With the widespread and cheap availability of imaging devices (scanners, digital cameras, camera-equipped PDAs and cellular phones), and the rapid decrease in storage costs, individuals and organizations are acquiring and collecting vast amounts of image data. Yet, operating system and application software has not caught up with this development; imaging is still the domain of special-purpose applications.
The long-term goal of this project is to bridge the gap that currently exists between human and computer abilities to interpret image data and to make image understanding technologies an integral part of personal computing.
The initial goal of this work is to create a flexible toolbox for document layout analysis, optical character recognition, handwriting recognition, image matching, and content-based retrieval based on a class of geometric algorithms and statistical methods being developed in our group. This toolbox will also be demonstrated using a number of sample applications in document and image management, personal digital libraries, and context-aware information retrieval.
The toolbox will form the basis of our long-term research in image-based personal computing. Furthermore, it will be used as the foundation on which other projects, to be funded under additional external research grants, will be based.