Robust Face Recognition Technique under Varying Illumination
Face recognition is one of a complex biometrics in the field of pattern recognition due to the constraints imposed by variation in the appearance of facial images. These changes in appearance are affected by variation in illumination, expression or occlusions etc. Illumination can be considered a complex problem in both indoor and outdoor pattern matching. Literature studies have revealed that two problems of textural based illumination handling in face recognition seem to be very common. Firstly, textural values are changed during illumination normalization due to increase in the contrast that changes the original pixels of face. Secondly, it minimizes the distance between interclasses which increases the false acceptance rates. This paper addresses these issues and proposes a robust algorithm that overcomes these limitations. The limitations are resolved through transforming pixels from nonillumination side to illuminated side. It has been revealed that proposed algorithm produced better results as compared to existing related algorithms.
| Main Authors: | , , , , |
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| Format: | Digital revista |
| Language: | English |
| Published: |
Universidad Nacional Autónoma de México, Instituto de Ciencias Aplicadas y Tecnología
2015
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| Online Access: | http://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S1665-64232015000100009 |
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| Summary: | Face recognition is one of a complex biometrics in the field of pattern recognition due to the constraints imposed by variation in the appearance of facial images. These changes in appearance are affected by variation in illumination, expression or occlusions etc. Illumination can be considered a complex problem in both indoor and outdoor pattern matching. Literature studies have revealed that two problems of textural based illumination handling in face recognition seem to be very common. Firstly, textural values are changed during illumination normalization due to increase in the contrast that changes the original pixels of face. Secondly, it minimizes the distance between interclasses which increases the false acceptance rates. This paper addresses these issues and proposes a robust algorithm that overcomes these limitations. The limitations are resolved through transforming pixels from nonillumination side to illuminated side. It has been revealed that proposed algorithm produced better results as compared to existing related algorithms. |
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