Text Segmentation and Grouping in Tactile Graphic Production
by
Matt Renzelmann
Ideas are routinely communicated using a variety of techniques: words,
sounds, and images are but a few. Some of these techniques, however, are
ineffective if the person being communicated with has a disability, such as
blindness. In many science and engineering fields, blind persons face
tremendous obstacles in their effort to perceive such forms of communication
as diagrams, charts, and graphs. The primary goal of our research is to
develop computer software capable of automating the conversion of figures
and diagrams in a book to a tactile format that blind persons can readily
perceive. Among the challenges posed by this goal is the need to find and
remove text from the figures and diagrams for eventual conversion to
Braille. It is this challenge on which my work focuses. Since conventional
optical character recognition (OCR) software is poorly suited to the task of
finding short pieces of text embedded within images, we are exploring new
methods based on training and statistics. Because the figures and diagrams
in a book are of a similar style, we can exploit this similarity to improve
text recognition accuracy. The software we have written is able to
recognize a high percentage of the text once provided with a small training
set from which to base its predictions. We will discuss the techniques used
in our software and make comparisons with alternatives, such as existing
commercial OCR software.
Advised by Richard Ladner
CSE 403
Wednesday
April 20, 2005
3:30 - 4:20 pm