Bayesian Robust Coding Face Recognition Algorithm Based on New Dictionary
| Autor: | Ye Cai Guo, Ling Hua Zhang |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
Standard test image
Computer science business.industry Binary image Bayesian probability ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition General Medicine Facial recognition system Image (mathematics) Transformation (function) Face (geometry) Artificial intelligence business Algorithm Smoothing |
| Zdroj: | Applied Mechanics and Materials. :4080-4083 |
| ISSN: | 1662-7482 |
| DOI: | 10.4028/www.scientific.net/amm.644-650.4080 |
| Popis: | In order to overcome the defects that the face recognition rate can be greatly reduced in the existing uncontrolled environments, Bayesian robust coding for face recognition based on new dictionary was proposed. In this proposed algorithm, firstly a binary image is gained by gray threshold transformation and a more clear image without some isolated points can be obtained via smoothing, secondly a new dictionary can be reconstructed via fusing the binary image with the original training dictionary, finally the test image can be classified as the existing class via Bayesian robust coding. The experimental results based on AR face database show that the proposed algorithm has higher face recognition rate comparison with RRC and RSC algorithm. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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