Optimization design and application of library face recognition access control system based on improved PCA.
The application of face recognition technology in Library Access Control System (LACS) has an important impact on improving the security and management efficiency of the library. However, the traditional face recognition methods have some limitations in the face of complex environmental conditions s...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0313415 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841533169350737920 |
|---|---|
| author | Na Lin Yan Ding Yulei Tan |
| author_facet | Na Lin Yan Ding Yulei Tan |
| author_sort | Na Lin |
| collection | DOAJ |
| description | The application of face recognition technology in Library Access Control System (LACS) has an important impact on improving the security and management efficiency of the library. However, the traditional face recognition methods have some limitations in the face of complex environmental conditions such as illumination and posture change. To solve this problem, an improved method combining the Aggregating Spatial Embeddings for Face Recognition (ASEF) algorithm and Principal Component Analysis (PCA) is proposed. The PCA algorithm is optimized by introducing beta prior and full probability Bayesian model. In addition, the research also integrates K-means Clustering Algorithm (KA) to further improve the accuracy and efficiency of face recognition. The experiment showed that the improved PCA method had an average recognition rate of 92.6%, an average recognition speed of 0.40s, and higher accuracy compared to other related methods, reaching 96%. In practical applications, the system quickly and accurately completes the identification of personnel entry and exit, and improves the efficiency and security of library access management. |
| format | Article |
| id | doaj-art-78f4dfdc874042a3852a0aa3869d39a0 |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-78f4dfdc874042a3852a0aa3869d39a02025-01-17T05:31:39ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01201e031341510.1371/journal.pone.0313415Optimization design and application of library face recognition access control system based on improved PCA.Na LinYan DingYulei TanThe application of face recognition technology in Library Access Control System (LACS) has an important impact on improving the security and management efficiency of the library. However, the traditional face recognition methods have some limitations in the face of complex environmental conditions such as illumination and posture change. To solve this problem, an improved method combining the Aggregating Spatial Embeddings for Face Recognition (ASEF) algorithm and Principal Component Analysis (PCA) is proposed. The PCA algorithm is optimized by introducing beta prior and full probability Bayesian model. In addition, the research also integrates K-means Clustering Algorithm (KA) to further improve the accuracy and efficiency of face recognition. The experiment showed that the improved PCA method had an average recognition rate of 92.6%, an average recognition speed of 0.40s, and higher accuracy compared to other related methods, reaching 96%. In practical applications, the system quickly and accurately completes the identification of personnel entry and exit, and improves the efficiency and security of library access management.https://doi.org/10.1371/journal.pone.0313415 |
| spellingShingle | Na Lin Yan Ding Yulei Tan Optimization design and application of library face recognition access control system based on improved PCA. PLoS ONE |
| title | Optimization design and application of library face recognition access control system based on improved PCA. |
| title_full | Optimization design and application of library face recognition access control system based on improved PCA. |
| title_fullStr | Optimization design and application of library face recognition access control system based on improved PCA. |
| title_full_unstemmed | Optimization design and application of library face recognition access control system based on improved PCA. |
| title_short | Optimization design and application of library face recognition access control system based on improved PCA. |
| title_sort | optimization design and application of library face recognition access control system based on improved pca |
| url | https://doi.org/10.1371/journal.pone.0313415 |
| work_keys_str_mv | AT nalin optimizationdesignandapplicationoflibraryfacerecognitionaccesscontrolsystembasedonimprovedpca AT yanding optimizationdesignandapplicationoflibraryfacerecognitionaccesscontrolsystembasedonimprovedpca AT yuleitan optimizationdesignandapplicationoflibraryfacerecognitionaccesscontrolsystembasedonimprovedpca |