Image moments are global descriptors of an image and can be used to achieve control-decoupling properties in visual servoing. However, only a few methods completely decouple the control. This study introduces a novel camera pose estimation method, which is a closed-form solution, based on the image moments of planar objects. Traditional position-based visual servoing estimates the pose of a camera relative to an object, but the pose estimation method directly estimates the pose of an initial camera relative to a desired camera. Because the estimation method is based on plane parameters, a plane parameters estimation method based on the 2D rotation, 2D translation, and scale invariant moments is also proposed. A completely decoupled position-based visual servoing control scheme from the two estimation methods above was adopted. The new scheme exhibited asymptotic stability when the object plane was in the camera field of view. Simulation results demonstrated the effectiveness of the two estimation methods and the advantages of the visual servo control scheme compared with the classical method.

图像矩是图像的全局描述符，可用于实现视觉伺服中的控制解耦特性。但是，只有少数方法可以完全解耦控件。本研究介绍了一种新的相机位姿估计方法，它是一种基于平面物体图像矩的封闭式解决方案。传统的基于位置的视觉伺服估计相机相对于物体的位姿，但是位姿估计方法直接估计初始相机相对于期望相机的位姿。由于该估计方法是基于平面参数的，因此还提出了一种基于二维旋转、二维平移和尺度不变矩的平面参数估计方法。采用与上述两种估计方法完全解耦的基于位置的视觉伺服控制方案。当物体平面在相机视野中时，新方案表现出渐近稳定性。仿真结果证明了两种估计方法的有效性以及视觉伺服控制方案与经典方法相比的优势。