Abstract:
This Paper proposes a new facial feature extraction
approach, Wash-Hadamard Transform (WHT). This approach is
based on correlation between local pixels of the face image. Its
primary advantage is the simplicity of its computation.
The paper compares the proposed approach, WHT, which was
traditionally used in data compression with two other known
approaches: the Principal Component Analysis (PCA) and the
Discrete Cosine Transform (DCT) using the face database of Olivetti
Research Laboratory (ORL). In spite of its simple computation, the
proposed algorithm (WHT) gave very close results to those obtained
by the PCA and DCT.
This paper initiates the research into WHT and the family of
frequency transforms and examines their suitability for feature
extraction in face recognition applications.
