Digital image processing technique for particle size, shape and mineralogical, textural analysis

Abstract

Aggregate size and shape measurements are extremely important issues in mining and construction industry because of it directly affect the performance of aggregate products, also there is a prime need of textural analysis in many fields including geological and geotechnical studies. Traditional methods are time consuming and complex. In the present research, we applied DIP (Digital Image Processing) techniques for grain size analysis. Mainly, there are four sections which are unattached particles/fragment analysis, Attached particles/fragment Analysis, Moving particles/fragment Analysis and Colour, texture based classification. In unattached particles analysis, particles were spread without contacting each other and then analysis done. In attached particles analysis, watershed transformation was applied to distinguish particles and then analysis was done. Moving particle analysis were performed by acquiring a video of free falling particles and generating contact-less flow of particles using video processing techniques. Colour and Texture based classification was done by separating the RGB (red, green, blue) bands and calculating mean, standard deviation and smoothness and then k-rnean classification were performed. Finally results from Image processing methods were compared with the conventional methods. The method developed by the research was successfully applied in aggregate and sediment analysis.