A Comparison Between Stereo-Vision Techniques for the Reconstruction of 3-D Coordinates of Objects

This paper deals with the problems in setting up stereo-vision systems for contactless measurement of dimensional parameters in industrial environments. Two implicit calibration algorithms for the reconstruction of three-dimensional (3-D) real-world coordinates of objects from pairs of two-dimensional image coordinates have been implemented and compared. The former is based on a direct linear transformation, while the latter on an Artificial Neural Network (ANN). The results of the comparison made on artificial and real objects are finally reported in terms of statistical analysis of the reconstruction error

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