Writing and drawing are basic forms of human communica- tion. Handwritten and hand-drawn documents are often used at initial stages of a project. For storage and later usage, handwritten documents are often converted into a digital format with a graphics program. Draw- ing with a computer in many cases requires skill and more time than less formal handwritten drawings. Even when people have experience in computer drawing and are familiar with the application, it takes time. Automatic conversion of images of hand-drawn diagrams into a digi- tal graphic format file could save time in the design process. One of early critical tasks in hand-drawn diagram interpretation is segmenta- tion of the diagram into text and non-text components. In this paper, we compare two approaches for offline text and non-text segmentation of contours in an image. We describe the feature extraction and classi- fication processes. Our methods obtain 82-86 % accuracy. Future work will explore the application of these techniques in a complete diagram interpretation system.
['Buntita Pravalpruk', 'Matthew M. Dailey']
Offline Text and Non-text Segmentation for Hand-Drawn Diagrams