Introduction to Using Image Analysis for Particle Size and Shape Analysis

Introduction to Using Image Analysis for Particle Size and Shape Analysis.

Image Analysis (IA) technology characterizes particles by digitizing photos of each particle and storing them in an image file which is then analyzed by calculating all the morphological parameters based on the known size and location of the pixels in each image. IA instruments can be either static or dynamic in nature and can measure either dry materials or suspensions and emulsions.

Both dynamic and static IA instruments measure typically twenty-five or more different sizes and shapes of particles. In contrast to more traditional particle characterization technologies, which measure only one size, Equivalent Spherical Diameter, or ESD, (sieves, sedimentation and laser diffraction for example), and no shapes, IA provides much more complete morphological information about the material. And it makes it available in the same type of graphical and tabular distributions, summary data and statistics for each parameter, which the traditional techniques report.

In addition to the full morphological profile which IA provides, there are two more distinct advantages. Individual particles are measured, rather than an ensemble of multiple particles generating one combined signal. This makes the Number (or Count) distribution as accurate as the Volume distribution, unlike the traditional methods which calculate an estimate of the Number distribution from the measured Volume distribution. The second added advantage is that the entire image file is stored for visual review and decision making. Seeing the particles can give quick confirmation of the analytical results and point out subtleties that might not be reported, like whether any certain particle(s) are agglomerates or individual particles.

Static IA’s are basically bench-top optical microscopes equipped with a motorized stage which moves stepwise to different locations where the frames of particles are photographed. The image file is stored in the controlling computer and analyzed by measuring the size and locations of the image pixels, just as the analysis is conducted in dynamic IA’s after the image file is saved.  Dynamic IA’s measure a stream of flowing particles using a rapid strobe light on one side of the stream and a digital camera on the other capturing the particle images used in the analysis. More on static and dynamic IA differences in future blog posts.

Figure: Extract of a few images from an image file of a multi-component granular fertilizer blend. Note differences in opacity based on the amount of light coming through the particles. In addition to sizes and shapes, the light intensity is also a parameter which can be used to distinguish different components in a multi-component blend of particles. The parameter value chosen to be displayed above is length, in millimeters.

Figure: Extract of a few images from an image file of a multi-component granular fertilizer blend. Note differences in opacity based on the amount of light coming through the particles. In addition to sizes and shapes, the light intensity is also a parameter which can be used to distinguish different components in a multi-component blend of particles. The parameter value chosen to be displayed above is length, in millimeters.

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