High Speed Holographic Optical Correlator for Face Recognition

Watanabe, Eiji; Kodate, Kashiko

doi:10.5772/6642

Cited by 2 publications

(2 citation statements)

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“…Worthy of note is the two-level decision tree learning approach used in [9] to improve the recognition rate. Another typical example of optical implementation for face recognition is the S-FARCO system proposed [10].…”

Section: A Brief Review On Correlation-based Face Recognitionmentioning

confidence: 99%

“…Since Vijaya Kumar applied the minimum average correlation energy (MACE) filter for biometric (face, finger print and iris) verification [3], a number of face recognition or tracking schemes based on correlation methods have been reported [4][5][6][7][8]. Some of them have been implemented and put into practical use [9][10][11][12][13]. Compared with other traditional face recognition methods, these correlation-based schemes exhibit strong discrimination ability, robustness, and efficiency.…”

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confidence: 99%

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New perspectives in face correlation: discrimination enhancement in face recognition based on iterative algorithm

Wang

Alfalou

Brosseau

2016

Optical Pattern Recognition XXVII

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Here, we report a brief review on the recent developments of correlation algorithms. Several implementation schemes and specific applications proposed in recent years are also given to illustrate powerful applications of these methods. Following a discussion and comparison of the implementation of these schemes, we believe that all-numerical implementation is the most practical choice for application of the correlation method because the advantages of optical processing cannot compensate the technical and/or financial cost needed for an optical implementation platform. We also present a simple iterative algorithm to optimize the training images of composite correlation filters. By making use of three or four iterations, the peak-to-correlation energy (PCE) value of correlation plane can be significantly enhanced. A simulation test using the Pointing Head Pose Image Database (PHPID)illustrates the effectiveness of this statement. Our method can be applied in many composite filters based on linear composition of training images as an optimization means.

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Section: A Brief Review On Correlation-based Face Recognitionmentioning

confidence: 99%