The Optimization of Binocular Vision Measurement Based on Non-Minimal Suppression
The accuracy of visual measurements is limited by inherent errors within the system.A novel approach based on the RANSAC non-minimal error suppression model was proposed to enhance the precision and robustness of binocular visual meas-urements.Building upon the traditional binocular measurement model,a least squares error evaluation function was introduced to quantify the measurement errors using spatial reference points.The proposed error evaluation function was employed as the objective function for model optimization through iterative RANSAC processes,resulting in the optimal model with minimum total error.Ex-perimental results demonstrated that compared to the traditional model,the proposed method achieved a reduction in maximum error from 0.359 mm to 0.200 mm,and an average error decreased from 0.186 mm to 0.115 mm.This corresponded to an error suppres-sion rate of 38.2%.The proposed method can improve the accuracy and reliability of binocular measurement system,and holds sig-nificant potential for widespread applications in the field of precise visual measurements.
万方数据
维普
