Performance Enhancement of Face Recognition Algorithms Based on Principal Components Analysis

1
Ahmed Elbala Ahmed
Ahmed Elbala Ahmed
2
Khalil. B. Ahmed. A
Khalil. B. Ahmed. A
3
Banaga Hassan Mohammed
Banaga Hassan Mohammed
1 ALIMAM ALHADI College-Electrical Engineering, Sudan.

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In this paper many face recognition algorithms and codes were studied and tested, and it was concluded that they still face the challenge of not providing optimal accuracy and precision, especially in the case of images that have some distortions such as those resulting from poor illumination, different angles of taking the image and different facial expressions or wear hats, masks or glasses. Although recognition technologies using iris and fingerprint are more accurate, face recognition technology is the most common and widely utilized since it is simple to apply and execute, in addition it can be used directly anywhere and does not require any physical input from user. The results show that the best performance of face recognition depends on the number of principal components (PCs), the percentage of face recognition increases in the ranges of 10%, 40%, 50%, 80%, 90% and 100% when the PCs increase in order of 1, 3, 5, 7, 11 and 15, respectively.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

Ahmed Elbala Ahmed. 2026. \u201cPerformance Enhancement of Face Recognition Algorithms Based on Principal Components Analysis\u201d. Global Journal of Research in Engineering - F: Electrical & Electronic GJRE-F Volume 23 (GJRE Volume 23 Issue F2): .

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Enhanced face recognition algorithms improve accuracy via principal components.
Journal Specifications

Crossref Journal DOI 10.17406/gjre

Print ISSN 0975-5861

e-ISSN 2249-4596

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GJRE-F Classification: LCC Code: QA76.9.N37
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v1.2

Issue date

August 12, 2023

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English

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In this paper many face recognition algorithms and codes were studied and tested, and it was concluded that they still face the challenge of not providing optimal accuracy and precision, especially in the case of images that have some distortions such as those resulting from poor illumination, different angles of taking the image and different facial expressions or wear hats, masks or glasses. Although recognition technologies using iris and fingerprint are more accurate, face recognition technology is the most common and widely utilized since it is simple to apply and execute, in addition it can be used directly anywhere and does not require any physical input from user. The results show that the best performance of face recognition depends on the number of principal components (PCs), the percentage of face recognition increases in the ranges of 10%, 40%, 50%, 80%, 90% and 100% when the PCs increase in order of 1, 3, 5, 7, 11 and 15, respectively.

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Performance Enhancement of Face Recognition Algorithms Based on Principal Components Analysis

Ahmed Elbala Ahmed
Ahmed Elbala Ahmed ALIMAM ALHADI College-Electrical Engineering, Sudan.
Khalil. B. Ahmed. A
Khalil. B. Ahmed. A
Banaga Hassan Mohammed
Banaga Hassan Mohammed

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