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19 pages, 4654 KB  
Article
Development and Assessment of a Field-Programmable Gate Array (FPGA)-Based Image Processing (FIP) System for Agricultural Field Monitoring Applications
by Sabiha Shahid Antora, Young K. Chang, Tri Nguyen-Quang and Brandon Heung
AgriEngineering 2023, 5(2), 886-904; https://doi.org/10.3390/agriengineering5020055 - 11 May 2023
Cited by 9 | Viewed by 3886
Abstract
Field imagery is an effective way to capture the state of the entire field; yet, current field inspection approaches, when accounting for image resolution and processing speed, using existent imaging systems, do not always enable real-time field inspection. This project involves the innovation [...] Read more.
Field imagery is an effective way to capture the state of the entire field; yet, current field inspection approaches, when accounting for image resolution and processing speed, using existent imaging systems, do not always enable real-time field inspection. This project involves the innovation of novel technologies by using an FPGA-based image processing (FIP) device that eliminates the technical limitations of the current agricultural imaging services available in the market and will lead to the development of a market-ready service solution. The FIP prototype developed in this study was tested in both a laboratory and outdoor environment by using a digital single-lens reflex (DSLR) camera and web camera, respectively, as the reference system. The FIP system had a high accuracy with a Lin’s concordance correlation coefficient of 0.99 and 0.91 for the DLSR and web camera reference system, respectively. The proposed technology has the potential to provide on-the-spot decisions, which in turn, will improve the compatibility and sustainability of different land-based systems. Full article
(This article belongs to the Special Issue Implementation of Artificial Intelligence in Agriculture)
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