Class-associative multiple target detection by use of fringe-adjusted joint transform correlation

Face recognition is a critical tool used in almost all major biometrics based security systems. But recognition, authentication and liveness detection of the face of an actual user is a major challenge because an imposter or a non-live face of the actual user can be used to spoof the security system. In this paper, a robust technique is proposed which detects liveness of faces in order to counter spoof attacks. The proposed technique uses a three-dimensional (3D) fast Fourier transform (FFT) to compare spectral energies of a live face and a fake face in a mathematically selective manner. The mathematical model involves evaluation of energies of selective high frequency bands of average power spectra of both live and non-live faces. It also carries out proper recognition and authentication of the face of the actual user using the fringe-adjusted joint transform correlation technique, which has been found to yield the highest correlation output for a match. Experimental tests using real life datasets show that the proposed technique yields excellent results for identifying live faces.

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“…The zero order term can be suppressed by additional further processing such as the Fourier plane image subtraction technique [15].…”

Section: Discussionmentioning

confidence: 99%

Efficient live face detection to counter spoof attack in face recognition systems

Biswas

Alam

2015

SPIE Proceedings

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“…The aforementioned false alarms and the undesired zero-order terms can be alleviated by using an algorithm known as multi-target detection algorithm (MTDA) 20 . In this algorithm, the following two combinations of the input joint image, involving the reference image ) , ( o y y x r + and the unknown input scene ) , ( o y y x s − as shown in the following equations, are taken.…”

Section: Multiple Target Detectionmentioning

confidence: 99%

“…An enhanced version of the fringe-adjusted filter, called hetero-associative fringe-adjusted filter is used to achieve a technique for robust real-time simultaneous multiple targets detection and tracking while satisfying the equal correlation peak criterion 20 . To evaluate the performance of the proposed technique, real life gray level image sequences supplied by the Army Missile Command (AMCOM) are used.…”

Section: Introductionmentioning

confidence: 99%

<title>Fringe-adjusted joint-transform-correlation-based hetero-associative multiple target-tracking</title>

2004

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A technique has been formulated based on hetero-associative target detection strategy that recognizes and tracks multiple dissimilar or hetero-associative targets from gray-scale image sequences taken from a moving aircraft in real time. Fringe-adjusted joint transform correlation combined with the proposed hetero-associative filter is used to enhance the correlation performance and thus ensures strong and equal cross-correlation peak for each element of the selected class. Tracking is accomplished by combining the analysis of single image frame with the determination of the motion from consecutive image frames. For efficient performance, the desired targets are identified prior to be tracked by correlating successive frames using the proposed filter which is an enhanced version of the fringe-adjusted filter. The optimality of the tracking performance is tested by MATLAB software.

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“…Among the various forms of JTC-based target recognition, the fringe-adjusted JTC (FJTC) technique has demonstrated great enhancements in detecting the correlation output peaks 13 – 16 In practice, multiple target detection faces many challenges, such as target variations from the same class and between class similarity, orientation, scaling, noises, deformations, and occlusions. To alleviate some of these problems, several methods were reported, such as Fourier plane subtraction, shifted phase-encoded technique, and reference phase-encoded technique 14 , 15 …”

Section: Introductionmentioning

confidence: 99%

Class-associative multiple target recognition for highly compressed color images in a joint transform correlator

Cherri

Nazar

2022

Opt. Eng.

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We propose a practical near real-time compression-based class-associative multiple target detection technique for color images. The size of the color images is reduced to its utmost ratio to speed up the processing time and to increase the storage capacity of the recognition system. A fringe-adjusted joint transform correlation technique is employed to successfully detect the compression-based multiple targets in colored images. In addition, to eliminate the false alarms and zero-order terms due to multiple desired and undesired objects in an input scene, we have used the shifted phase-encoded and the reference phase-encoded techniques. The performance of detecting the class-associative multiple targets for large compression ratios (up to 94%) and under strong noisy conditions (Gaussian and salt and pepper noises) is assessed through many computer simulations experiments. Furthermore, detecting small targets or even a small part of a target is presented for images occluded up to 90%.

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Class-associative multiple target detection by use of fringe-adjusted joint transform correlation

Cited by 17 publications

References 14 publications

Efficient live face detection to counter spoof attack in face recognition systems

Efficient live face detection to counter spoof attack in face recognition systems

<title>Fringe-adjusted joint-transform-correlation-based hetero-associative multiple target-tracking</title>

Class-associative multiple target recognition for highly compressed color images in a joint transform correlator

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