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Generic FPGA Pre-Processing Image Library for Industrial Vision Systems

Sensors, ISSN: 1424-8220, Vol: 24, Issue: 18
2024
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    Citations
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    Usage
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    Captures
  • 2
    Mentions
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    Social Media
Metric Options:   Counts1 Year3 Year

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  • Mentions
    2
    • Blog Mentions
      1
      • Blog
        1
    • News Mentions
      1
      • News
        1

Most Recent Blog

Sensors, Vol. 24, Pages 6101: Generic FPGA Pre-Processing Image Library for Industrial Vision Systems

Sensors, Vol. 24, Pages 6101: Generic FPGA Pre-Processing Image Library for Industrial Vision Systems Sensors doi: 10.3390/s24186101 Authors: Diogo Ferreira Filipe Moutinho  João P. Matos-Carvalho 

Most Recent News

Study Results from NOVA University Lisbon Update Understanding of Sensor Research (Generic FPGA Pre-Processing Image Library for Industrial Vision Systems)

2024 OCT 11 (NewsRx) -- By a News Reporter-Staff News Editor at Tech Daily News -- Research findings on sensor research are discussed in a

Article Description

Currently, there is a demand for an increase in the diversity and quality of new products reaching the consumer market. This fact imposes new challenges for different industrial sectors, including processes that integrate machine vision. Hardware acceleration and improvements in processing efficiency are becoming crucial for vision-based algorithms to follow the complexity growth of future industrial systems. This article presents a generic library of pre-processing filters for execution in field-programmable gate arrays (FPGAs) to reduce the overall image processing time in vision systems. An experimental setup based on the Zybo Z7 Pcam 5C Demo project was developed and used to validate the filters described in VHDL (VHSIC hardware description language). Finally, a comparison of the execution times using GPU and CPU platforms was performed as well as an evaluation of the integration of the current work in an industrial application. The results showed a decrease in the pre-processing time from milliseconds to nanoseconds when using FPGAs.

Bibliographic Details

Diogo Ferreira; Magno Guedes ; Pedro Deusdado ; Filipe Moutinho ; João P. Matos-Carvalho 

MDPI AG

Chemistry; Computer Science; Physics and Astronomy; Biochemistry, Genetics and Molecular Biology; Engineering

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