Published October 25, 2017
We present an overview of two decades of innovation in handwriting recognition at the Govindaraju lab at the University at Buffalo and offer a perspective on the evolution of research in this area and the future of the field.
We highlight our seminal work in handwriting recognition that was at the core of the first handwritten address interpretation system used by the U.S. Postal Service, described as one of the first practical success stories of AI (Daphne Koller, Stanford, at the CCC symposium on Computing Research that changed the World) and as a shining example of AI for the Social Good (Eric Horvitz, Microsoft Research).
We journey through the HWR landscape, from lexicon-based to lexicon-free approaches, and from heuristics-driven techniques to the principled methodologies that we introduced. We explore a sample of the variety of impactful applications that resulted from our research, from the processing of healthcare forms for the NYS Department of Health for deriving early indicators of outbreaks, to access to historical documents through word spotting, transcript mapping and other indexing schemes for digital libraries, to award-winning pre-processing techniques and multilingual OCR solutions for automated machine translation for armed forces in the theater. We introduce the novel concept of accents in handwriting and our pioneering use of handwritten CAPTCHAs to enhance security. We end with a look at some of the challenging problems that we are working on in the digital humanities space and new ideas to explore such as the potential use of whiteboard recognition technologies in the flipped classroom setting.
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