Thursday Extra: A robust system for discovering text baselines in scene text images

On Thursday, October 6, Zach Butler '13 and Dugan Knoll '12, will present a talk in the "Thursday Extra" series on their summer research:

Scientists have been working in the field of text recognition, the science of automatically reading text, for over 200 years. While the problem of reading whole documents (commonly called OCR, or optical character recognition) is more or less solved, the problem of reading text from arbitrary real-world scenes (Scene Text Recognition, or STR) still presents researchers with many challenges. Yet humans have been able to read such text ever since we created language. Many have created a robust recognition programs, but some still suffer from not knowing where the text baseline is—that is, where the non-descending characters of a line of text end. In this talk, we will discuss what makes reading scene text so difficult, how we made a baseline detection algorithm to improve the results of scene text recognition systems, and how we used the scientific method to make our system as robust as possible in ten weeks.

Refreshments will be served at 4:15 p.m. in the Computer Science Commons (Noyce 3817). The talk, "A robust system for discovering text baselines in scene text images," will follow at 4:30 p.m. in Noyce 3821. Everyone is welcome to attend.