Path-independent digital image correlation for mobile smart devices

Digital Image Correlation (2D DIC) techniques has been one of the most popular and important research topics in optical processing, and was applied to measure deformation of an object. Over the past three decades, many 2D DIC applications have been deployed into various platforms. However, none or few of the application have been deployed into mobile devices platform. The Path-independent DIC is a computational heavy algorithm, which is capable of achieving high accuracy, and time efficiency in full-field measurement of deformation by using of Fast Fourier Transform (FFT) to estimate initial guess for Inverse Compositional Gauss-Newton (IC-GN) algorithm. In order to improve the mobility and usability of this algorithm, a mobile application is designed and implemented for users to have an interactive data analysis experience through touch screen image manipulation. Although there is an impression that the mobile devices are limited in the capability to manipulate heavy computational task, this project demonstrates that with current multi-core design of the devices, it is capable to handle the processing of heavy algorithms, which may not be possible in the past. The details of the algorithm used and technical implementation information will be elaborated in this report. Furthermore, the experimental results will also be presented to illustrate correctness and efficiency of this current application.Bachelor of Engineering (Computer Science