Conventional camera calibration that utilizes the extrinsic and intrinsic parameters of the camera and the objects has certain limitations for micro-level cell operations due to the presence of hardware deviations and external disturbances during the experimental process, thereby invalidating the extrinsic parameters. This invalidation is often neglected in macro-world visual servoing and affects the visual image processing quality, causing deviation from the desired position in micro-level cell operations. To increase the success rate of vision guided biological micromanipulations, a novel algorithm monitoring the changing image pattern of the manipulators including the injection micropipette and cell holder is designed and implemented based on 2 dimensional (2D)-to 2D feature correspondences and can adjust the manipulator and perform position control simultaneously. When any deviation is found, the manipulator is retracted to the initial focusing plane before continuing the operation.
Position Control using 2D-to-2D Feature Correspondences in Vision Guided Cell Micromanipulation. Publishing Authors By Initials