PCA Based Image Fusion for Multispectral Palm Enhancement

Image fusion is performed by combining the data from the multiple spectrums i.e. red, blue, NIR and green, results in enhanced image. Each spectral band has specific features of the palm that collect more information to improve the accuracy and anti-spoofing capability of palm print systems. Principal component analysis (PCA) are used for image fusion line like pattern are most discriminative features in both visible and infrared hand images (principal lines and wrinkles for visible image and blood vessel for infrared image),Enhancing the image using image fusion technique to extract the correlative and complementary information of multispectral palm images Principal Component Analysis (PCA) algorithm builds a fused image of several input palmprints as a weighted superposition of all input images. The resulting image contains enhanced information with improved resolution as compared to individual images. For this evaluation we have calculated quality metrics SSIM,MI, QI, Edge based parameter etc.