Evaluation of Grain Size Distribution by Digital Image Processing

Abstract

Sieve analysis tests are frequently used to determine the grain size distribution of granular materials. This project proposes an ImageJbased image analysis approach for evaluating aggregate particle size distribution. Grain size in image analysis should be estimated to compare the graduation curves between the two methods.. Black sheets were more effective than white sheets for particle placement, perhaps due to light effects. This technology may be utilized for in-suit testing, as it requires a camera and computer. The study used monochromatic light and a highdefinition camera to capture grain photos while controlling for background, light direction, and intensity. A ground truth was established to evaluate errors in determining grain areas. All grain shape parameters are obtained using the ImageJ program. The grain size distribution curve is generated using image analysis.