摘要
为减少浮选气泡合并、破碎等变化对泡沫表面流动特征提取的影响,提出了一种非下采样剪切波变换(Nonsubsampled Shearlet Transform,NSST)域红外目标分割及改进加速鲁棒特征(Speeded Up Robust Features,SURF)匹配的泡沫表面流速检测方法。首先,对相邻两帧泡沫红外图像NSST分解,在多尺度域构建图割能量函数的边界、亮度、显著性约束项实现对合并、破碎气泡的分割;然后,对分割后的背景区域进行SURF特征点检测,通过统计扇形区域内的尺度相关系数确定特征点主方向,采用特征点邻域的多方向高频系数构造特征描述符;最后,对相邻两帧泡沫红外图像进行特征点匹配,根据匹配结果计算泡沫流速的大小、方向、加速度、无序度。实验结果表明,本文方法能有效分割出合并、破碎的气泡,具有较高的分割精度,提升了SURF算法的匹配精度,流速检测受气泡合并、破碎的影响小,检测精度和效率较现有方法有一定提升,能准确地表征不同工况下泡沫表面的流动特性,为后续的工况识别奠定基础。
In order to reduce the influence of changes such as flotation bubble merging and breaking on the foam surface flow feature extraction,a foam surface flow rate detection method based on infrared target segmentation and improved SURF matching in NSST domain is proposed.First,two adjacent froth infrared images are decomposed through NSST,and boundary,brightness,and saliency constraint terms of the graph cut energy function are constructed in the multi-scale domain to realize the segmentation of the merged and broken bubbles.Then,SURF feature point detection are performed on the segmented background region.The main direction of the feature point is determined by statistical the scale correlation coefficients in the sector area,and the multi-directional high-frequency coefficients in the neighborhood of the feature point are used to construct the feature descriptors.Finally,feature points are matched for two adjacent froth infrared images,and the magnitude,direction,acceleration and disorder of foam flow velocity are calculated based on the matching results.The experimental results show that the method in this paper can effectively segment the merged and broken bubbles with high segmentation accuracy,improve the matching accuracy of SURF algorithm,reduce the impact of the bubbles merging and breaking on the flow velocity detection.Compared with the existing methods,the method in this paper improve the detection accuracy and efficiency,which can accurately characterize the flow characteristics of the foam surface under different working conditions and lay the foundation for the subsequent working condition identification.
作者
施雯玲
廖一鹏
许志猛
严欣
朱坤华
SHI Wenling;LIAO Yipeng;XU Zhimeng;YAN Xin;ZHU Kunhua(College of Physics and Information Engineering,Fuzhou University,Fuzhou 350108,China)
出处
《红外技术》
CSCD
北大核心
2023年第5期463-473,共11页
Infrared Technology
基金
国家自然科学基金项目(61601126,61904031)
福建省自然科学基金项目(2019J01224)。
关键词
泡沫红外图像
流速检测
非下采样剪切波变换
红外目标分割
SURF匹配
foam infrared images
flow velocity detection
non⁃subsampled shearlet transform
infrared tar-get segmentation
SURF matching
