AN ILLUMINATION INVARIANT TEXTURE BASED FACE RECOGNITION
Automatic face recognition remains an interesting but challenging computer vision open problem. Poor illumination is considered as one of the major issue, since illumination changes cause large variation in the facial features. To resolve this, illumination normalization preprocessing techniques are...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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ICT Academy of Tamil Nadu
2013-11-01
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| Series: | ICTACT Journal on Image and Video Processing |
| Subjects: | |
| Online Access: | http://ictactjournals.in/paper/V4_I2_Paper_6_709_716_online.pdf |
| _version_ | 1818289438789206016 |
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| author | K. Meena A. Suruliandi R. Reena Rose |
| author_facet | K. Meena A. Suruliandi R. Reena Rose |
| author_sort | K. Meena |
| collection | DOAJ |
| description | Automatic face recognition remains an interesting but challenging computer vision open problem. Poor illumination is considered as one of the major issue, since illumination changes cause large variation in the facial features. To resolve this, illumination normalization preprocessing techniques are employed in this paper to enhance the face recognition rate. The methods such as Histogram Equalization (HE), Gamma Intensity Correction (GIC), Normalization chain and Modified Homomorphic Filtering (MHF) are used for preprocessing. Owing to great success, the texture features are commonly used for face recognition. But these features are severely affected by lighting changes. Hence texture based models Local Binary Pattern (LBP), Local Derivative Pattern (LDP), Local Texture Pattern (LTP) and Local Tetra Patterns (LTrPs) are experimented under different lighting conditions. In this paper, illumination invariant face recognition technique is developed based on the fusion of illumination preprocessing with local texture descriptors. The performance has been evaluated using YALE B and CMU-PIE databases containing more than 1500 images. The results demonstrate that MHF based normalization gives significant improvement in recognition rate for the face images with large illumination conditions. |
| first_indexed | 2024-12-13T02:12:17Z |
| format | Article |
| id | doaj.art-b0aa6275176747a789e2f7473c3b3475 |
| institution | Directory Open Access Journal |
| issn | 0976-9099 0976-9102 |
| language | English |
| last_indexed | 2024-12-13T02:12:17Z |
| publishDate | 2013-11-01 |
| publisher | ICT Academy of Tamil Nadu |
| record_format | Article |
| series | ICTACT Journal on Image and Video Processing |
| spelling | doaj.art-b0aa6275176747a789e2f7473c3b34752022-12-22T00:02:59ZengICT Academy of Tamil NaduICTACT Journal on Image and Video Processing0976-90990976-91022013-11-0142709716AN ILLUMINATION INVARIANT TEXTURE BASED FACE RECOGNITIONK. Meena0A. Suruliandi1R. Reena Rose2Department of Electronics and Communication Engineering, J. P. College of Engineering, IndiaDepartment of Computer Science and Engineering, Manonmaniam Sundaranar University, IndiaDepartment of Computer Applications, St. Xavier’s Catholic College of Engineering, IndiaAutomatic face recognition remains an interesting but challenging computer vision open problem. Poor illumination is considered as one of the major issue, since illumination changes cause large variation in the facial features. To resolve this, illumination normalization preprocessing techniques are employed in this paper to enhance the face recognition rate. The methods such as Histogram Equalization (HE), Gamma Intensity Correction (GIC), Normalization chain and Modified Homomorphic Filtering (MHF) are used for preprocessing. Owing to great success, the texture features are commonly used for face recognition. But these features are severely affected by lighting changes. Hence texture based models Local Binary Pattern (LBP), Local Derivative Pattern (LDP), Local Texture Pattern (LTP) and Local Tetra Patterns (LTrPs) are experimented under different lighting conditions. In this paper, illumination invariant face recognition technique is developed based on the fusion of illumination preprocessing with local texture descriptors. The performance has been evaluated using YALE B and CMU-PIE databases containing more than 1500 images. The results demonstrate that MHF based normalization gives significant improvement in recognition rate for the face images with large illumination conditions.http://ictactjournals.in/paper/V4_I2_Paper_6_709_716_online.pdfFace RecognitionTexture AnalysisTexture Features |
| spellingShingle | K. Meena A. Suruliandi R. Reena Rose AN ILLUMINATION INVARIANT TEXTURE BASED FACE RECOGNITION ICTACT Journal on Image and Video Processing Face Recognition Texture Analysis Texture Features |
| title | AN ILLUMINATION INVARIANT TEXTURE BASED FACE RECOGNITION |
| title_full | AN ILLUMINATION INVARIANT TEXTURE BASED FACE RECOGNITION |
| title_fullStr | AN ILLUMINATION INVARIANT TEXTURE BASED FACE RECOGNITION |
| title_full_unstemmed | AN ILLUMINATION INVARIANT TEXTURE BASED FACE RECOGNITION |
| title_short | AN ILLUMINATION INVARIANT TEXTURE BASED FACE RECOGNITION |
| title_sort | illumination invariant texture based face recognition |
| topic | Face Recognition Texture Analysis Texture Features |
| url | http://ictactjournals.in/paper/V4_I2_Paper_6_709_716_online.pdf |
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