A New Hybrid Face Recognition System via Local Gradient Probabilistic Pattern (LGPP) and 2D-DWT
| Autor: | Abdellatif Dahmouni, Karim El Moutaouakil, Nabil Aharrane, Khalid Satori |
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| Rok vydání: | 2016 |
| Předmět: |
business.industry
Computer science Probabilistic logic Bayesian network 020206 networking & telecommunications Pattern recognition 02 engineering and technology Facial recognition system Confidence interval Field (computer science) Support vector machine Homogeneous 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence business |
| Zdroj: | Advances in Intelligent Systems and Computing ISBN: 9783319465678 |
| DOI: | 10.1007/978-3-319-46568-5_28 |
| Popis: | In last years, the facial biometry is coming back into education field; it is proposed to control student activities. In this paper, we propose a new face recognition system based on our Local Gradient Probabilistic Pattern (LGPP) and 2D-DWT. Firstly, the almost homogeneous and the picks areas are separate according to LGPP confidence interval. Secondly, the obtained images are decomposed using 2D-DWT in “LL, LH, HL and HH” sub-bands. Thereafter, we extract the features vector using 2D-PCA method applied on the approximation (LL-band). In classification phase, we compare between MLP, Bayesian Networks, SVM and KNN classifiers at features vector. The experimental results show that proposed system improves the recognition rate. Indeed, we reach a rate of 97 % for ORL and 98.8 % for Yale. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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