auto focusing
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2021 ◽  
pp. 2100419
Author(s):  
Jialong Tu ◽  
Xinyue Wang ◽  
Xing Yu ◽  
Haonan Wang ◽  
Dongmei Deng

2021 ◽  
Vol 60 (12) ◽  
Author(s):  
Evgeniy Makagon ◽  
Sergey Khodorov ◽  
Anatoly Frenkel ◽  
Leonid Chernyak ◽  
Igor Lubomirsky

2021 ◽  
Author(s):  
Yong Zhang ◽  
Jialong Tu ◽  
Shangling He ◽  
Yiping Ding ◽  
zhili lu ◽  
...  
Keyword(s):  

2021 ◽  
Vol 130 (23) ◽  
pp. 234903
Author(s):  
Shifu Pu ◽  
Gepu Guo ◽  
Xiasheng Guo ◽  
Chenchen Zhou ◽  
Yuzhi Li ◽  
...  
Keyword(s):  

2021 ◽  
Author(s):  
Wentao Han ◽  
Xiwei Huang ◽  
Maoyu Wei ◽  
Renjie Wang ◽  
Xuefeng Xu ◽  
...  
Keyword(s):  
On Chip ◽  

2021 ◽  
Author(s):  
Xing Liu ◽  
Guodong Chen ◽  
Jinlun Zheng ◽  
Jingsong Wei

Author(s):  
Islam Helmy ◽  
Alaa Hamdy ◽  
Doaa Eid ◽  
Ahmed Shokry

Focus accuracy affects the quality of the astronomical observations. Auto-focusing is necessary for imaging systems designed for astronomical observations. The automatic focus system searches for the best focus position by using a proposed search algorithm. The search algorithm uses the image’s focus levels as its objective function in the search process. This paper aims to study the performance of several search algorithms to select a suitable one. The proper search algorithm will be used to develop an automatic focus system for Kottamia Astronomical Observatory (KAO). The optimal search algorithm is selected by applying several search algorithms into five sequences of star-clusters observations. Then, their performance is evaluated based on two criteria, which are accuracy and number of steps. The experimental results show that the Binary search is the optimal search algorithm.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Krishna C. Polavaram ◽  
Nishant Garg

AbstractIn physical sciences such as chemistry and earth sciences, specifically for characterization of minerals in a rock, automated, objective mapping methods based on elemental analysis have replaced traditional optical petrography. However, mineral phase maps obtained from these newer approaches rely on conversion of elemental compositions to mineralogical compositions and thus cannot distinguish mineral polymorphs. Secondly, these techniques often require laborious sample preparations such as sectioning, polishing, and coating which are time-consuming. Here, we develop a new Raman imaging protocol that is capable of mapping unpolished samples with an auto-focusing Z-mapping feature that allows direct fingerprinting of different polymorphs. Specifically, we report a new methodology for generating high fidelity phase maps by exploiting characteristic peak intensity ratios which can be extended to any multi-phase, heterogenous system. Collectively, these enhancements allow us to rapidly map an unpolished granite specimen (~ 2 × 2 mm) with an exceptionally high accuracy (> 97%) and an extremely fine spatial resolution (< 0.3–2 µm).


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