Dynamics-Based Motion Deblurring Improves the Performance of Optical Character Recognition During Fast Scanning of a Robotic Eye

This paper presents a quantitative evaluation of the dynamics-based deblurring method using an optical character recognition (OCR) technology. Although various image deblurring algorithms have been studied, there has been no standard performance metric; deblurred images have often been evaluated in a qualitative manner. In this study, blurry images containing alphanumeric characters were obtained in the course of rapid motion using a robotic vision system. The obtained blurry images were recovered by the dynamics-based deblurring method. For a quantitative evaluation, OCR rates from the deblurred images by the dynamics-based method were calculated and compared with those by other well-known methods. Experiment results show that the dynamics-based method has the best quantitative results.