Click on “Download PDF” for the PDF version or on the title for the HTML version. If you are not an ASABE member or if your employer has not arranged for access to the full-text, Click here for options. Simplified No-Code Machine Vision Method of Accurate Dimension Measurement of Granular MaterialsPublished by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org Citation: Paper number RRV12124, ASABE/CSBE North Central Intersectional Meeting. (doi: 10.13031/2013.41317) @2007Authors: Igathinathane - Cannayen, Leslie F Backer Keywords: ImageJ, particles, plugin, dimensions, physical properties, image processing Dimension measurement of agricultural produce and products plays a vital role in quality control, grading, and characterization. Measurement using digital calipers is the most common manual method, but the difficulty increases especially when the particles size is small or their number is large. Useful measurements, such as length, width, projected area, and perimeter, are laborious to obtain or sometimes impractical by manual methods. A simple, inexpensive and yet accurate solution to this challenging issue is the application of machine vision method coupled with image processing. This method uses a common digital document scanner for image acquisition along with ImageJ, an open source free software, to perform the dimensional measurements. ImageJ has several built-in commands that can analyze the images and produce several useful measurements that can be directly used or further analyzed for particle size distribution. This paper presents a step-by-step procedure in measuring the dimensions of granular materials using the machine vision method. Several food grains and airborne pellet dust particles were used as example materials and the no-code machine vision method was demonstrated. (Download PDF) (Export to EndNotes)
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