Evaluation of the DWT-PCA/SVD Recognition Algorithm on Reconstructed Frontal Face Images
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 recons...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2021/5541522 |
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| author | Louis Asiedu Bernard O. Essah Samuel Iddi K. Doku-Amponsah Felix O. Mettle |
| author_facet | Louis Asiedu Bernard O. Essah Samuel Iddi K. Doku-Amponsah Felix O. Mettle |
| author_sort | Louis Asiedu |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-b012868e877542cd995446a91540aa8d |
| institution | Kabale University |
| issn | 1110-757X 1687-0042 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Applied Mathematics |
| spelling | doaj-art-b012868e877542cd995446a91540aa8d2025-02-03T06:06:27ZengWileyJournal of Applied Mathematics1110-757X1687-00422021-01-01202110.1155/2021/55415225541522Evaluation of the DWT-PCA/SVD Recognition Algorithm on Reconstructed Frontal Face ImagesLouis Asiedu0Bernard O. Essah1Samuel Iddi2K. Doku-Amponsah3Felix O. Mettle4Department of Statistics & Actuarial Science, School of Physical and Mathematical Sciences, University of Ghana, Legon, Accra, GhanaDepartment of Statistics & Actuarial Science, School of Physical and Mathematical Sciences, University of Ghana, Legon, Accra, GhanaDepartment of Statistics & Actuarial Science, School of Physical and Mathematical Sciences, University of Ghana, Legon, Accra, GhanaDepartment of Statistics & Actuarial Science, School of Physical and Mathematical Sciences, University of Ghana, Legon, Accra, GhanaDepartment of Statistics & Actuarial Science, School of Physical and Mathematical Sciences, University of Ghana, Legon, Accra, GhanaThe 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.http://dx.doi.org/10.1155/2021/5541522 |
| spellingShingle | Louis Asiedu Bernard O. Essah Samuel Iddi K. Doku-Amponsah Felix O. Mettle Evaluation of the DWT-PCA/SVD Recognition Algorithm on Reconstructed Frontal Face Images Journal of Applied Mathematics |
| title | Evaluation of the DWT-PCA/SVD Recognition Algorithm on Reconstructed Frontal Face Images |
| title_full | Evaluation of the DWT-PCA/SVD Recognition Algorithm on Reconstructed Frontal Face Images |
| title_fullStr | Evaluation of the DWT-PCA/SVD Recognition Algorithm on Reconstructed Frontal Face Images |
| title_full_unstemmed | Evaluation of the DWT-PCA/SVD Recognition Algorithm on Reconstructed Frontal Face Images |
| title_short | Evaluation of the DWT-PCA/SVD Recognition Algorithm on Reconstructed Frontal Face Images |
| title_sort | evaluation of the dwt pca svd recognition algorithm on reconstructed frontal face images |
| url | http://dx.doi.org/10.1155/2021/5541522 |
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