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LMZMPM: Local Modified Zernike Moment Per-Unit Mass for Robust Human Face Recognition

Arindam Kar, Sourav Pramanik, Arghya Chakraborty, Debotosh Bhattacharjee, Edmond S. L. Ho and Hubert P. H. Shum
IEEE Transactions on Information Forensics and Security (TIFS), 2021

 Impact Factor: 6.8 Top 25% Journal in Engineering, Electrical & Electronic# Citation: 18#

LMZMPM: Local Modified Zernike Moment Per-Unit Mass for Robust Human Face Recognition
# According to Google Scholar 2023"

Abstract

In this work, we proposed a novel method, called Local Modified Zernike Moment per unit Mass (LMZMPM), for face recognition, which is invariant to illumination, scaling, noise, in-plane rotation, and translation, along with other orthogonal and inherent properties of the Zernike Moments (ZMs). The proposed LMZMPM is computed for each pixel in a neighborhood of size 3 x 3, and then considers the complex tuple that contains both the phase and magnitude coefficients of LMZMPM as the extracted features. As it contains both the phase and the magnitude components of the complex feature, it has more information about the image and thus preserves both the edge and structural information. We also propose a hybrid similarity measure, combining the Jaccard Similarity with the L1 distance, and applied to the extracted feature set for classification. The feasibility of the proposed LMZMPM technique on varying illumination has been evaluated on the CMU-PIE and the extended Yale B databases with an average Rank-1 Recognition (R1R) accuracy of 99.8% and 98.66% respectively. To assess the reliability of the method with variations in noise, rotation, scaling, and translation, we evaluate it on the AR database and obtain an average R1R higher than that of recent state-of-the-art methods. The proposed method shows a very high recognition rate on Heterogeneous Face Recognition as well, with 100% on CUFS, and 98.80% on CASIA-HFB.

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Citations

BibTeX

@article{kar21lmzmpm,
 author={Kar, Arindam and Pramanik, Sourav and Chakraborty, Arghya and Bhattacharjee, Debotosh and Ho, Edmond S. L. and Shum, Hubert P. H.},
 journal={IEEE Transactions on Information Forensics and Security},
 title={LMZMPM: Local Modified Zernike Moment Per-Unit Mass for Robust Human Face Recognition},
 year={2021},
 volume={16},
 number={1},
 pages={495--509},
 numpages={15},
 doi={10.1109/TIFS.2020.3015552},
 issn={1556-6021},
 publisher={IEEE},
}

RIS

TY  - JOUR
AU  - Kar, Arindam
AU  - Pramanik, Sourav
AU  - Chakraborty, Arghya
AU  - Bhattacharjee, Debotosh
AU  - Ho, Edmond S. L.
AU  - Shum, Hubert P. H.
T2  - IEEE Transactions on Information Forensics and Security
TI  - LMZMPM: Local Modified Zernike Moment Per-Unit Mass for Robust Human Face Recognition
PY  - 2021
VL  - 16
IS  - 1
SP  - 495
EP  - 509
DO  - 10.1109/TIFS.2020.3015552
SN  - 1556-6021
PB  - IEEE
ER  - 

Plain Text

Arindam Kar, Sourav Pramanik, Arghya Chakraborty, Debotosh Bhattacharjee, Edmond S. L. Ho and Hubert P. H. Shum, "LMZMPM: Local Modified Zernike Moment Per-Unit Mass for Robust Human Face Recognition," IEEE Transactions on Information Forensics and Security, vol. 16, no. 1, pp. 495-509, IEEE, 2021.

Supporting Grants

Similar Research

Lining Zhang, Hubert P. H. Shum, Li Liu, Guodong Guo and Ling Shao, "Multiview Discriminative Marginal Metric Learning for Makeup Face Verification", Neurocomputing, 2019
Daniel Organisciak, Edmond S. L. Ho and Hubert P. H. Shum, "Makeup Style Transfer on Low-Quality Images with Weighted Multi-Scale Attention", Proceedings of the 2020 International Conference on Pattern Recognition (ICPR), 2020
Asish Bera, Ratnadeep Dey, Debotosh Bhattacharjee, Mita Nasipuri and Hubert P. H. Shum, "Spoofing Detection on Hand Images Using Quality Assessment", Multimedia Tools and Applications (MTAP), 2021

 

 

Last updated on 17 February 2024
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