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Foam infrared image segmentation method based on NSST saliency detection and image segmentation

An infrared image, a remarkable technology, applied in image analysis, image enhancement, image data processing, etc., can solve the problems of difficult extraction of watershed identification points, low resolution and contrast, blurred segmentation area, etc., to solve over-segmentation and under-segmentation. Problems, strong anti-interference ability, and the effect of improving segmentation accuracy

Active Publication Date: 2020-01-03
FUZHOU UNIV
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AI Technical Summary

Problems solved by technology

However, the foam infrared image has the problem of low resolution and contrast, and is easily disturbed by noise, and the high temperature area at the edge of the bubble will affect the segmentation results. At present, the segmentation methods of infrared images mainly include: the region growing segmentation algorithm first performs Gaussian filtering to remove noise, and then Using the region growing algorithm, the segmentation accuracy and speed are improved, but it will cause holes and blurred edges in the segmented area; the improved watershed segmentation method uses area reconstruction transformation to solve the problem of difficult extraction of watershed identification points, but there is a problem of blurred boundaries And the segmentation parameters need to change with the actual situation; the threshold segmentation algorithm extends Otsu threshold segmentation to Otsu multi-threshold segmentation, and introduces the group search random optimization algorithm into multi-threshold segmentation, which improves the threshold search speed and segmentation accuracy, but is not suitable for noise processing and Processing of infrared photovoltaic images with complex backgrounds; K-clustering algorithm segmentation first enhances infrared images based on morphology, and then performs image segmentation by modifying the distance formula used in k-means clustering. The segmented image target outline is clear, But the integrity of the target area is low

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  • Foam infrared image segmentation method based on NSST saliency detection and image segmentation

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Embodiment Construction

[0035] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0036] The invention provides a foam infrared image segmentation method based on NSST saliency detection and graph cuts. First, the foam infrared image is decomposed by NSST to obtain low-frequency sub-band images and multi-scale high-frequency sub-bands; secondly, the GBVS algorithm is used to Perform saliency detection on low-frequency sub-band images to obtain saliency values ​​and visual saliency maps; then, calculate thresholds and scale correlation coefficients for each high-frequency direction sub-band coefficient, and remove noise coefficients and nonlinear enhanced edge and weak edge coefficients; finally, The NSST reconstructed image is combined with visual saliency to perform graph cuts to obtain segmentation results. like figure 1 As shown, the method specifically includes the following steps:

[0037] Step 1. Perform NSST multi-s...

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Abstract

The invention relates to a foam infrared image segmentation method based on NSST saliency detection and image segmentation, and the method comprises the steps: firstly carrying out the NSST decomposition of a foam infrared image, and obtaining a low-frequency sub-band image and a multi-scale high-frequency sub-band; secondly, performing saliency detection on the low-frequency sub-band image by adopting a GBVS algorithm to obtain a saliency value and a visual saliency map; thirdly, calculating a threshold value and a scale correlation coefficient for each high-frequency direction sub-band coefficient, and removing a noise coefficient, a non-linear enhanced edge coefficient and a weak edge coefficient; and finally, performing image segmentation on the NSST reconstructed image in combinationwith visual saliency to obtain a segmentation result. The method is strong in anti-interference capability and high in segmentation precision.

Description

technical field [0001] The invention relates to the technical field of flotation, in particular to a foam infrared image segmentation method based on NSST saliency detection and graph cut. Background technique [0002] Flotation is the collision and adhesion between the minerals in the flotation machine and the micro-bubbles in the air. Using the hydrophilic and hydrophobic properties of the surface of the minerals and impurities, the highly buoyant mineral particles float up to the foam layer of the liquid surface with the bubbles, so that the target minerals A beneficiation method for sorting ore from ores with complex material composition. Studies have shown that the generation and collapse of bubbles in the flotation process can effectively reflect the mineral content, and image segmentation is the key to flotation image processing analysis and detection of newly generated and collapsed bubbles, and is widely used in computer vision and industrial production. [0003] T...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/12G06T5/00
CPCG06T7/12G06T2207/10048G06T5/70
Inventor 廖一鹏陈诗媛张进
Owner FUZHOU UNIV
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