전기학회논문지 (The Transactions of The Korean Institute of Electrical Engineers)

  • 제65권4호
  • /
  • Pages.666-672
  • /
  • 2016
  • /
  • 1975-8359(pISSN)
  • /
  • 2287-4364(eISSN)
대한전기학회 (The Korean Institute of Electrical Engineers)
권호 표지
DOI QR코드

DOI QR Code

OpenCL을 이용한 GPGPU 기반 지문개선 알고리즘 가속화

Accelerating Fingerprint Enhancement Algorithm on GPGPU using OpenCL

  • Kim, Daehee (Dept. of Computer Science and Engineering, Konkuk University) ;
  • Park, Neungsoo (Dept. of Computer Science and Engineering, Konkuk University)
  • 투고 : 2016.02.19
  • 심사 : 2016.03.05
  • 발행 : 2016.04.01
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

Recently the fingerprint is widely used as one of biometrics to improve the security of financial mobile applications, because of its user convenience and high recognition rate. However, in order to apply fingerprint algorithms to finance and security applications, the recognition rate and processing speed of the fingerprint algorithms have to be improved further. In this paper, we propose the parallel fingerprint enhancement algorithm on general-purpose computing on graphics processing unit (GPGPU) using OpenCL. We discuss the analysis of the parallelism in the fingerprint algorithm as well as the exploration of optimization parameters of the parallel fingerprint algorithm to improve the performance. The experimental results showed that the execution of parallel fingerprint enhancement algorithm on GPGPUs was accelerated from 29.4 upto 69.2 times compared with the execution of the original one on the host CPUs.

키워드

참고문헌

  1. Lin Hong, Anil Jain, Sharathcha Pankanti, and Ruud Bolle, Automatic Fingerprint Recognition Systems, Springer, pp. 127-143, 2004.
  2. Francisco Fons, Mariano Fons, and Enrique Canto, "Approaching fingerprint image enhancement through reconfigurable hardware accelerators," In proceedings of 1st Workshop on Intelligent Signal Processing(WISP 2007), pp. 1-6, 2007.
  3. Raja Lehtihet, Wael El Oraiby, and Mohammed Benmohammed, "Fingerprint grid enhancement on GPU," In proceedings of 20th the International Conference on Image Processing, Computer Vision, and Pattern Recognition(IPCV 2013), pp. 1, 2013.
  4. Chirag Agarwal, Akhtar Rasool, and Nilay Khare, "PFAC Implementation Issues and their Solutions on GPGPU's using OpenCL," The International Journal of Computer Applications, Vol. 72, No. 7, pp. 52-58, 2013. https://doi.org/10.5120/12510-9161
  5. Jeonghyeon Ma, Sejin Park, and Chanik Park, "Parallel Rabin Fingerprinting on GPGPU for Efficiemt Data Deduplication," The Journal of Korean Institute of Information Scientists and Engineers, Vol. 41, No. 9, pp. 611-616, 2014.
  6. G. T. Candela, P. J. Grother, C. I. Watson, R. A. Wilkinson, and C. L. Wilson, "PCASYS-A pattern-level classification automation system for fingerprints," Technical Report NISTIR-5647, NIST, August 1995.
  7. Craig I. Watson, Michael D. Garris, Elham Tabassi, Charles L. Wilson, R. Michael McCabe, Stanley Janet, and Kenneth Ko, "User's guide to NIST biometric image software (NBIS)", Technical Report NISTIR-7392, NIST, January 2007.
  8. Lee Howes and Aaftab Munshi, "The OpenCL Specification version 2.0", Khronos OpenCL Working Group, October 2015. https://www.khronos.org/registry/cl/specs/opencl-2.0.pdf
  9. NIST Special Database 27a, http://www.nist.gov/itl/iad/ig/sd27a.cfm