Research on the intelligent detection technology of multi-objective coarse aggregates

Abstract

In order to achieve the screening of multi-objective coarse aggregate particles and the detection of needle-like particles, this paper targets the limestone coarse aggregate feature points obtained by Harris corner detection as the research object, using unsupervised clustering technology to intelligently cluster the corner coordinates. To achieve intelligent separation of coarse aggregates and screening of needle-like particles. At the same time, the Harris corners are sensitive to scale, the multi-scale corner information is fitted and the sieving critical value is regressed, and the needle flake determination threshold is integrated. Finally, the intelligent screening system of multi-objective coarse aggregate was integrated, and the correct recognition rate was counted. Studies have shown that the number of feature points of coarse aggregates with different particle sizes has a stable change at different resolutions. Intelligent clustering of feature points of coarse aggregates can replace image segmentation. There is a strong correlation between coarse aggregate texture information and particle size.