Generalized Net Model of Person Recognition Using ART2 Neural Network and Viola-Jones Algorithm

In this paper we present a method for the purpose to detect a certain person in an image. We use the tools of neural networks and face recognition algorithm to achieve our goal. The type of neural network is unsupervised adaptive resonance theory 2 (ART2). It is trained by the set of person images and divided into two clusters—the first cluster represents the human who has to be found and the second one represents the other people. The algorithm which is used for face detection is Viola-Jones and the combination with neural networks helps to identify the person. The generalized net model is used to describe the recognition process.

[1]  Amar Djeradi,et al.  Face recognition system using neural network with Gabor and discrete wavelet transform parameterization , 2014, 2014 6th International Conference of Soft Computing and Pattern Recognition (SoCPaR).

[2]  Oliver Kramer,et al.  Dimensionality Reduction with Unsupervised Nearest Neighbors , 2013, Intelligent Systems Reference Library.

[3]  Paul A. Viola,et al.  Robust Real-Time Face Detection , 2001, International Journal of Computer Vision.

[4]  Stephen Grossberg,et al.  The ART of adaptive pattern recognition by a self-organizing neural network , 1988, Computer.

[5]  Martin T. Hagan,et al.  Neural network design , 1995 .

[6]  Y. H. Liu,et al.  DYNAMIC CLUSTERING ALGORITHM BASED ON ADAPTIVE RESONANCE THEORY , 2006 .

[7]  Marek R. Ogiela,et al.  Biometric watermarks based on face recognition methods for authentication of digital images , 2015, Secur. Commun. Networks.

[8]  N. A. Zainuddin,et al.  Analysis of Artificial Neural Network and Viola-Jones Algorithm Based Moving Object Detection , 2014, 2014 International Conference on Computer and Communication Engineering.

[9]  Ryan N. Rakvic,et al.  A Viola-Jones based hybrid face detection framework , 2013, Electronic Imaging.