A new high-precision sphere-fitting method with small segment angles

2020 ◽  
Vol 32 (1) ◽  
pp. 015012
Author(s):  
Zhigen Fei ◽  
Jixiang Fu ◽  
Jun Ma ◽  
Wenbin He ◽  
Yanqiu Xiao
Keyword(s):  
High Precision ◽  
Small Segment ◽  
Fitting Method ◽  
Sphere Fitting

A new short-arc fitting method with high precision using Adam optimization algorithm

Optik ◽  
2020 ◽  
Vol 212 ◽  
pp. 164788
Author(s):  
Zhigen Fei ◽  
Zhiying Wu ◽  
Yanqiu Xiao ◽  
Jun Ma ◽  
Wenbin He
Keyword(s):  
High Precision ◽  
Optimization Algorithm ◽  
Fitting Method ◽  
Short Arc

scholarly journals APPLICATION OF MULTI-FACETED FUNCTION MODEL BASED ON VONDRAK FILTER OPTIMIZATION IN UAV AERIAL IMAGE HEIGHT CORRECTION

2020 ◽  
Vol XLII-3/W10 ◽  
pp. 1313-1317
Author(s):  
F. Zhou ◽  
L. Pu ◽  
S. H. Tang ◽  
Y. F. Yang
Keyword(s):  
High Precision ◽  
Surface Fitting ◽  
Aerial Image ◽  
Experimental Comparison ◽  
Cubic Surface ◽  
Aerial Photogrammetry ◽  
Function Fitting ◽  
Fitting Method ◽  
Elevation Correction ◽  
Vondrak Filter

Abstract. With the rapid development of drone technology and digital camera technology, the method of obtaining high-precision coordinates based on UAV aerial photogrammetry technology is popular. The plane coordinate accuracy of the aerial image of the drone has been able to meet the needs of practical applications, but the elevation accuracy is generally low. Aiming at the low elevation accuracy of UAV aerial photogrammetry, a multi-face function fitting method based on Vondrak filter optimization was proposed. The improved fitting model was used to obtain the elevation correction value of the aerial image, thereby obtaining high-precision image elevation data. In this paper, based on the traditional multi-face function fitting method, some known points were used to model and find the difference between the measured elevation value and the measured elevation. The Vondrak filter was used to smooth the fitting result. Finally, a small number of known elevation points were used for checking, so that the obtained elevation was compared with the actual elevation. The experimental comparison showed that the improved multi-face function fitting method used Vondrak filter was improved by 34.76% compared with the quadric surface fitting, and improved by 14.48% compared with the optimized cubic surface fitting method. Research shows that the multi-faceted function method based on Vondrak filtering is superior to the traditional elevation correction method. The experiment verifies the effectiveness and feasibility of the improved method, and provides some reference value for the research of aerial image elevation correction model.

A new fitting method for measurement of the curvature radius of a short arc with high precision

2018 ◽  
Vol 29 (7) ◽  
pp. 075014 ◽  
Author(s):  
Wei Tao ◽  
Hong Zhong ◽  
Xiao Chen ◽  
Yassine Selami ◽  
Hui Zhao
Keyword(s):  
High Precision ◽  
Curvature Radius ◽  
Fitting Method ◽  
Short Arc

scholarly journals Capturing Surface Complementarity in Proteins using Unsupervised Learning and Robust Curvature Measure

2021 ◽  
Author(s):  
Abhijit Gupta ◽  
Arnab Mukherjee
Keyword(s):  
Machine Learning ◽  
Biological Function ◽  
Current Approach ◽  
Curvature Measure ◽  
Shape Complementarity ◽  
Binding Partners ◽  
Fitting Method ◽  
Antigen Antibody ◽  
The Relationship ◽  
Sphere Fitting

The structure of a protein plays a pivotal role in determining its function. Often, the protein surface’s shape and curvature dictate its nature of interaction with other proteins and biomolecules. However, marked by corrugations and roughness, a protein’s surface representation poses significant challenges for its curvature-based characterization. In the present study, we employ unsupervised machine learning to segment the protein surface into patches. To measure the surface curvature of a patch, we present an algebraic sphere fitting method that is fast, accurate, and robust. Moreover, we use local curvatures to show the existence of “shape complementarity” in protein-protein, antigen-antibody, and protein-ligand interfaces. We believe that the current approach could help understand the relationship between protein structure and its biological function and can be used to find binding partners of a given protein.

scholarly journals On High-precision Subpixel-based Drilling Technique for Suture Needles with Thread

2014 ◽  
Vol 8 (1) ◽  
pp. 607-612
Author(s):  
Tiebo Sun ◽  
Hong Li
Keyword(s):  
Edge Detection ◽  
High Precision ◽  
Noise Suppression ◽  
Hole Drilling ◽  
Drilling Process ◽  
Structural Elements ◽  
Spatial Moments ◽  
Automated Production ◽  
Fitting Method ◽  
Drilling Method

In order to improve the automation of end-hole drilling process in the production of suture needles with thread, a high-precision subpixel-based drilling method is proposed. According to the edge detection principle in mathematical morphology, combined with the characteristics of the magnified images of the ends of suture needles to be drilled, the morphological edge detection operators with variable structural elements are constructed to achieve noise suppression and fully extract the detailed information of edges of images of needle end holes to be drilled. Then, the subdivision method of spatial moments is adopted to realize the subpixel positioning of pixel-level edges. Finally, least squares fitting method is used to achieve the high-precision positioning of center of needle end hole to be drilled. The experimental results of the 0.5 mm needle samples show that the drilling method proposed in this study has a concentricity error no more than ± 0.2 μm and an average drilling time of 0.65S. Moreover, the method also boasts good real-time performance and stability and meets the automated production needs of drilling process of suture needles with thread.

scholarly journals High Precision Timing with Parabolic Equation Fitting in Narrowband Systems

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4164
Author(s):  
Zou ◽  
Xu
Keyword(s):  
Parabolic Equation ◽  
High Precision ◽  
Communication Systems ◽  
Orthogonal Frequency Division Multiplexing ◽  
Sampling Rate ◽  
Wireless Communication Systems ◽  
Fitting Method ◽  
Fitting In ◽  
Timing Requirement ◽  
Synchronization Performance

Timing forms the basis of wireless communication systems. Orthogonal frequency division multiplexing (OFDM) technology has strict requirements for synchronization performance, and timing errors lead to interference between subcarriers and symbols. Although cyclic prefix (CP) can relax the timing requirement, high precision timing is still necessary and can release the pressure on CP. Due to the uncertainty of signal arrival, there is a sampling offset between the sampling sample’s timing and the real timing, which can be large in the narrowband system with a low sampling rate. In this paper, we propose a parabolic equation fitting method to improve the timing precision in narrowband systems that have two times the rate of the Nyquist sampling rate. The proposed timing method is easy to implement, with low additional complexity compared to traditional timing detection and is based on traditional direct correlator output.

Research of a High Precision Time Synchronization Method Based on GPS Calibration

2014 ◽  
Vol 644-650 ◽  
pp. 1477-1480
Author(s):  
Bu Xin You ◽  
Jing Bu ◽  
Ming Hui Yin ◽  
Yun Zou
Keyword(s):  
Power System ◽  
High Precision ◽  
Time Synchronization ◽  
Least Squares Method ◽  
Generalized Least Squares ◽  
Measuring Instruments ◽  
Random Errors ◽  
Crystal Oscillator ◽  
Precision Measuring ◽  
Fitting Method

With the higher requirement for clock accuracy in power system, the accuracy and stability of wild area punctuality in GPS cannot meet the demands of the high–precision measuring instruments in power system. Firstly, this paper establishes the mathematical model of crystal oscillator clock error using polynomial fitting method. Then, it estimates the parameters of polynomial model with generalized least squares method. Thirdly, it updates the error-model of crystal oscillator clock dynamically for modifying its predicted error. The result shows, this method can not only predict accurate time error, but also filter out random errors well in GPS.

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