Implementing Machine Vision Systems Using FPGAs

Reference work entry

Abstract

Field programmable gate arrays (FPGAs) offer a convenient and flexible platform on which real-time machine vision systems may be implemented. This chapter discusses how FPGA based design differs from conventional software design for implementing image processing algorithms. Simply porting from software to hardware can give disappointing results. The process of transforming an algorithm for mapping it onto an FPGA is described in some detail, illustrating how a range of low-level image processing operations may be efficiently implemented. Systems integration issues such as interfacing, debugging and tuning are also discussed.

Keywords

Clock Cycle Field Programmable Gate Array Machine Vision System Hardware Description Language Frame Buffer 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Notes

Acknowledgements

I would like to acknowledge my research students (David Johnson, Kim Gribbon, Chris Johnston, Aaron Bishell, Andreas Buhler, and Ni Ma) who helped shape my thinking as we struggled together to work out efficient ways of implementing image processing algorithms.

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Copyright information

© Springer-Verlag London Ltd. 2012

Authors and Affiliations

  1. 1.School of Engineering and Advanced TechnologyMassey UniversityPalmerston NorthNew Zealand

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