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  • 标题:Design of Face Recognition System by Using Neural Network with Discrete Cosine Transform and Principal Component Analysis
  • 本地全文:下载
  • 作者:Rohit Jain ; Rajshree Taparia
  • 期刊名称:International Journal of Advanced Computer Research
  • 印刷版ISSN:2249-7277
  • 电子版ISSN:2277-7970
  • 出版年度:2012
  • 卷号:2
  • 期号:7
  • 页码:66-69
  • 出版社:Association of Computer Communication Education for National Triumph (ACCENT)
  • 摘要:This research paper deals with the implementation of face recognition system using neural network Importance of face recognition system has speed up in the last few decades. A face recognition system is one of the biometric information processing. The developed algorithm for the face recognition system formulates an image-based approach, which uses the Two-Dimensional Discrete Cosine Transform (2D-DCT) for image compression and the Self- Organizing Map (SOM) Neural Network for recognition purpose, simulated in MATLAB. By using 2D-DCT we extract image vectors and these vectors becomes the input to neural network classifier, which uses self-organizing map, algorithm to recognize familiar faces (trained) and faces with variations in expressions, illumination changes, tilt of 5 to 10 degrees. Again face Recognition system is developed with principal component analysis (PCA) instead of Two Dimensional Discrete Cosine Transform (2D-DCT) and self-Organizing Map (SOM) Neural Network for recognition purpose. The crux of proposed algorithm is its beauty to use unsupervised single neural network as classifier.
  • 关键词:Artificial Neural Network; Self-Organizing map; Two dimensional discrete cosine transform; Principal component analysis; unsupervised.
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