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J. Imaging, Volume 5, Issue 12 (December 2019) – 2 articles

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Cover Story (view full-size image) Here the author describes the use of open-source software and an open hardware design to build a [...] Read more.
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Open AccessReview
Machine Vision Systems in Precision Agriculture for Crop Farming
J. Imaging 2019, 5(12), 89; https://doi.org/10.3390/jimaging5120089 - 07 Dec 2019
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Abstract
Machine vision for precision agriculture has attracted considerable research interest in recent years. The aim of this paper is to review the most recent work in the application of machine vision to agriculture, mainly for crop farming. This study can serve as a [...] Read more.
Machine vision for precision agriculture has attracted considerable research interest in recent years. The aim of this paper is to review the most recent work in the application of machine vision to agriculture, mainly for crop farming. This study can serve as a research guide for the researcher and practitioner alike in applying cognitive technology to agriculture. Studies of different agricultural activities that support crop harvesting are reviewed, such as fruit grading, fruit counting, and yield estimation. Moreover, plant health monitoring approaches are addressed, including weed, insect, and disease detection. Finally, recent research efforts considering vehicle guidance systems and agricultural harvesting robots are also reviewed. Full article
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Open AccessReview
Software-Based Three-Dimensional Deconvolution Microscopy of Cytoskeletal Proteins in Cultured Fibroblast Using Open-Source Software and Open Hardware
J. Imaging 2019, 5(12), 88; https://doi.org/10.3390/jimaging5120088 - 23 Nov 2019
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Abstract
As conventional fluorescence microscopy and confocal laser scanning microscopy generally produce images with blurring at the upper and lower planes along the z-axis due to non-focal plane image information, the observation of biological images requires “deconvolution.” Therefore, a microscope system’s individual blur [...] Read more.
As conventional fluorescence microscopy and confocal laser scanning microscopy generally produce images with blurring at the upper and lower planes along the z-axis due to non-focal plane image information, the observation of biological images requires “deconvolution.” Therefore, a microscope system’s individual blur function (point spread function) is determined theoretically or by actual measurement of microbeads and processed mathematically to reduce noise and eliminate blurring as much as possible. Here the author describes the use of open-source software and open hardware design to build a deconvolution microscope at low cost, using readily available software and hardware. The advantage of this method is its cost-effectiveness and ability to construct a microscope system using commercially available optical components and open-source software. Although this system does not utilize expensive equipment, such as confocal and total internal reflection fluorescence microscopes, decent images can be obtained even without previous experience in electronics and optics. Full article
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