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To acquire the mineral composition of iron ore sinter, the research work until now mainly focuses on two aspects which are traditional manual method often called Point Counting Method and Image Processing Method respectively. Point Counting Method is of high labor intensity and of low efficiency compared with Image Processing Method. Meanwhile, existing Image Processing Method always encounters low accuracy when it is applied to analyze the sinter with special microstructure such as large pores. This paper presents an improved method based on modified gray-level images and extracted texture images with knowledge base rules, producing the final images more suitable for computer to deal with. The experimental results demonstrate that this improved technique is valid for quantifying the mineral composition of sinter and it has a higher-level accuracy of recognition than existing image processing methods do.

Quantitative Analysis of Mineral Composition of Iron Ore Sinter Based on Comprehensive Image Processing Techniques