Abstract:
Face recognition is the second most important biometric part of the human
body, apart from the biometric nger print. Detecting and measuring half
face image processing or pattern recognition is a challenge in this eld. The
research made use of Discrete Wavelet Transform (DWT) as the preprocessing
mechanism and adopted the Principal Component Analysis and Singular
Value Decomposition (PCA/SVD) for feature extraction and recognition.
Numerical assessment of the performance of the adopted recognition algorithm
gave average recognition rates of 95% and 75% when left and right
reconstructed face images are used for recognition. Statistical analysis using
the Wilcoxon Sign Rank test shows that, there is no signi cant di erence in
the left and right reconstructed half face images when DWT-PCA/SVD is
used for recognition. In conclusion, DWT-PCA/SVD is therefore recommend
as one of the best noise viable algorithm for recognizing face images under
partial occlusion.
