Wavelet Transform based Score Fusion for Face Recognition using SIFT Descriptors

Authors : Musa M.Ameen & Bilal Ahmed & Muhammed Anwar & Payam M.Hussein

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.

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

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doi: 10.23918/eajse.v2i2p48