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Examination of Speed Contribution of Parallelization for Several Fingerprint Pre-Processing AlgorithmsGORGUNOGLU, S. , ORAK, I. M. , CAVUSOGLU, A. , GOK, M.
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CUDA, fingerprint recognition, parallel processing, parallel programming, OpenMP
image(11), fingerprint(10), processing(6), algorithm(6), pattern(4), minutiae(4)
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About this article
Date of Publication: 2014-05-31
Volume 14, Issue 2, Year 2014, On page(s): 3 - 8
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2014.02001
Web of Science Accession Number: 000340868100001
SCOPUS ID: 84901844580
In analysis of minutiae based fingerprint systems, fingerprints needs to be pre-processed. The pre-processing is carried out to enhance the quality of the fingerprint and to obtain more accurate minutiae points. Reducing the pre-processing time is important for identification and verification in real time systems and especially for databases holding large fingerprints information. Parallel processing and parallel CPU computing can be considered as distribution of processes over multi core processor. This is done by using parallel programming techniques. Reducing the execution time is the main objective in parallel processing. In this study, pre-processing of minutiae based fingerprint system is implemented by parallel processing on multi core computers using OpenMP and on graphics processor using CUDA to improve execution time. The execution times and speedup ratios are compared with the one that of single core processor. The results show that by using parallel processing, execution time is substantially improved. The improvement ratios obtained for different pre-processing algorithms allowed us to make suggestions on the more suitable approaches for parallelization.
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 Optimizing the Forward Algorithm for Hidden Markov Model on IBM Roadrunner clusters, SOIMAN, S.-I., RUSU, I., PENTIUC, S.-G., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 2, Volume 15, 2015.
Digital Object Identifier: 10.4316/AECE.2015.02013 [CrossRef] [Full text]
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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