Script-agnostic reflow of text in document images
- Saurabh Panjwani ,
- Abhinav Uppal ,
- Ed Cutrell
MobileHCI 2011: Proceedings of the 13th International Conference on Human Computer Interaction with Mobile Devices and Services |
Published by ACM
Reading text from document images can be difficult on mobile devices due to the limited screen width available on them. While there exist solutions for reflowing Latin-script texts on such devices, these solutions do not work well for images of other scripts or combinations of scripts, since they rely on script-specific characteristics or OCR. We present a technique that reflows text in document images in a manner that is agnostic to the script used to compose them. Our technique achieved over 95% segmentation accuracy for a corpus of 139 images containing text in 4 genetically-distant languages—English, Hindi, Kannada and Arabic. A preliminary user study with a prototype implementation of the technique provided evidence of some of its usability benefits.