Image Registration in Centrifuge-Based Adhesive Fracture Testing

This thesis investigates the application of image registration techniques in centrifuge-based adhesive fracture testing, aiming to develop a framework for fully automated analysis of adhesive joints. Adhesive bonding is widely used in various industries, yet the evaluation of adhesive performance remains challenging, particularly in aligning fractured surfaces for analysis. The proposed framework utilizes image registration algorithms to automate the alignment process, enhancing the accuracy and efficiency of fracture pattern classification. A comprehensive evaluation of different algorithms shows that gradient descent-based optimization methods, particularly those utilizing Mutual Information (MI) as a distance measure, yield the most reliable results. This work not only contributes to the automation of fracture analysis but also provides insights into the integration of image registration techniques into standard adhesive testing procedures, ultimately promoting the reliability and consistency of adhesive evaluations.