Evaluation of the DWT‐PCA/SVD Recognition Algorithm on Reconstructed Frontal Face Images
Louis Asiedu,
Bernard O. Essah,
Samuel Iddi,
K. Doku-Amponsah and
Felix O. Mettle
Journal of Applied Mathematics, 2021, vol. 2021, issue 1
Abstract:
The face is the second most important biometric part of the human body, next to the finger print. Recognition of face image with partial occlusion (half image) is an intractable exercise as occlusions affect the performance of the recognition module. To this end, occluded images are sometimes reconstructed or completed with some imputation mechanism before recognition. This study assessed the performance of the principal component analysis and singular value decomposition algorithm using discrete wavelet transform (DWT‐PCA/SVD) as preprocessing mechanism on the reconstructed face image database. The reconstruction of the half face images was done leveraging on the property of bilateral symmetry of frontal faces. Numerical assessment of the performance of the adopted recognition algorithm gave average recognition rates of 95% and 75% when left and right reconstructed face images were used for recognition, respectively. It was evident from the statistical assessment that the DWT‐PCA/SVD algorithm gives relatively lower average recognition distance for the left reconstructed face images. DWT‐PCA/SVD is therefore recommended as a suitable algorithm for recognizing face images under partial occlusion (half face images). The algorithm performs relatively better on left reconstructed face images.
Date: 2021
References: Add references at CitEc
Citations:
Downloads: (external link)
https://doi.org/10.1155/2021/5541522
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:wly:jnljam:v:2021:y:2021:i:1:n:5541522
Access Statistics for this article
More articles in Journal of Applied Mathematics from John Wiley & Sons
Bibliographic data for series maintained by Wiley Content Delivery ().