Computer Science

Computer Science ›› 2023, Vol. 50 ›› Issue (11A): 221100170-5.doi: 10.11896/jsjkx.221100170

• Image Processing & Multimedia Technology • Previous Articles     Next Articles

Study on Prediction Modeling and Compensation of Circular Target Center Positioning Error Based on GA-BP

CHEN Haiyan1, ZHU Junlin1, WANG Ping2   

  1. 1 School of Computer and Communication,Lanzhou University of Technology,Lanzhou 730050,China
    2 School of Electrical Engineering and Information Engineering,Lanzhou University of Technology,Lanzhou 730050,China
  • Published:2023-11-09
  • About author:CHEN Haiyan,born in 1978,Ph.D,associate professor.Her main research interests include computer vision and small target detection.
  • Supported by:
    National Natural Science Foundation of China(62161019,62001198,62073161) and Gansu Youth Science and Technology Fund program(20JR10RA186).

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Abstract: When using circular target for camera calibration,the target imaging effect will be elliptical with different camera shooting positions,so the image circle center coordinates obtained by using the conventional circle center positioning method are not the real circle center imaging position in the image,and the calibration accuracy is not high when using the circle center image coordinates for camera calibration directly.To address this problem,a method is proposed to model the error prediction of circular target image circular center positioning error,and then carry out error compensation to improve the circular center positioning accuracy.Firstly,a simulated image set of circular target image is established.Secondly,the image is pre-processed and the ellipse fitting method is used to locate the circle center coordinates in the image.Thirdly,a GA-BP neural network is constructed and trained to establish the relationship model between the circle center localization error and the camera lens position.Finally,the error compensation strategy is used to compensate for the localized circle center coordinates.Experimental results show that the error prediction accuracy of the constructed GA-BP neural network model for the horizontal and vertical coordinates of the circular center positioning is significantly better than that of the BP or E-R models,with MAPE,RMSE,and R2 of 5.51%,0.004 8,0.999 6and 6.14%,0.096 4,0.999 8,respectively.The accuracy of the circular center positioning after error compensation is higher,which verifies the feasibility of using error prediction modeling and error compensation to improve the accuracy of circular center positioning,and provides method support for the high-precision camera calibration task.

Key words: Circular target, Ellipse fitting, Circular center positioning error, Predictive modeling, BP neural network, Genetic algorithm, Error compensation

CLC Number: 

  • TP391
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