Pixelina
The problem
In almost every lab where there is a a microscope, there is a need to document images. But the needs varies largely for different labs and organizations. In the easiest case you probably just want to capture one or a few images, save it to file, and later use them in some kind of report. In the more advanced scenario, you might have requirement to document all samples analyzed, with thousands or even hundred of thousands images per year.
Almost certainly you want to share your images with others and even with other labs or departments in your organization.
Our products can do all the above. This article is to explain which products might suit you best.
GRAIN SIZE MEasurEment
In metal alloys, one of the most important characteristics of the material is the average grain size. For this purpose, the well known and widely accepted ASTM-112 standard has been developed.
The standard determines the average size of uni-modal distributed grains, measured on a 2D-surface, making it suitable for microscopic analysis.
Unfortunately the work of measuring the grain size of a sample according to the standard is in most cases very time consuming, involves a lot of manual work, is error prone and often downright boring. Pixelina now offers a module that tries to addresses all these issues by introducing Artificial Intelligence to separate grains,
Different sample
Since grains looks extremely different in different materials and also varies with sample preparation and illumination method different approaches has been developed to measure the average grain size.
The standard offers three different approaches to determine the average grain size, often referred to as:
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The comparison method, where the sample is compared against a set of images with well known average size.
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The intercept method, where the number of grains or grain boundaries on a line with well know length is counted
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The planimetric method (image analysis) method, where whole grains are automatically identified and their actual size is counted.
Pixelina supports all methods.
Regardless of method, one of the most challenging part of grain size estimation is to locate the grain boundaries. The grain boundaries are often weak, could be of any color or intensity and could easily be confused with both twins and scratches. Simple edge detection or threshold based algorithm simply does not cut it in most real life situations, why we introduced Artificial Intelligence to highly improve this part of the work.
Rega
By tracking orientation, Pixelina can assist you in computing the grain size in any plane/orientation.
Both Picsara and Pixelina is capable to determine the Average Grain Size according to ASTM-112, but the recommended app is Pixelina.