IMAGE DISTORTION CORRECTION FOR BIPRISM-BASED SINGLE-LENS STEREOVISION SYSTEM

Ph.DDOCTOR OF PHILOSOPH

Optimal calibration of a prism-based videoendoscopic system for precise 3D measurements

Modern videoendoscopes are capable of performing precise three-dimensional (3D) measurements of hard-to-reach elements. An attachable prism-based stereo adapter allows one to register images from two different viewpoints using a single sensor and apply stereoscopic methods. The key condition for achieving high measurement accuracy is the optimal choice of a mathematical model for calibration and 3D reconstruction procedures. In this paper, the conventional pinhole camera models with polynomial distortion approximation were analyzed and compared to the ray tracing model based on the vector form of Snell’s law. We, first, conducted a series of experiments using an industrial videoendoscope and utilized the criteria based on the measurement error of a segment length to evaluate the mathematical models considered. The experimental results confirmed a theoretical conclusion that the ray tracing model outperforms the pinhole models in a wide range of working distances. The results may be useful for the development of new stereoscopic measurement tools and algorithms for remote visual inspection in industrial and medical applications.The Russian Science Foundation (project #7-19-01355) financially supported the work. The authors thank A. Naumov, A. Shurygin and D. Khokhlov for continuous technical support

Single-lens multi-ocular stereovision using prism

Ph.DDOCTOR OF PHILOSOPH

Depth recovery and parameter analysis using single-lens prism based stereovision system

Ph.DDOCTOR OF PHILOSOPH

Depth Recovery with Rectification using Single-Lens Prism based Stereovision System

Ph.DDOCTOR OF PHILOSOPH

Segment-based stereo matching algorithm with rectification for single-lens bi-prism stereovision system

Ph.DDOCTOR OF PHILOSOPH

A Tutorial on Learning Human Welder\u27s Behavior: Sensing, Modeling, and Control

Human welder\u27s experiences and skills are critical for producing quality welds in manual GTAW process. Learning human welder\u27s behavior can help develop next generation intelligent welding machines and train welders faster. In this tutorial paper, various aspects of mechanizing the welder\u27s intelligence are surveyed, including sensing of the weld pool, modeling of the welder\u27s adjustments and this model-based control approach. Specifically, different sensing methods of the weld pool are reviewed and a novel 3D vision-based sensing system developed at University of Kentucky is introduced. Characterization of the weld pool is performed and human intelligent model is constructed, including an extensive survey on modeling human dynamics and neuro-fuzzy techniques. Closed-loop control experiment results are presented to illustrate the robustness of the model-based intelligent controller despite welding speed disturbance. A foundation is thus established to explore the mechanism and transformation of human welder\u27s intelligence into robotic welding system. Finally future research directions in this field are presented

Stereo Correspondence and Depth Recovery of Single-lens Bi-prism Based Stereovision System

Ph.DDOCTOR OF PHILOSOPH