MPCA (Multiway Principal Component Analysis)-based measurement method for area of local region of copper flotation froth image

Abstract

The invention discloses an MPCA (Multiway Principal Component Analysis)-based measurement method for the area of a local region of a copper flotation froth image. The method comprises the following steps: firstly, a three-dimensional RGB (Red, Green and Blue) image is expanded by MPCA to form two-dimensional image data and the two-dimensional image data is projected into an uncorrelated principal component space; then, a local black hydrated region in the image is marked in the principal component space; finally, a principal component image is reconstructed by a load vector, the relation between a principal component space score vector component value and a principal component image characteristic pixel value is used for determining the quantity and space positions of characteristic pixels in the principal component image, the marked local region is mapped to the principal component image and the size of the region is calculated and used as a spectral characteristic of the local region of the forth image. The MPCA-based measurement method for the area of the local region of the copper flotation froth image is applicable to a copper flotation production process and can be used for establishing a production working condition recognition model in a copper flotation process; the MPCA-based measurement method has important meanings of reducing the erroneous judgment rate of a working condition, improving the grade of copper concentrates and realizing the optimization of a copper flotation production and operation process.

Description

technical field [0001] The invention relates to the fields of image processing technology, multivariate statistical analysis and the like, in particular to an MPCA-based method for measuring the area of ​​a local area of ​​a copper flotation foam image. Background technique [0002] Flotation is the most widely used beneficiation method, and its function is to separate useful minerals from ores. For a long time, the production operation of the dressing plant has been completed by the naked eye observation of the flotation foam by experienced workers. The lack of objective standards for the judgment of the foam makes it difficult for the mineral flotation process based on manual observation to be in a stable and optimal operating state. . Using machine vision instead of human vision, using image processing technology to extract the most significant and effective visual features from the foam image, and objectively describe the flotation foam, can provide operational guidance...

AI Technical Summary

Problems solved by technology

[0004] However, the foam state presented by different mineral flotation may be completely different. The study found that the size of the irregular black hydration area in the copper flotation foam image directly reflects the flotation performance. This feature has not been recognized. Applied to flotation process monitoring

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