Cybernetics and Information Technologies (Jun 2018)

New Proposed Fusion between DCT for Feature Extraction and NSVC for Face Classification

  • Nassih B.,
  • Ngadi M.,
  • Amine A.,
  • El-Attar A.

DOI
https://doi.org/10.2478/cait-2018-0030
Journal volume & issue
Vol. 18, no. 2
pp. 89 – 97

Abstract

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Feature extraction is an interactive and iterative analysis process of a large dataset of raw data in order to extract meaningful knowledge. In this article, we present a strong descriptor based on the Discrete Cosine Transform (DCT), we show that the new DCT-based Neighboring Support Vector Classifier (DCT-NSVC) provides a better results compared to other algorithms for supervised classification. Experiments on our real dataset named BOSS, show that the accuracy of classification has reached 99%. The application of DCT-NSVC on MIT-CBCL dataset confirms the performance of the proposed approach.

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