery in the visible-light range of wavelengths (RGB). We look beyond imagery in the visible-light spectrum to find potentially easier solutions for the challenge of face presentation-attack detection (PAD). In particular, we explore the use of near-infrared (NIR) and thermal imagery to detect print-, replay-, and 3D-mask-attacks. This preliminary study shows that both NIR and thermal imagery can potentially simplify the task of face-PAD.

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Section: Related Workmentioning

confidence: 99%

What You Can't See Can Help You - Extended-Range Imaging for 3D-Mask Presentation Attack Detection

Bhattacharjee

Marcel

2017

2017 International Conference of the Biometrics Special Interest Group (BIOSIG)

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“…Their experimental results show substantial improvements recognition performance overall. Bebis et al [11] presented and compared two different fusion schemes for combining IR and visible imagery for the purpose of face recognition. Two different fusion schemes had been investigated in this paper.…”

Section: Previous Workmentioning

confidence: 99%

Performance Evaluation of Infrared and Visible Image Fusion Algorithms for Face Recognition

Wang¹,

Liang²,

Hu³

et al. 2007

Proceedings on Intelligent Systems and Knowledge Engineering (ISKE2007)

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Fusion of infrared and visible image is a potential solution to improve face recognition performance. In this paper, we propose a new fusion method based on singular value decomposition (SVD) and apply it to multiple spectrum face recognition. The performance of the proposed SVD-based fusion method is compared with that of average fusion, Laplacian Pyramid Decomposition (LPD) based fusion and Discrete Wavelet Transform (DWT) based fusion methods. The performances of the four image fusion methods for face recognition are analyzed by statistical experiments and the results show that the SVD-based fusion method is better in most conditions.

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“…Visual band imaging is highly matured and successful due to the advancement of sensor technology, availability of computing power, and high digital storage capacity [4,5,6]. However, the image processing task and applications are challenging if the visual images obtained under non-ideal environments [7,8,9].…”

Section: Introductionmentioning

confidence: 99%

“…But, IR imaging is sensitive to temperature changes in the surrounding environment. Currents of cold or warm air could influence the performance of the IR system [4,5,9]. IR imaging is also sensitive to variations in the heat patterns of the objects.…”

Section: Introductionmentioning

confidence: 99%

Swarm Intelligence based Optimization in Thermal Image Fusion using Dual Tree Discrete Wavelet Transform

Madheswari¹,

Venkateswaran²

2015

Proceedings of the 2015 Asia International Conference on Quantitative InfraRed Thermography

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In this paper, we propose a Particle Swarm Optimized image fusion framework in Discrete Wavelet Transform domain that combines the thermal image with the visual image to obtain a single informative fused image. Dual tree Discrete Wavelet Transform (DT-DWT) is applied for feature selection and particle swarm optimization (PSO) technique is used to obtain the optimized image. In the fusion process, an optimized weighting factor has been used to form a new composite image with maximized Entropy and minimized Root Mean Square Error (RMSE). Simulation results indicate that the proposed fusion framework results in better quality of the fused image.

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Face recognition by fusing thermal infrared and visible imagery

Cited by 145 publications

References 41 publications

What You Can't See Can Help You - Extended-Range Imaging for 3D-Mask Presentation Attack Detection

What You Can't See Can Help You - Extended-Range Imaging for 3D-Mask Presentation Attack Detection

Performance Evaluation of Infrared and Visible Image Fusion Algorithms for Face Recognition

Swarm Intelligence based Optimization in Thermal Image Fusion using Dual Tree Discrete Wavelet Transform

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