Recognition of Reconstructed Frontal Face Images Using FFT-PCA/SVD Algorithm

Recognition of Reconstructed Frontal Face Images Using FFT-PCA/SVD Algorithm

Blog Article

Face recognition has gained prominence among the various biometric-based methods (such as fingerprint and iris) due to its noninvasive characteristics.Modern face recognition modules/algorithms have been successful in many application areas (access control, entertainment/leisure, security system based on biometric data, and user-friendly human-machine interfaces).In spite of these achievements, the performance of current face recognition algorithms/modules is still inhibited by varying environmental constraints such as occlusions, EXTRA C 500 MG expressions, varying poses, illumination, and ageing.This study assessed the performance of Principal Component Analysis with singular value decomposition using Fast Fourier Transform (FFT-PCA/SVD) for preprocessing the face recognition algorithm on left Portable Ranges and right reconstructed face images.

The study found that average recognition rates for the FFT-PCA/SVD algorithm were 95% and 90% when the left and right reconstructed face images are used as test images, respectively.The result of the paired sample t-test revealed that the average recognition distances for the left and right reconstructed face images are not significantly different when FFT-PCA/SVD is used for recognition.FFT-PCA/SVD is recommended as a viable algorithm for recognition of left and right reconstructed face images.