基于热红外深度估计的路用骨料三维特征评价OA北大核心CSTPCD
Three-dimensional Characterization of Road Aggregates Based on Thermal Infrared Depth Estimation
为优化和实现复杂环境下路用骨料三维特征的快速识别,本文基于温度辅助增强骨料轮廓的思想,提出一种红外图像三维重建方法.首先通过计算不同关键筛孔骨料的点云数据,重建三维模型库.在此基础上,对三维模型的粒度特征、有向包围盒(Oriented bounding box,OBB)特征以及骨料针片状颗粒识别进行评价分析.结果表明,三维模型粒度与骨料粒径的相关系数达到 0.9916,并且OBB尺度特征可以体现骨料三维尺寸信息,贴合误差小;相对传统二维识别算法,基于OBB尺度特征识别针片状颗粒的准确率提高 12%,可为路用骨料特征评价的实际应用提供新思路.
To optimize and realize the rapid identification of three-dimensional features of road aggregates in complex environments,in this study,an infrared image three-dimensional reconstruction method is proposed based on temperature-assisted enhancement of aggregate profile.First,a 3D model library is reconstructed by calculating the point-cloud data of the aggregates with different key sieve holes.On this basis,the particle size characteristics of the 3D model,OBB enveloping box characteristics,and recognition of aggregate pinflake particles are evaluated and analyzed.The results show that the correlation coefficient between the 3D model particle size and aggregate particle size reaches 0.9916,and the OBB scale feature can reflect the 3D size information of the aggregate with a small fitting error.Compared with the traditional two-dimensional identification method,the accuracy of identifying needle flake particles based on the OBB scale feature is improved by 12%,providing new ideas for the practical application of road aggregate feature recognition.
聂根良;程晓红;周超;侯德华;李忠玉
四川工程职业技术学院,四川 德阳 618000四川工程职业技术学院,四川 德阳 618000||河南省高等级公路检测与养护技术重点实验室,河南 新乡 453003河南省高等级公路检测与养护技术重点实验室,河南 新乡 453003||河南省高远公路养护技术有限公司,河南 新乡 453003
交通运输
红外图像点云图像三维重建OBB包围盒针片状颗粒
infrared imagepoint cloud image3d reconstructionoriented bounding boxflat-elongated particles
《红外技术》 2024 (009)
1099-1105 / 7
国家重点研发计划项目(2022YFE0123800);河南省杰出外籍科学家工作室基金资助项目(GZS2022004);河南省重点研发专项(231111520200);新乡市重大科技专项(22ZD013)
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