An Efficient Hybrid Face Recognition Algorithm Using PCA and GABOR Wavelets
With the rapid development of computers and the increasing, mass use of high-tech mobile devices, vision-based face recognition has advanced significantly. However, it is hard to conclude that the performance of computers surpasses that of humans, as humans have generally exhibited better performanc...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2014-04-01
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| Series: | International Journal of Advanced Robotic Systems |
| Online Access: | https://doi.org/10.5772/58473 |
| _version_ | 1819074993551572992 |
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| author | Hyunjong Cho Rodney Roberts Bowon Jung Okkyung Choi Seungbin Moon |
| author_facet | Hyunjong Cho Rodney Roberts Bowon Jung Okkyung Choi Seungbin Moon |
| author_sort | Hyunjong Cho |
| collection | DOAJ |
| description | With the rapid development of computers and the increasing, mass use of high-tech mobile devices, vision-based face recognition has advanced significantly. However, it is hard to conclude that the performance of computers surpasses that of humans, as humans have generally exhibited better performance in challenging situations involving occlusion or variations. Motivated by the recognition method of humans who utilize both holistic and local features, we present a computationally efficient hybrid face recognition method that employs dual-stage holistic and local feature-based recognition algorithms. In the first coarse recognition stage, the proposed algorithm utilizes Principal Component Analysis (PCA) to identify a test image. The recognition ends at this stage if the confidence level of the result turns out to be reliable. Otherwise, the algorithm uses this result for filtering out top candidate images with a high degree of similarity, and passes them to the next fine recognition stage where Gabor filters are employed. As is well known, recognizing a face image with Gabor filters is a computationally heavy task. The contribution of our work is in proposing a flexible dual-stage algorithm that enables fast, hybrid face recognition. Experimental tests were performed with the Extended Yale Face Database B to verify the effectiveness and validity of the research, and we obtained better recognition results under illumination variations not only in terms of computation time but also in terms of the recognition rate in comparison to PCA- and Gabor wavelet-based recognition algorithms. |
| first_indexed | 2024-12-21T18:18:20Z |
| format | Article |
| id | doaj.art-28216f9be80944cb93ec4cae0f604d6a |
| institution | Directory Open Access Journal |
| issn | 1729-8814 |
| language | English |
| last_indexed | 2024-12-21T18:18:20Z |
| publishDate | 2014-04-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | International Journal of Advanced Robotic Systems |
| spelling | doaj.art-28216f9be80944cb93ec4cae0f604d6a2022-12-21T18:54:37ZengSAGE PublishingInternational Journal of Advanced Robotic Systems1729-88142014-04-011110.5772/5847310.5772_58473An Efficient Hybrid Face Recognition Algorithm Using PCA and GABOR WaveletsHyunjong Cho0Rodney Roberts1Bowon Jung2Okkyung Choi3Seungbin Moon4 Sejong University, Seoul, Republic of Korea Department of Electrical and Computer Engineering, Florida State University, USA Sejong University, Seoul, Republic of Korea Sejong University, Seoul, Republic of Korea Sejong University, Seoul, Republic of KoreaWith the rapid development of computers and the increasing, mass use of high-tech mobile devices, vision-based face recognition has advanced significantly. However, it is hard to conclude that the performance of computers surpasses that of humans, as humans have generally exhibited better performance in challenging situations involving occlusion or variations. Motivated by the recognition method of humans who utilize both holistic and local features, we present a computationally efficient hybrid face recognition method that employs dual-stage holistic and local feature-based recognition algorithms. In the first coarse recognition stage, the proposed algorithm utilizes Principal Component Analysis (PCA) to identify a test image. The recognition ends at this stage if the confidence level of the result turns out to be reliable. Otherwise, the algorithm uses this result for filtering out top candidate images with a high degree of similarity, and passes them to the next fine recognition stage where Gabor filters are employed. As is well known, recognizing a face image with Gabor filters is a computationally heavy task. The contribution of our work is in proposing a flexible dual-stage algorithm that enables fast, hybrid face recognition. Experimental tests were performed with the Extended Yale Face Database B to verify the effectiveness and validity of the research, and we obtained better recognition results under illumination variations not only in terms of computation time but also in terms of the recognition rate in comparison to PCA- and Gabor wavelet-based recognition algorithms.https://doi.org/10.5772/58473 |
| spellingShingle | Hyunjong Cho Rodney Roberts Bowon Jung Okkyung Choi Seungbin Moon An Efficient Hybrid Face Recognition Algorithm Using PCA and GABOR Wavelets International Journal of Advanced Robotic Systems |
| title | An Efficient Hybrid Face Recognition Algorithm Using PCA and GABOR Wavelets |
| title_full | An Efficient Hybrid Face Recognition Algorithm Using PCA and GABOR Wavelets |
| title_fullStr | An Efficient Hybrid Face Recognition Algorithm Using PCA and GABOR Wavelets |
| title_full_unstemmed | An Efficient Hybrid Face Recognition Algorithm Using PCA and GABOR Wavelets |
| title_short | An Efficient Hybrid Face Recognition Algorithm Using PCA and GABOR Wavelets |
| title_sort | efficient hybrid face recognition algorithm using pca and gabor wavelets |
| url | https://doi.org/10.5772/58473 |
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