Comparing an FPGA to a Cell for an Image Processing Application

Modern advancements in configurable hardware, most notably Field-Programmable Gate Arrays (FPGAs), have provided an exciting opportunity to discover the parallel nature of modern image processing algorithms. On the other hand, PlayStation3 (PS3) game consoles contain a multicore heterogeneous processor known as the Cell, which is designed to perform complex image processing algorithms at a high performance. In this research project, our aim is to study the differences in performance of a modern image processing algorithm on these two hardware platforms. In particular, Iris Recognition Systems have recently become an attractive identification method because of their extremely high accuracy. Iris matching, a repeatedly executed portion of a modern iris recognition algorithm, is parallelized on an FPGA system and a Cell processor. We demonstrate a 2.5 times speedup of the parallelized algorithm on the FPGA system when compared to a Cell processor-based version.

[1]  John Daugman,et al.  How iris recognition works , 2002, IEEE Transactions on Circuits and Systems for Video Technology.

[2]  Martin Hopkins,et al.  Synergistic Processing in Cell's Multicore Architecture , 2006, IEEE Micro.

[3]  Libor Masek,et al.  Recognition of Human Iris Patterns for Biometric Identification , 2003 .

[4]  John Daugman,et al.  Probing the Uniqueness and Randomness of IrisCodes: Results From 200 Billion Iris Pair Comparisons , 2006, Proceedings of the IEEE.

[5]  Robert W. Ives,et al.  Binary Morphology and Local Statistics Applied to Iris Segmentation for Recognition , 2006, 2006 International Conference on Image Processing.

[6]  John Daugman,et al.  Statistical Richness of Visual Phase Information: Update on Recognizing Persons by Iris Patterns , 2001, International Journal of Computer Vision.

[7]  Gaurav Gupta,et al.  Iris Recognition Using Non Filter-based Technique , 2005 .

[8]  Deepthi Rampally,et al.  Iris recognition based on feature extraction , 2010 .

[9]  R.W. Ives,et al.  Accelerating Iris Template Matching using Commodity Video Graphics Adapters , 2008, 2008 IEEE Second International Conference on Biometrics: Theory, Applications and Systems.

[10]  R.W. Ives,et al.  Iris recognition using the Ridge Energy Direction (RED) algorithm , 2008, 2008 42nd Asilomar Conference on Signals, Systems and Computers.

[11]  Randy P. Broussard,et al.  Identifying discriminatory information content within the iris , 2008, SPIE Defense + Commercial Sensing.

[12]  Nick Knupffer Intel Corporation , 2018, The Grants Register 2019.

[13]  Anil K. Jain,et al.  Localized Iris Image Quality Using 2-D Wavelets , 2006, ICB.

[14]  Mark J. T. Smith,et al.  Iris-Based Personal Authentication Using a Normalized Directional Energy Feature , 2003, AVBPA.