Face and fingerprint recognition on field programmable gate array

The aim of this study is to implement a face and fingerprint recognition system on field programmable gate array (FPGA).In the research stage of this thesis, biometric recognition which refers to use of distinctive physiological and behavioral characteristics for automatically recognizing a person were observed to constitute a face and fingerprint recognition system. FPGA configuration and programming methods were also investigated to design the hardware and the software of the recognition systems.The recognition systems that are proposed in this thesis have two working phases. In the offline training phase, face and fingerprint images are collected by MATLAB. Then, this database is sent to FPGA to extract features. Principal Component Analysis (PCA) is the feature extraction algorithm that is used in this study. After all features of face and fingerprint images are extracted, the features are stored on the memory of FPGA. In the online test phase or recognition phase, the features of test images are extracted then these are compared to restored values of the database from the memory of FPGA. The result of comparison is then displayed. This thesis also proposes a multibiometric recognition system which is constituted from face and fingerprint recognition systems by using the fusion at the decision level.