Face Recognition under Illumination Changes Using Color Fast and Adaptive Bi-Directional Empirical Mode Decomposition
Recently, the importance of face recognition in color images has been increasingly emphasized since popular CCD cameras are distributed to various applications. However, face feature extracted from the image will distorted non-linearly by lighting variations in intensity or directions, so this chan...
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| Format: | Article |
| Language: | Arabic |
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Mustansiriyah University/College of Engineering
2012-12-01
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| Series: | Journal of Engineering and Sustainable Development |
| Subjects: | |
| Online Access: | https://jeasd.uomustansiriyah.edu.iq/index.php/jeasd/article/view/1243 |
| _version_ | 1828198601134702592 |
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| author | Husam J. Naeemah |
| author_facet | Husam J. Naeemah |
| author_sort | Husam J. Naeemah |
| collection | DOAJ |
| description |
Recently, the importance of face recognition in color images has been increasingly emphasized since popular CCD cameras are distributed to various applications. However, face feature extracted from the image will distorted non-linearly by lighting variations in intensity or directions, so this changes will cause a serious performance degradation in face recognition. Many algorithms adopted by researchers to overcome the illumination problem. Most of them need multiple registered images per person or the prior knowledge of lighting conditions. According to the “common assumption” that illumination varies slowly and the face intrinsic feature (including 3D surface and reflectance) varies rapidly in local area, high frequency feature represents the face intrinsic structure. The Fast and Adaptive Bi-dimensional Empirical Mode Decomposition FABEMD has been extended for color image analysis. The proposed algorithm, based on the powerful transform for the color image named color FABEMD (CFABEMD). The color image decomposed into multi-layer high frequency images representing detail feature and low frequency images representing analogy feature. In addition a two measurements are proposed to quantify the detail feature that use to eliminate illumination variation, with these measurement weights, CFABEMD based multi-layer detail images recognition can be done under vary illumination.
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| first_indexed | 2024-04-12T10:41:11Z |
| format | Article |
| id | doaj.art-28fb7bf52cb84a24a4193609eab4aebf |
| institution | Directory Open Access Journal |
| issn | 2520-0917 2520-0925 |
| language | Arabic |
| last_indexed | 2024-04-12T10:41:11Z |
| publishDate | 2012-12-01 |
| publisher | Mustansiriyah University/College of Engineering |
| record_format | Article |
| series | Journal of Engineering and Sustainable Development |
| spelling | doaj.art-28fb7bf52cb84a24a4193609eab4aebf2022-12-22T03:36:35ZaraMustansiriyah University/College of EngineeringJournal of Engineering and Sustainable Development2520-09172520-09252012-12-01164Face Recognition under Illumination Changes Using Color Fast and Adaptive Bi-Directional Empirical Mode DecompositionHusam J. Naeemah0Electrical Engineering Department, Al-Mustansiriyah University, Baghdad, Iraq Recently, the importance of face recognition in color images has been increasingly emphasized since popular CCD cameras are distributed to various applications. However, face feature extracted from the image will distorted non-linearly by lighting variations in intensity or directions, so this changes will cause a serious performance degradation in face recognition. Many algorithms adopted by researchers to overcome the illumination problem. Most of them need multiple registered images per person or the prior knowledge of lighting conditions. According to the “common assumption” that illumination varies slowly and the face intrinsic feature (including 3D surface and reflectance) varies rapidly in local area, high frequency feature represents the face intrinsic structure. The Fast and Adaptive Bi-dimensional Empirical Mode Decomposition FABEMD has been extended for color image analysis. The proposed algorithm, based on the powerful transform for the color image named color FABEMD (CFABEMD). The color image decomposed into multi-layer high frequency images representing detail feature and low frequency images representing analogy feature. In addition a two measurements are proposed to quantify the detail feature that use to eliminate illumination variation, with these measurement weights, CFABEMD based multi-layer detail images recognition can be done under vary illumination. https://jeasd.uomustansiriyah.edu.iq/index.php/jeasd/article/view/1243illumination invariantBEMDCFABEMDface recognition |
| spellingShingle | Husam J. Naeemah Face Recognition under Illumination Changes Using Color Fast and Adaptive Bi-Directional Empirical Mode Decomposition Journal of Engineering and Sustainable Development illumination invariant BEMD CFABEMD face recognition |
| title | Face Recognition under Illumination Changes Using Color Fast and Adaptive Bi-Directional Empirical Mode Decomposition |
| title_full | Face Recognition under Illumination Changes Using Color Fast and Adaptive Bi-Directional Empirical Mode Decomposition |
| title_fullStr | Face Recognition under Illumination Changes Using Color Fast and Adaptive Bi-Directional Empirical Mode Decomposition |
| title_full_unstemmed | Face Recognition under Illumination Changes Using Color Fast and Adaptive Bi-Directional Empirical Mode Decomposition |
| title_short | Face Recognition under Illumination Changes Using Color Fast and Adaptive Bi-Directional Empirical Mode Decomposition |
| title_sort | face recognition under illumination changes using color fast and adaptive bi directional empirical mode decomposition |
| topic | illumination invariant BEMD CFABEMD face recognition |
| url | https://jeasd.uomustansiriyah.edu.iq/index.php/jeasd/article/view/1243 |
| work_keys_str_mv | AT husamjnaeemah facerecognitionunderilluminationchangesusingcolorfastandadaptivebidirectionalempiricalmodedecomposition |