RERS-CC: Robotic facial recognition system for improving the accuracy of human face identification using HRI
BACKGROUND: Human-Computer Interaction (HCI) is incorporated with a variety of applications for input processing and response actions. Facial recognition systems in workplaces and security systems help to improve the detection and classification of humans based on the vision experienced by the input...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English English |
| Published: |
IOS Press
2021
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| Online Access: | http://umpir.ump.edu.my/id/eprint/33293/ http://umpir.ump.edu.my/id/eprint/33293/1/RERS-CC-%20Robotic%20facial%20recognition%20system%20for%20improving.pdf http://umpir.ump.edu.my/id/eprint/33293/7/RERS-CC_%20Robotic%20facial%20recognition%20system%20for%20improving%20the%20accuracy%20of%20human%20face%20identification%20using%20HRI.pdf |
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| author | Wang, Jing Tao, Hai Rahman, Md. Arafatur M. Nomani, Kabir Yafeng, Li Zhang, Renrui Salih, Sinan Q. Jasni, Mohamad Zain |
| author_facet | Wang, Jing Tao, Hai Rahman, Md. Arafatur M. Nomani, Kabir Yafeng, Li Zhang, Renrui Salih, Sinan Q. Jasni, Mohamad Zain |
| author_sort | Wang, Jing |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | BACKGROUND: Human-Computer Interaction (HCI) is incorporated with a variety of applications for input processing and response actions. Facial recognition systems in workplaces and security systems help to improve the detection and classification of humans based on the vision experienced by the input system.
OBJECTIVES: In this manuscript, the Robotic Facial Recognition System using the Compound Classifier (RERS-CC) is introduced to improve the recognition rate of human faces. The process is differentiated into classification, detection, and recognition phases that employ principal component analysis based learning. In this learning process, the errors in image processing based on the extracted different features are used for error classification and accuracy improvements.
RESULTS: The performance of the proposed RERS-CC is validated experimentally using the input image dataset in MATLAB tool. The performance results show that the proposed method improves detection and recognition accuracy with fewer errors and processing time.
CONCLUSION: The input image is processed with the knowledge of the features and errors that are observed with different orientations and time instances. With the help of matching dataset and the similarity index verification, the proposed method identifies precise human face with augmented true positives and recognition rate. |
| first_indexed | 2025-11-15T03:09:33Z |
| format | Article |
| id | ump-33293 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-15T03:09:33Z |
| publishDate | 2021 |
| publisher | IOS Press |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-332932024-01-15T01:48:42Z http://umpir.ump.edu.my/id/eprint/33293/ RERS-CC: Robotic facial recognition system for improving the accuracy of human face identification using HRI Wang, Jing Tao, Hai Rahman, Md. Arafatur M. Nomani, Kabir Yafeng, Li Zhang, Renrui Salih, Sinan Q. Jasni, Mohamad Zain QA76 Computer software T Technology (General) BACKGROUND: Human-Computer Interaction (HCI) is incorporated with a variety of applications for input processing and response actions. Facial recognition systems in workplaces and security systems help to improve the detection and classification of humans based on the vision experienced by the input system. OBJECTIVES: In this manuscript, the Robotic Facial Recognition System using the Compound Classifier (RERS-CC) is introduced to improve the recognition rate of human faces. The process is differentiated into classification, detection, and recognition phases that employ principal component analysis based learning. In this learning process, the errors in image processing based on the extracted different features are used for error classification and accuracy improvements. RESULTS: The performance of the proposed RERS-CC is validated experimentally using the input image dataset in MATLAB tool. The performance results show that the proposed method improves detection and recognition accuracy with fewer errors and processing time. CONCLUSION: The input image is processed with the knowledge of the features and errors that are observed with different orientations and time instances. With the help of matching dataset and the similarity index verification, the proposed method identifies precise human face with augmented true positives and recognition rate. IOS Press 2021 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/33293/1/RERS-CC-%20Robotic%20facial%20recognition%20system%20for%20improving.pdf pdf en http://umpir.ump.edu.my/id/eprint/33293/7/RERS-CC_%20Robotic%20facial%20recognition%20system%20for%20improving%20the%20accuracy%20of%20human%20face%20identification%20using%20HRI.pdf Wang, Jing and Tao, Hai and Rahman, Md. Arafatur and M. Nomani, Kabir and Yafeng, Li and Zhang, Renrui and Salih, Sinan Q. and Jasni, Mohamad Zain (2021) RERS-CC: Robotic facial recognition system for improving the accuracy of human face identification using HRI. Work, 68 (3). pp. 923-934. ISSN 1051-9815. (Published) https://doi.org/10.3233/wor-203426 10.3233/WOR-203426 |
| spellingShingle | QA76 Computer software T Technology (General) Wang, Jing Tao, Hai Rahman, Md. Arafatur M. Nomani, Kabir Yafeng, Li Zhang, Renrui Salih, Sinan Q. Jasni, Mohamad Zain RERS-CC: Robotic facial recognition system for improving the accuracy of human face identification using HRI |
| title | RERS-CC: Robotic facial recognition system for improving the accuracy of human face identification using HRI |
| title_full | RERS-CC: Robotic facial recognition system for improving the accuracy of human face identification using HRI |
| title_fullStr | RERS-CC: Robotic facial recognition system for improving the accuracy of human face identification using HRI |
| title_full_unstemmed | RERS-CC: Robotic facial recognition system for improving the accuracy of human face identification using HRI |
| title_short | RERS-CC: Robotic facial recognition system for improving the accuracy of human face identification using HRI |
| title_sort | rers-cc: robotic facial recognition system for improving the accuracy of human face identification using hri |
| topic | QA76 Computer software T Technology (General) |
| url | http://umpir.ump.edu.my/id/eprint/33293/ http://umpir.ump.edu.my/id/eprint/33293/ http://umpir.ump.edu.my/id/eprint/33293/ http://umpir.ump.edu.my/id/eprint/33293/1/RERS-CC-%20Robotic%20facial%20recognition%20system%20for%20improving.pdf http://umpir.ump.edu.my/id/eprint/33293/7/RERS-CC_%20Robotic%20facial%20recognition%20system%20for%20improving%20the%20accuracy%20of%20human%20face%20identification%20using%20HRI.pdf |