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An efficient multiscale scheme using local zernike moments for face recognition

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info:eu-repo/semantics/openAccess

Date

2018

Author

Başaran, Emrah
Gökmen, Muhittin
Kamasak, Mustafa E.

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Citation

Basaran, E., Gokmen, M., & Kamasak, M.E. An Efficient Multiscale Scheme Using Local Zernike Moments for Face Recognition. Appl. Sci. 2018, 8, 827.

Abstract

In this study, we propose a face recognition scheme using local Zernike moments (LZM), which can be used for both identification and verification. In this scheme, local patches around the landmarks are extracted from the complex components obtained by LZM transformation. Then, phase magnitude histograms are constructed within these patches to create descriptors for face images. An image pyramid is utilized to extract features at multiple scales, and the descriptors are constructed for each image in this pyramid. We used three different public datasets to examine the performance of the proposed method:Face Recognition Technology (FERET), Labeled Faces in the Wild (LFW), and Surveillance Cameras Face (SCface). The results revealed that the proposed method is robust against variations such as illumination, facial expression, and pose. Aside from this, it can be used for low-resolution face images acquired in uncontrolled environments or in the infrared spectrum. Experimental results show that our method outperforms state-of-the-art methods on FERET and SCface datasets.

Source

Applied Sciences

Volume

8

Issue

5

URI

https://doi.org/10.3390/app8050827
https://hdl.handle.net/20.500.11779/406

Collections

  • Araştırma Çıktıları, Scopus İndeksli Yayınlar Koleksiyonu [375]
  • Araştırma Çıktıları, WOS İndeksli Yayınlar Koleksiyonu [433]
  • MF, BM, Makale Koleksiyonu [23]



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