In this study, the authors propose an efficient embedded processing architecture that uses the vascular pattern extraction (VPE) algorithm to authenticate a user to an embedded system. This study first considers the use of direction-based vascular pattern extraction (DBVPE), and analyses the computational workload involved in running software implementations on an embedded processor. The authors then present a comprehensive performance analysis of the VPE algorithm and examine in detail the various factors that contribute to processing latencies, including VPE recognition processing. In order to improve the efficiency of VPE processing in embedded devices, the authors offer details regarding the process needed to create a highly efficient application-specific processor and extend the base instruction set of the processor by using custom instructions for recognition processing. The authors implemented our proposed methodology in the context of a commercial extensible processor design flow using the Xtensa platform from Tensilica Inc. Our experiments show that our proposed methodology achieves a 3.95-fold increase in the vascular pattern recognition speed. Hence, the authors consider our technique to be efficient.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.