The Implementation of A Fingerprint Enhancement System Based on GPU via CUDA

The Implementation of A Fingerprint Enhancement System Based on GPU via CUDA

In order to reduce the large execution time of an existing fingerprint enhancement system, a parallel implementation method based on GPU via CUDA is proposed. Firstly, the necessity and feasibility of employing parallel programming for the whole system are analyzed. Then pre-processing, global analy...

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Bibliographic Details
Main Authors: Yang, Kaiyuan, Wang, Fuliang
Format: Others
Language:English
Published: Blekinge Tekniska Högskola, Institutionen för tillämpad signalbehandling 2017
Subjects:
Adaptive Fingerprint Enhancement
CUDA
Parallel Programming
GPU Programming
Signal Processing
Signalbehandling
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:bth-15092
Description
Summary:In order to reduce the large execution time of an existing fingerprint enhancement system, a parallel implementation method based on GPU via CUDA is proposed. Firstly, the necessity and feasibility of employing parallel programming for the whole system are analyzed. Then pre-processing, global analysis, local analysis and matched filtering of the whole fingerprint enhancement system is designed, optimized and implemented respectively using parallel computing technology via CUDA. Finally, numerous fingerprints from FVC2000 databases are tested and the  obtained execution time is compared with that of the CPU based system. The results show that the execution time is significantly reduced by using the parallel implementation method based on GPU. 

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