Intelligent system for cross-spectral and cross-distance face matching

Shamia, D.; Chandy, D. Abraham

doi:10.1016/j.compeleceng.2017.09.004

Cited by 7 publications

(9 citation statements)

References 6 publications

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“…To the best of our knowledge, this study is the first in the literature to employ a phase-based correlation for cross-spectral cross-distance (CSCD) face recognition. Moreover, the proposed method outperforms the state-of-the-art approaches, such as those in [ 9 , 23 , 24 , 25 ].…”

Section: Introductionmentioning

confidence: 92%

“…In the CS system, the face images captured under the NIR spectral band are matched with the face images captured under the VIS spectral band. In the VIS spectral band, facial descriptions of people from different races show different characteristics [ 25 ]. In contrast, the NIR spectral band utilizes the calibrated IR sensor to overcome the different race factors such as skin color and facial characteristics.…”

Section: Related Workmentioning

confidence: 99%

“…Shamia and Chandy [ 25 ] examined the use of a combination of wavelet transform, Histogram-Oriented Gradient (HOG), and Local Binary Pattern (LBP) for CSCD face matching. In their study, the VIS spectral band was used as a gallery image, while the NIR spectral band was used as a probe image.…”

Section: Related Workmentioning

confidence: 99%

“…Finally, (c) we compared the performance the proposed method with the existing CSCD baseline methods [ 9 , 24 , 25 ].…”

Section: Experimental Settingmentioning

confidence: 99%

“…Previous CSCD approaches [ 9 , 23 , 24 , 25 ] applied a typical face recognition procedure, which consists of three steps: (1) preprocessing, (2) feature extraction, and (3) distance/ threshold calculation. The preprocessing step aims to prepare the image prior to feature extraction.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Homomorphic Filtering and Phase-Based Matching for Cross-Spectral Cross-Distance Face Recognition

Arnia

Oktiana

Saddami

et al. 2021

Sensors

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Facial recognition has a significant application for security, especially in surveillance technologies. In surveillance systems, recognizing faces captured far away from the camera under various lighting conditions, such as in the daytime and nighttime, is a challenging task. A system capable of recognizing face images in both daytime and nighttime and at various distances is called Cross-Spectral Cross Distance (CSCD) face recognition. In this paper, we proposed a phase-based CSCD face recognition approach. We employed Homomorphic filtering as photometric normalization and Band Limited Phase Only Correlation (BLPOC) for image matching. Different from the state-of-the-art methods, we directly utilized the phase component from an image, without the need for a feature extraction process. The experiment was conducted using the Long-Distance Heterogeneous Face Database (LDHF-DB). The proposed method was evaluated in three scenarios: (i) cross-spectral face verification at 1m, (ii) cross-spectral face verification at 60m, and (iii) cross-spectral face verification where the probe images (near-infrared (NIR) face images) were captured at 1m and the gallery data (face images) was captured at 60 m. The proposed CSCD method resulted in the best recognition performance among the CSCD baseline approaches, with an Equal Error Rate (EER) of 5.34% and a Genuine Acceptance Rate (GAR) of 93%.

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Section: Introductionmentioning

confidence: 92%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

“…Finally, (c) we compared the performance the proposed method with the existing CSCD baseline methods [ 9 , 24 , 25 ].…”

Section: Experimental Settingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Homomorphic Filtering and Phase-Based Matching for Cross-Spectral Cross-Distance Face Recognition

Arnia

Oktiana

Saddami

et al. 2021

Sensors

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show abstract

Thermal image identification against pose and expression variations using deep learning

Zaeri,

Qasim

2023

Journal of Engineering Research

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Multispectral Facial Recognition: A Review

2020

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Multispectral images are images with more than one channel acquired in different bands or spectral ranges of the electromagnetic spectrum. Each one has specific details that can be exploited in facial recognition applications. In particular, to detect facial expression variations, pose variations and presentation attacks, a facial analysis system can benefit not only of images from the visible spectral band but also of infrared images. In this paper we perform a review of the state of the art methods used in multispectral facial recognition using images from the visible spectral band and also from the Near Infrared, Short Wavelength Infrared and Long Wavelength Infrared sub-bands. The public multispectral databases for facial analysis are identified, and a comparison is made, taking into consideration their specifications. The multispectral facial recognition methods are classified according to their basic working principle, from the traditional Fusion and Subspace methods to the more recent Deep Neural Networks.INDEX TERMS Face recognition, multispectral image, infrared image. V. METHODS

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Intelligent system for cross-spectral and cross-distance face matching

Cited by 7 publications

References 6 publications

Homomorphic Filtering and Phase-Based Matching for Cross-Spectral Cross-Distance Face Recognition

Homomorphic Filtering and Phase-Based Matching for Cross-Spectral Cross-Distance Face Recognition

Thermal image identification against pose and expression variations using deep learning

Multispectral Facial Recognition: A Review

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