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Fast Centroid Estimation Algorithm for Coordinates Measurement of Infrared Markers

机译:红外标记坐标测量的快速质心估计算法

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摘要

To determine the coordinates of infrared markers, it is very important for the binocular vision system based on lightweighted passive infrared reflective markers and infrared LED array PCB board, which is often used to measure the 3-D motion parameters of a rocket motor. Therefore, a fast centroid estimation algorithm, which segments the infrared image using self-adapting thresholding method, and then the centroid of infrared markers is calculated using improved statistical averaging technique, was developed. A comparison was made between the newly developed algorithm and other algorithms such as traditional statistical averaging, FFT and least-squares method. It is found through comparison that the new algorithm is more suitable for high-speed motion analysis due to its higher accuracy and faster processing speed. Experiments performed on real-world images show that the algorithm can greatly improve the speed of the calculation and meantime ensure the demand of precision on the basis of the better image segmentation result and improved statistical averaging technique.
机译:对于确定红外标记的坐标,这对于基于轻型无源红外反射标记和红外LED阵列PCB板的双目视觉系统非常重要,该红外LED阵列PCB板通常用于测量火箭发动机的3-D运动参数。因此,开发了一种快速质心估计算法,该算法使用自适应阈值法对红外图像进行分割,然后使用改进的统计平均技术计算红外标记的质心。在新开发的算法和其他算法(例如传统的统计平均,FFT和最小二乘法)之间进行了比较。通过比较发现,由于新算法具有更高的准确性和更快的处理速度,因此它更适合于高速运动分析。在真实世界图像上进行的实验表明,该算法可以在更好的图像分割结果和改进的统计平均技术的基础上,极大地提高计算速度,同时满足精度要求。

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