Applications of Angle Measure Technique (AMT) in image analysis: Part I. A new methodology for in situ powder characterization

A new approach for powder characterization based on image analysis, “Angle Measure Technique” (AMT) and multivariate data modeling is presented. AMT is designed to describe signal complexity as a function of geometrical scale from local to global. In this application, powder images are first unfolded to produce 1-D measurement series, which AMT, subsequently, transforms into multivariate scale characterizations. This new compound approach is able to extract and characterize powder features, such as particle size(s), shape(s), smoothness, coarseness, graininess, mixing homogeneity, as well as to classify and discriminate between different powders and even predict bulk behavioral properties. Experimental work reported here involves digital imaging of several tens of different types of powders, using a problem-dependent, low-angle, asymmetric illumination. The unilateral illumination setup brings about a significant simplification of traditional image analysis in powder studies, which is usually orientated towards characterizing all individual particles before aggregating this information. The present new technique achieves the same objectives by a simple and direct imaging, followed by AMT chemometric analysis. Principal Component Analysis (PCA) on AMT spectra derived from this type of imagery is used here to illustrate the power of this new technique, specifically to discriminate between powder types.