Dynamic measurement precision assessment has been achieved for a differential circle measurement application. Differential circle diameter measurement, in image analysis, typically requires fitting a circle model that optimizes for image distortions, defects or occlusions. The differential task occurs when precise measurements of diameter change are required given object size variation with time. An automated system was designed to provide diameter measurements and associated measurement precision of images of a fuel droplet undergoing combustion in zero gravity for the FLEX-2 dataset. An image gradient-based, least-squares boundary point fitting method to a circle or ellipse model is used for diameter measurement. The presence of soot aggregates poses significant challenges for diameter measurements when it occludes part of the droplet boundary. The precision of the diameter measurements depends upon the image quality. Using synthetic image simulations that model the soot behavior, we developed a model based on image quality measures that assesses the measurement precision for each individual diameter measurement. Thus, diameter measurements with precision assessments were made available for follow-up scientific analysis. The algorithm's success rate for measurable runs was 98%. In cases of limited occlusion, a measurement precision of ±0.2 pixels for the FLEX-2 dataset was achieved.

中文翻译：

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动态差分图像圆直径测量精度评估：在燃烧液滴中的应用


已实现微分圆测量应用的动态测量精度评估。在图像分析中，微分圆直径测量通常需要拟合一个针对图像失真、缺陷或遮挡进行优化的圆模型。当给定物体尺寸随时间变化的情况下需要精确测量直径变化时，就会发生微分任务。自动化系统旨在为 FLEX-2 数据集提供在零重力下燃烧的燃料液滴图像的直径测量和相关测量精度。基于图像梯度的最小二乘边界点拟合圆形或椭圆模型的方法用于直径测量。当烟灰聚集体遮挡部分液滴边界时，它的存在给直径测量带来了重大挑战。直径测量的精度取决于图像质量。使用模拟烟灰行为的合成图像模拟，我们开发了一个基于图像质量测量的模型，用于评估每个单独直径测量的测量精度。因此，具有精确评估的直径测量可用于后续科学分析。该算法可测量运行的成功率为 98%。在有限遮挡的情况下，FLEX-2 数据集的测量精度达到 ±0.2 像素。