Processing of huge volumes of unprocessed, handwritten and historical documents is a critical challenge in front of many heritage and cultural institutes and organizations. Our main objective in the field of document image processing and understanding is development and implementation of novel models and techniques which may help in generating, enhancing, presenting and understanding of handwritten document images. Direct involvement of scholars and researchers from various institutes and universities, such as McGill University, allowed us to choose goal-oriented directions for our research and development. Currently, our focus is on providing a complete understanding system which consists of imaging, pre-processing/enhancement, word-spotting, transliteration and data mining units in an user-friendly collaborative and virtual environment.

In terms of imaging, multi-spectral infra-red imaging is considered toward almost-true virtual replacements for physical historical documents. Enhancement, image segmentation and binarization, and line and word segmentation are under extensive study in the preprocessing part. At the understanding level, we are working on both word spotting and transliteration using innovative methods which are segmentation-free and explore new directions in this field. For a sample list of our works, please see the below. We also welcome collaboration at any level.