Abstract Marker coordinate recognition (MCR) is widely used in fields such as medical character positioning, artificial intelligence control, and motion and deformation monitoring. Registration algorithms are often applied to improve the accuracy of MCR. However, external conditions such as light and temperature induce a temporal variation in the grey level during image acquisition, thereby reducing measurement accuracy. To overcome this problem, a mechanical constraint is introduced into marker point image processing, and an algorithm that incorporates the temporal continuity of deformation is proposed. A detailed derivation of this algorithm is generated, and the algorithm's performance is systematically validated through numerical and experimental tests. The results show that the proposed method yields accurate measurements accuracy but with a slight increase in computational cost. The proposed method can be used to improve deformation measurement and position accuracy.

中文翻译：

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包含变形时间连续性的改进标记坐标识别算法

摘要 标记坐标识别（MCR）广泛应用于医学字符定位、人工智能控制、运动与变形监测等领域。通常应用配准算法来提高 MCR 的准确性。然而，外部条件如光和温度会在图像采集过程中引起灰度级的时间变化，从而降低测量精度。为了克服这个问题，在标记点图像处理中引入了机械约束，并提出了一种结合变形时间连续性的算法。生成了该算法的详细推导，并通过数值和实验测试系统地验证了该算法的性能。结果表明，所提出的方法产生准确的测量精度，但计算成本略有增加。所提出的方法可用于提高变形测量和定位精度。