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Journal of Software Engineering
  Year: 2014 | Volume: 8 | Issue: 3 | Page No.: 211-218
DOI: 10.3923/jse.2014.211.218
Feature Extraction by Wavelet and Gabor Transform with MMC for a Single Training Sample
Senhai Zhong, Liejun Wang and Li Zhang

Abstract:
Face feature extraction is a key technology for face recognition. A new framework of feature extraction is proposed in this study. Use wavelet and Gabor transformation with maximum margin criterion to extract face features for a single training sample. The less data of face features make it possible to transmit those data to servers as quickly as possible. The results conducted on ORL database show that the proposed method improves the performance, simultaneously obtains less data to transmit.
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How to cite this article:

Senhai Zhong, Liejun Wang and Li Zhang, 2014. Feature Extraction by Wavelet and Gabor Transform with MMC for a Single Training Sample. Journal of Software Engineering, 8: 211-218.

DOI: 10.3923/jse.2014.211.218

URL: http://scialert.net/abstract/?doi=jse.2014.211.218

 
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