Wavelet Transform based Score Fusion for Face Recognition using SIFT Descriptors

Authors

  • Musa M. Ameen Computer Engineering Dept., Ishik University, Erbil, Iraq
  • Bilal Ahmed Information Technologies Dept., Ishik University, Erbil, Iraq
  • Muhammed Anwar Information Technologies Dept., Ishik University, Erbil, Iraq
  • Payam M. Hussein Information Technologies Dept., Ishik University, Erbil, Iraq

DOI:

https://doi.org/10.23918/eajse.v2i2p48

Keywords:

SIFT, Face Recognition, Wavelet Transform, DWT, GWT, Score Fusion

Abstract

One of the main areas in computer vision is automatic face recognition which deals with detecting human face autonomously. Developments and the progress in the field of face recognition have shown that many face recognition systems and applications the automated methods outperform humans. The conventional Scale-Invariant Feature Transform (SIFT) is used in face recognition where they provide high performances. However, this performance can be improved further by transforming the input into different domains before applying SIFT algorithm. Hence, we apply Discrete Wavelet Transform (DWT) or Gabor Wavelet Transform (GWT) at the input face images, which provides denser and extra information to be used by the conventional SIFT algorithm. Matching scores of SIFT from each subimage is fused before making final decision. Simulations show that the proposed approaches based on wavelet transforms using SIFT provides very high performance compared to the conventional algorithm.

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Published

2017-06-01

Issue

Section

Articles

How to Cite

Ameen, M. M., Ahmed, B., Anwar, M., & Hussein, P. M. (2017). Wavelet Transform based Score Fusion for Face Recognition using SIFT Descriptors. EURASIAN JOURNAL OF SCIENCE AND ENGINEERING, 2(2), 48-55. https://doi.org/10.23918/eajse.v2i2p48

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