Biometric is the science and technology of measuring and analyzing biological data of human body, extracting a feature set from the acquired data and comparing this set against the template set in the database. In this paper, Recognition through fusion of face and iris biometric images based on wavelet features and Kernel Fisher Discriminant Analysis (KFDA) is developed. Discrete Wavelet Transform (DWT) of face and iris image is used to reduce the dimensions which help to prevent from requirement of storage space of database. Nearest Neighbour classifier is selected to assign class to its nearest neighbour. Then, nonlinear original input space can be converted through a nonlinear map function into a linear high-dimensional feature space with the use of KFDA
