  In the domain of Biometrics, recognition systems based on iris, fingerprint
or palm print scans etc. are often considered more dependable due to extremely
low variance in the properties of these entities with respect to time. However,
over the last decade data processing capability of computers has increased
manifold, which has made real-time video content analysis possible. This shows
that the need of the hour is a robust and highly automated Face Detection and
Recognition algorithm with credible accuracy rate. The proposed Face Detection
and Recognition system using Discrete Wavelet Transform (DWT) accepts face
frames as input from a database containing images from low cost devices such as
VGA cameras, webcams or even CCTV's, where image quality is inferior. Face
region is then detected using properties of L*a*b* color space and only Frontal
Face is extracted such that all additional background is eliminated. Further,
this extracted image is converted to grayscale and its dimensions are resized
to 128 x 128 pixels. DWT is then applied to entire image to obtain the
coefficients. Recognition is carried out by comparison of the DWT coefficients
belonging to the test image with those of the registered reference image. On
comparison, Euclidean distance classifier is deployed to validate the test
image from the database. Accuracy for various levels of DWT Decomposition is
obtained and hence, compared.
