![]() We developed an ImageJ plugin that extracts the dimensions from a digital image of disjoint particles after identifying their shapes and determines their particles size distribution. Quick and accurate particle size distribution analysis is desirable in various technical fields that handle granular or particulate materials including size reduction. The plugin produced quick and accurate size distribution of particles from digital images and can be applied to variety of particle analysis applications. Developed plugin was applied successfully to analyze the dimensions and size distribution of food grains and ground Miscanthus particles images. Evaluation of effects of the particles shape, size, and orientation on the deviation from the reference particle's length and width indicated that the mean absolute deviations of all these factors were less than 1.3%. ![]() The strategy used only three newly defined shape parameters to identify objects, such as reciprocal aspect ratio, rectangularity, and feret major axis ratio from the standard outputs generated by ImageJ. Using computer generated geometrical shapes as reference objects, a shape identification strategy that addresses common geometric shapes such as square, inclined square, rectangle, inclined rectangle, circle, ellipse, and inclined ellipse was developed. This paper describes the plugin development and its application to food grains and ground biomass. We established that the major and minor axes of ImageJ fitted ellipse along with the developed correction factors efficiently determined dimensions of particles. Questions or concerns? Reach out to our support team at open a support ticket.Quick and accurate particle size distribution analysis is desirable in various technical fields that handle granular or particulate materials including size reduction. This graph compares the normal distributions of particle area for rPET water bottle flake that was submitted to a variety of processing methods. An example of a graph produced from ImageJ data is shown below. It will contain the area in mm^2 of all the particles analyzed. csv file can then be imported into a spreadsheet software of your choice (Excel, Google Sheets, etc). In the results window, go to File > Save As and save as a. If not, rerun Analyze Particles and adjust the minimum and maximum pixel area in the Size (mm^2) box. ![]() Also confirm that the calibration paper is not included in the outlines window. Compare it to the original image to confirm good particle detection.
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