Face recognition

List of Articles Face recognition

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1 - A Novel Proposed Algorithm to Tackle Glasses Wearing and Beard Issues in Facial IR Recognition
H. Komari Alaie M. Khademi
20.1001.1.16823745.1390.9.1.1.8

Face recognition via thermal infrared images is a modern recognition method. It has been so interesting for many researchers during last ten years. This method which operates via thermal features and the situation of human face vessels has much more benefits than visual More

Face recognition via thermal infrared images is a modern recognition method. It has been so interesting for many researchers during last ten years. This method which operates via thermal features and the situation of human face vessels has much more benefits than visual-based methods. In these images, the effect of environmental lights changes, which is one of the most important obstacles of face recognition via visual images, is totally eliminated. The most important face recognition problem via thermal infrared images is the existence of diffusion obstacles like glasses and beard, which block the exact extraction of the situation of face vessels. Considering the suggested algorithm, these problems have been completely solved. In this paper face recognition is done through face vessels. For extraction of the face features, the situation of vessel branches is used. Also by choosing appropriate classification, fake vessels and false branches has been omitted. On the other hand, the best feature is extracted by using Dynamic Time Wrapping algorithm which is resistant to nonlinear changes. The simulation on UTK-IRIS gallery set has showed the accurate recognition rate 95% on the images with glasses and 88% on the images with beard, so the proposed method has improved the recognition rate about 10% and 44% respectively on same gallery set compared with the best other works. Manuscript profile
Open Access Article
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2 - Improving Pose Manifold and Virtual Images Using Bidirectional Neural Networks in Face Recognition Using Single Image per Person
F. Abdolali S. A. Seyed Salehi
20.1001.1.16823745.1390.9.1.2.9

In this article, for the purpose of improving neural network models applied in face recognition using single image per person, a bidirectional neural network inspired of neocortex functional model is presented. In the proposed model, recognition is not performed in a si More

In this article, for the purpose of improving neural network models applied in face recognition using single image per person, a bidirectional neural network inspired of neocortex functional model is presented. In the proposed model, recognition is not performed in a single stage, but via two bottom-up and top-down phases and the recognition results of first stage is used for model adaptation. We have applied this novel adapting model in combination with clustering person and pose information technique to separate person and pose information and to estimate corresponding manifolds. To increase the number of training samples in the classifier neural network, virtual views of frontal images in the test dataset are synthesized using estimated manifolds. Training classifier network via virtual images obtained from bidirectional network, gives an accuracy rate of 85.45% on the test dataset which shows 1.82% improvement in accuracy of face recognition compared to training classifier with virtual images obtained from clustering person and pose information network. Manuscript profile
Open Access Article
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3 - Providing a Face Recognition System with an Optimal Selection of Features Based on the Cuckoo Optimization Algorithm
Farnaz Hoseini Hamed Sepehrzadeh

Face recognition is a pattern recognition process that is specifically performed on faces. Face recognition has many applications in identifying credit cards, security systems, and other cases. Creating a face recognition system with high accuracy is a big challenge tha More

Face recognition is a pattern recognition process that is specifically performed on faces. Face recognition has many applications in identifying credit cards, security systems, and other cases. Creating a face recognition system with high accuracy is a big challenge that has been the focus of various researchers in recent years. The feature extraction process and classification are two important issues in diagnosis systems that can play a significant role in increasing the accuracy of diagnosis. Considering this issue, in this study, taking into account the combined features and optimizing the cuckoo algorithm, a method to improve the accuracy of face recognition is proposed. In the presented method, seven features are extracted from the images in the database, and then by obtaining the feature vector, the steps related to feature selection are performed using the cuckoo algorithm. The proposed method has been implemented with MATLAB software and compared with other methods. The evaluation results show that the proposed method was able to perform the detection on the images of ORL and FDBB databases with 93.00% and 95.12% accuracy, respectively. The result obtained for this evaluation criterion has a higher value than other compared methods. Manuscript profile

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List of Articles Face recognition