Flotation broken froth detection method based on rapid retina feature point matching and multi-scale segmentation
A feature point matching and multi-scale segmentation technology, which is applied in image analysis, image data processing, instruments, etc., can solve the problems of low accuracy, limited accuracy and stability impact of feature point matching method, so as to achieve matching effect and real-time effect. The effect of strong performance, improved detection accuracy and good robustness
A feature point matching and multi-scale segmentation technology, which is applied in image analysis, image data processing, instruments, etc., can solve the problems of low accuracy, limited accuracy and stability impact of feature point matching method, so as to achieve matching effect and real-time effect. The effect of strong performance, improved detection accuracy and good robustness
CN110245672AActive Publication Date: 2019-09-17FUZHOU UNIV
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[0031] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.
[0032] It should be pointed out that the following detailed description is exemplary and is intended to provide further explanation to the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
[0033] It should be noted that the terminology used here is only for describing specific implementations, and is not intended to limit the exemplary implementations according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combina...
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The invention relates to a flotation broken froth detection method based on rapid retina feature point matching and multi-scale segmentation. The flotation broken froth detection method comprises the following steps: firstly, collecting two continuous frames of flotation froth images, carrying out NSST decomposition on the two frames of froth images, carrying out froth edge detection and fusion on a multi-scale high-frequency sub-band, and extracting a central point of each segmented froth in a next frame of image; secondly, carrying out feature point description and matching on the two frames of images by adopting an improved FREAK sampling model, and extracting candidate broken froths according to the distribution density of matching points around the previous frame of segmented froths; finally, mapping the central point of each segmented froth in the next frame of image into the previous frame of segmented image, counting the central point number contained in the candidate broken froths; and judging the candidate broken froths containing a plurality of center points or without center points as broken froths. For the flotation broken froth detection method based on rapid retina feature point matching and multi-scale segmentation, the improved FREAK algorithm is high in matching effect and real-time performance, and the broken froth detection method is less influenced by illumination and motion changes, and the broken froths can be effectively extracted.
Description
technical field [0001] The invention relates to the technical field of flotation bubble detection, in particular to a flotation broken bubble detection method based on fast retinal feature point matching and multi-scale segmentation. Background technique [0002] The stability of flotation bubbles affects the performance of production indicators such as recovery rate and concentrate grade. Accurately extracting broken bubbles is crucial to the establishment of a prediction model for flotation production indicators, but bubbles are constantly changing, such as displacement, deformation, and rupture. Moreover, the collected images are affected by light, which makes it difficult to detect broken bubbles. At present, there are mainly two detection methods at home and abroad: frame difference and feature point matching: the frame difference method first performs displacement correction on adjacent image frames and then calculates the difference, judges the highlighted area in the...
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Patent Timeline
17 Sep 2019
Publication
CN110245672A
- IPC
- G06K9/46; G06T7/13
- CPC
- G06T7/13; G06T2207/30108; G06V10/462
- Inventors
- 廖一鹏; 杨洁洁