Calibration procedure in dual-energy scanning using the basis function technique

1983 ◽  
Vol 10 (5) ◽  
pp. 628-635 ◽  
Author(s):  
C. K. Wong ◽  
H. K. Huang
Keyword(s):  
Basis Function ◽  
Calibration Procedure ◽  
Dual Energy ◽  
Function Technique

scholarly journals Calibration Method of Orthogonally Splitting Imaging Pose Sensor Based on General Imaging Model

2018 ◽  
Vol 8 (8) ◽  
pp. 1399 ◽  
Author(s):  
Na Zhao ◽  
Changku Sun ◽  
Peng Wang
Keyword(s):  
Coordinate System ◽  
Radial Basis Function ◽  
Basis Function ◽  
Calibration Method ◽  
Calibration Procedure ◽  
Distortion Correction ◽  
Imaging Model ◽  
The World ◽  
Radial Basis ◽  
Pinhole Imaging

Orthogonally splitting imaging pose sensor is a new sensor with two orthogonal line array charge coupled devices (CCDs). Owing to its special structure, there are distortion correction and imaging model problems during the calibration procedure. This paper proposes a calibration method based on the general imaging model to solve these problems. The method introduces Plücker Coordinate to describe the mapping relation between the image coordinate system and the world coordinate system. This paper solves the mapping relation with radial basis function interpolation and adaptively selecting control points with Kmeans clustering method to improve the fitting accuracy. This paper determines the appropriate radial basis function and its shape parameter by experiments. And these parameters are used to calibrate the orthogonally splitting imaging pose sensor. According to the calibration result, the root mean square (RMS)of calibration dataset and the RMS of test dataset are 0.048 mm and 0.049 mm. A comparative experiment is conducted between the pinhole imaging model and the general imaging model. Experimental results show that the calibration method based on general imaging model applies to the orthogonally splitting imaging pose sensor. The calibration method requires only one image corresponding to the target in the world coordinates and distortion correction is not required to be taken into account. Compared with the calibration method based on the pinhole imaging model, the calibration procedure based on the general imaging model is easier and accuracy is greater.

scholarly journals Improving the modeling and forecasting of fuel selling price using the radial basis function technique: A case study

2019 ◽  
Vol 13 ◽  
pp. 174830261988112
Author(s):  
Zineb Aman ◽  
Latifa Ezzine ◽  
Younes Fakhradine El Bahi ◽  
Haj EL Moussami
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Radial Basis Function ◽  
Basis Function ◽  
Radial Basis Function Network ◽  
Arima Model ◽  
Function Technique ◽  
Selling Price ◽  
Radial Basis ◽  
Artificial Neural

Recently, the petroleum sector in Morocco has been liberalized which has a significant effect for petroleum product distributors. Since the beginning of December 2015, fuel prices are freely determined. This event presents many constraints affecting the balance of the sector plus the competition between its economic players. The lack of accompanying measures by the State makes this vital reform for public finances that stop subsidizing the price of gasoline vulnerable. As all fuel products are imported, we will be interested in the evolution by making forecasts of the price of fuels in the Moroccan market. In this context, our paper aims mainly to study the selling price of diesel and gasoline in order to provide precise forecasts to the company and to respect the permissible error margin of 3%. To this end, we worked with a widely used approach for price forecasting: artificial neural networks technique (radial basis function). Recently, it is suggested to work with artificial neural networks in forecasting field as an alternative to the traditional linear methods. We developed a radial basis function network to come up with conclusions in terms of the superiority in forecasting performance. Consequently, the radial basis function technique proved its strength manifested in the error that was further minimized: 1.95% instead of 2.85% for autoregressive integrated moving average (ARIMA) model used in our previous work. The error is further minimized by applying radial basis function technique.

A Radial Basis Function Technique for the Early Detection and Measurement of Hip Implant Loosening

2020 ◽  
Author(s):  
Alexander Wiese ◽  
Ann DiGuglielmo ◽  
Jerico Mellet ◽  
Mckayla Rebillon ◽  
Shreekanth Mandayam ◽  
...  
Keyword(s):  
Early Detection ◽  
Radial Basis Function ◽  
Basis Function ◽  
Function Technique ◽  
Implant Loosening ◽  
Hip Implant ◽  
Radial Basis

Dual energy CT Angiographie der Becken Bein Region bei peripherer Verschlusskrankheit

2009 ◽  
Vol 181 (S 01) ◽  
Author(s):  
C Brockmann ◽  
S Jochum ◽  
K Huck ◽  
P Ziegler ◽  
M Sadick ◽  
...  
Keyword(s):  
Dual Energy ◽  
Dual Energy Ct ◽  
Ct Angiographie
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