Abstract
This paper presents FPGA implementations of image filtering and image averaging – two widely applied image preprocessing algorithms. The implementations are targeted for real time processing of high frame rate and high resolution image streams. The developed implementations are evaluated in terms of resource usage, power consumption, and achievable frame rates. For the evaluation, Microsemi’s Smartfusion2 Advanced Development Kit is used. It includes a SmartFusion2 M2S150 SoC FPGA. The performance of the developed implementation of image filtering algorithm is compared to a solution provided by MATLAB’s Vision HDL Toolbox, which is evaluated on the same platform. The performance of the developed implementations are also compared with FPGA implementations found in existing publications, although those are evaluated on different FPGA platforms. Difficulties with performance comparison between implementations on different platforms are addressed and limitations of processing image streams with FPGA platforms discussed.
Highlights
Cameras are nowadays indispensable gadgets used in a plethora of applications, ranging from uses in automotive industry for autonomous driving [1,2], for security and surveillance [3,4], in medicine [5], for product quality assurance in manufacturing [6], as well as observations of both space [7] and earth1 [8]
While there are multiple works investigating the topic of implementation of the two presented algorithms in a Field Programmable Gate Arrays (FPGAs), only a few provide an evaluation of the achievable processing data rates and/or power consumptions
This paper presented FPGA implementations of two standard image preprocessing algorithms, namely image filtering and image averaging
Summary
Cameras are nowadays indispensable gadgets used in a plethora of applications, ranging from uses in automotive industry for autonomous driving [1,2], for security and surveillance [3,4], in medicine [5], for product quality assurance in manufacturing [6], as well as observations of both space [7] and earth1 [8]. The paper extends the work presented in [22] by comparing the performance of the developed algorithm implementations in terms of processing data rates and power consumptions with the MATLAB’s solution for image filtering and with the performance of other published FPGA implementations of the same algorithms. It elaborates on the difficulties with conducting such a comparison
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