title: A self-adaptive and nonmechanical motion autofocusing system for optical microscopes.
abstract: For the design of a passive autofocusing (AF) system for optical microscopes, many time-consuming and tedious experiments have been performed to determine and design a better focus criterion function, owing to the sample-dependence of this function. To accelerate the development of the AF systems in optical microscopes and to increase AF speed as well as maintain the AF accuracy, this study proposes a self-adaptive and nonmechanical motion AF system. The presented AF system does not require the selection and design of a focus criterion function when it is developed. Instead, the system can automatically determine a better focus criterion function for an observed sample by analyzing the texture features of the sample and subsequently perform an AF procedure to bring the sample into focus in the objective of an optical microscope. In addition, to increase the AF speed, the Z axis scanning of the mechanical motion of the sample or the objective is replaced by focusing scanning performed by a liquid lens, which is driven by an electrical current and does not involve mechanical motion. Experiments show that the reproducibility of the results obtained with the proposed self-adaptive and nonmechanical motion AF system is better than that provided by that of traditional AF systems, and that the AF speed is 10 times faster than that of traditional AF systems. Also, the self-adaptive function increased the speed of AF process by an average of 10.5% than Laplacian and Tenegrad functions.
authors: Key Laboratory of Precision Opto-mechatronics Technology, Ministry of Education, Beihang University, Beijing, 100191, China. qyf@buaa.edu.cn.
authors: Yufu
authors: Y
authors: Qu
authors: Key Laboratory of Precision Opto-mechatronics Technology, Ministry of Education, Beihang University, Beijing, 100191, China.
authors: Shenyu
authors: S
authors: Zhu
authors: Key Laboratory of Precision Opto-mechatronics Technology, Ministry of Education, Beihang University, Beijing, 100191, China.
authors: Ping
authors: P
authors: Zhang
keywords: autofocusing; criterion function; liquid lens; self-adaptive