title: Image distortion correction for micromanipulation system based on SLM microscopic vision.
abstract: Stereo light microscope (SLM) simulates stereo imaging principle of human eyes. Microscopic vision system based on SLM has become an important visual tool for micro measurement, micromanipulation, and microinjection. We develop a micromanipulation system based on SLM and present an image distortion correction method. We mainly correct two kinds of image distortions: lateral and vertical distortion. Distortion correction consists of two steps. First, a linear fitting algorithm for each row or column of target points is developed, and the fitting errors are calculated. If the fitting errors are smaller than a given threshold, the linear fitting results are kept and used. Otherwise polynomial fitting procedure will be used. Second, the parallelism of straight lines is corrected. The results show that a line in world coordinate frame (WCF) is not necessarily a straight line in image coordinate frame (ICF), or two parallel lines in WCF may be not parallel in ICF. Distortion correction can restore the parallel and linear relationship. For distorted left and right images, the magnitude of distortion exceeds 6 pixels and 4 pixels in the horizontal direction, and 1.2 pixels and 1.7 pixels in the vertical direction, respectively. After corrected, for left and right image, distortion can be reduced to 0.8 pixels and 0.7 pixels in the horizontal direction, and 0.96 pixels and 1.3 pixels in the vertical direction, respectively. The results show that distortion parameters obtained from the proposed method can effectively correct distorted images.
authors.affiliation: College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing, 100124, China.
authors.forename: Yuezong
authors.initials: Y
authors.lastname: Wang
authors.forename: Yan
authors.initials: Y
authors.lastname: Jin
authors.affiliation: College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing, 100124, China.
authors.forename: Lika
authors.initials: L
authors.lastname: Wang
keywords: image distortion; micromanipulation; microscopic vision; stereo light microscope