DWT and LBP map based feature descriptors for face recognition in harsh light variations
Author
Source
The International Arab Journal of Information Technology
Issue
Vol. 19, Issue 3A (s) (31 May. 2022), pp.470-477, 8 p.
Publisher
Zarqa University Deanship of Scientific Research
Publication Date
2022-05-31
Country of Publication
Jordan
No. of Pages
8
Main Subjects
Information Technology and Computer Science
Abstract EN
In [11] Karanwal et al.
provided enhancements to three descriptors for Face Recognition under illumination variations.
The three descriptors for which enhancements are done are Local Binary Pattern (LBP), Horizontal Elliptical LBP (HELBP) and Median Binary Pattern (MBP).
By deploying Two Dimensional DWT (2D-DWT) (utilizing haar at level 1) before features extraction of LBP, HELBP and MBP, the enhancements are made.
These improved ones outperforms the original descriptors comprehensively.
After careful analyzing the work proposed in [11] it has been observed that even after image pre-processing, histograms of LBP, HELBP and MBP unable to capture the efficient information to declare as the robust descriptors in light variations.
In the proposed work it has been observed and implemented that map feature of LBP, HELBP and MBP (after image pre-processing by 2D-DWT) yields much better accuracy than the histogram based descriptors.
The three proposed descriptors are 2D-DWT+LBPmap, 2D-DWT+HELBPmap, 2D-DWT+MBPmap.
These map features full and completely outperform its respective histogram features & these are LBPhist, 2D-DWT+LBPhist, HELBPhist, 2D-DWT+HELBPhist, MBPhist and 2D-DWT+MBPhist.
Among all it is 2D-DWT+HELBPmap feature which yields best results.
The feature compression is fulfilled by the usage of Fishers Linear Discriminant Analysis (FLDA) and classification was done from Support Vector Machines (SVMs).
For experiments Yale B (YB) and Extended Yale B (EYB) datasets are used.
American Psychological Association (APA)
Karanwal, Shekhar. 2022. DWT and LBP map based feature descriptors for face recognition in harsh light variations. The International Arab Journal of Information Technology،Vol. 19, no. 3A (s), pp.470-477.
https://search.emarefa.net/detail/BIM-1437121
Modern Language Association (MLA)
Karanwal, Shekhar. DWT and LBP map based feature descriptors for face recognition in harsh light variations. The International Arab Journal of Information Technology Vol. 19, no. 3A (Special issue) (2022), pp.470-477.
https://search.emarefa.net/detail/BIM-1437121
American Medical Association (AMA)
Karanwal, Shekhar. DWT and LBP map based feature descriptors for face recognition in harsh light variations. The International Arab Journal of Information Technology. 2022. Vol. 19, no. 3A (s), pp.470-477.
https://search.emarefa.net/detail/BIM-1437121
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 476-477
Record ID
BIM-1437121