Enhancing microscopy images of minerals through morphological center operator-based feature extraction

Study on Calcination Characteristics of Diaspore-Kaolin Bauxite Based on Machine Vision

D-K-type bauxite from Guizhou can be used as an unburned ceramic, adsorbent, and geopolymer after low-temperature calcination. It aims to solve the problem where the color of the D-K-type bauxite changes after calcination at different temperatures. Digital image processing technology was used to extract the color characteristics of bauxite images after 10 min of calcination at various temperatures. Then, we analyzed changes in the chemical composition and micromorphology of bauxite before and after calcination and investigated the correlation between the color characteristics of images and composition changes after bauxite calcination. The test results indicated that after calcining bauxite at 500 °C to 1000 °C for 10 min, more obvious dehydration and decarburization reactions occurred. The main component gradually changed from diaspore to Al2O3, the chromaticity value of the image decreased from 0.0980 to 0.0515, the saturation value increased from 0.0161 to 0.2433, and the brightness value increased from 0.5890 to 0.7177. Studies have shown that changes in bauxite color characteristics are strongly correlated with changes in composition. This is important for directing bauxite calcination based on digital image processing from engineering viewpoints.

Microscopy mineral image enhancement through center operator construction

Enhancing a microscopy mineral image to produce clear and rich details is important for mineral analysis. To enhance effectively, an algorithm utilizing the constructed center operator is proposed in this paper. First, the center operator is constructed from the opening and closing based toggle operator. Second, the mineral image features are extracted by using the constructed center operator. Third, the multiscale mineral features are extracted through multiscale morphological theory using the multiscale structuring elements. Fourth, the final features for mineral image enhancement are calculated from the extracted multiscale features based on the weight strategy. Finally, the mineral image is effectively enhanced through importing the final features into the original mineral image. Experimental results on various microscopy mineral images verified that the proposed algorithm performed well for enhancement and had competing performance compared with some existing algorithms.