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A disparity servoing based fast autofocusing method is proposed for stereomicroscopes according to linear relationship between the disparity change in stereomicroscopic images and the move distance of a motorized translation stage. For a certain stereomicroscope, the calibration of a disparity range of clear images at each magnification is implemented offline. After that, the disparity of the stereomicroscopic image is used as an index to represent the sharpness of an arbitrary image. If the disparity does not satisfy the requirement, move steps and direction of a step motor are calculated by utilizing the linear relationship between the disparity change and the move distance of the stage. The iteration will be continued until the disparity of the captured stereomicroscopic image approximates to the clearest disparity. The experimental results show that the proposed method only requires a few iterations and less time to reach the focus position, and the disparity error is less than 0.5 pixel.
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Tom
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651--663
Opis fizyczny
Bibliogr. 13 poz., rys.
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autor
- Department of Information Science and Engineering, Ningbo University, Ningbo, China
autor
- Department of Information Science and Engineering, Ningbo University, Ningbo, China
autor
- Department of Information Science and Engineering, Ningbo University, Ningbo, China
autor
- Department of Information Science and Engineering, Ningbo University, Ningbo, China
autor
- Department of Information Science and Engineering, Ningbo University, Ningbo, China
- Department of Information, Ningbo Institute of Technology, Zhejiang University, Ningbo, China
autor
- Department of Information Science and Engineering, Ningbo University, Ningbo, China
- Department of Information, Ningbo Institute of Technology, Zhejiang University, Ningbo, China
Bibliografia
- [1] SHUNLI XIAO, YANGMIN LI, Visual servo feedback control of a novel large working range micro manipulation system for microassembly, Journal of Microelectromechanical Systems 23(1), 2014, pp. 181–190.
- [2] ÇELIK H.İ., DÜLGER L.C., TOPALBEKIROĞLU M., Development of a machine vision system: real-time fabric defect detection and classification with neural networks, The Journal of The Textile Institute 105(6), 2014, pp. 575–585.
- [3] CHUAN JIANG, MILLS J.K., Development of a cell orientation control system for mouse embryo using electro-rotation, 2014 IEEE International Conference on Mechatronics and Automation, 2014, pp. 1085–1090.
- [4] SHAFAAT AHMED BAZAZ, NAYYER ABBAS, MUHAMMAD BILAL SAIF, NISAR AHMAD, Design and characterization of MEMS based micrograsping system, Assembly Automation 33(3), 2013, pp. 260–271.
- [5] CHAO-CHEN GU, KAI-JIE WU, JIE HU, CHENG HAO, XIN-PING GUAN, Region sampling for robust and rapid autofocus in microscope, Microscopy Research and Technique 78(5), 2015, pp. 382–390.
- [6] YU SUN, DUTHALER S., NELSON B.J., Autofocusing algorithm selection in computer microscopy, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2005, pp. 70–76.
- [7] XIN XU, YINGLIN WANG, XIAOLONG ZHANG, SHUNXIN LI, XIAOMING LIU, XIAOFENG WANG, JINSHAN TANG, A comparison of contrast measurements in passive autofocus systems for low contrast images, Multimedia Tools and Applications 69(1), 2014, pp. 139–156.
- [8] BARAN E.A., AYIT O., SANTIAGO V.B., LÓPEZ-DÓRIGA S., SABANOVIC A., A self-optimizing autofocusing scheme for microscope integrated visual inspection systems, Industrial Electronics Society, IECON 2013 – 39th Annual Conference of the IEEE, 2013, pp. 4043–4048.
- [9] CHIEN-SHENG LIU, SHENG-HONG JIANG, Precise autofocusing microscope with rapid response, Optics and Lasers in Engineering 66, 2015, pp. 294–300.
- [10] CHIEN-SHENG LIU, YANG-CHENG LIN, PIN-HAO HU, Design and characterization of precise laser-based autofocusing microscope with reduced geometrical fluctuations, Microsystem Technologies 19(11), 2013, pp. 1717–1724.
- [11] MARTURI N., TAMADAZTE B., DEMBÉLÉ S., PIAT N., Visual servoing-based approach for efficient autofocusing in scanning electron microscope, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2013, pp. 2677–2682.
- [12] FUSIELLO A., IRSARA L., Quasi-Euclidean epipolar rectification of uncalibrated images, Machine Vision and Applications 22(4), 2011, pp. 663–670.
- [13] BAY H., TUYTELAARS T., VAN GOOL L., Surf: speeded up robust features, [In] Computer Vision – ECCV 2006, [Eds] A. Leonardis, H. Bischof, A. Pinz, Springer Berlin Heidelberg, 2006, pp. 404–417.
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
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Bibliografia
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