Textual Information Access for the Visually Impaired

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An ever-increasing segment of the population suffers from low vision resulting from complications of disease and old age. Surveys conducted by one of the Co-PIs as part of a previous project have determined, that the key information which is not available to people with low vision is textual information, usually of a directive or warning nature. For example, shopping in a large department store in a mall might involve looking for signs indicating where the store is, reading aisle signs in the store, and looking at product names, at labels and prices. This research will develop a "seeing-eye" computer to help people with low vision to observe and receive such information, so that they can participate more efficiently and comfortably in every day activities, and thereby lead more fulfilling and productive lives. The system will be composed of a digital video camera, computer, user interface, and speech or magnified visual output that can detect textual information in the environment, understand it using OCR, and provide it to the user who either has low vision or is blind. To achieve these goals, the PIs will in collaboration with colleagues at Johns Hopkins University build, over the first six months and then over the first two years, prototype systems using mostly existing technology and extensions to vision algorithms we have developed for identification of text regions in images and OCR, which can be evaluated on volunteer patients at the Wilmer Ophthalmological Institute and the National Federation for the Blind.. The functionality and range of applicability of our prototypes will necessarily be limited. Simultaneously, the PIs will work on long-term research problems that must be addressed to develop next generation seeing-eye computers with greater scalability and capability. In year three patient-volunteers at Wilmer and at the NFB will perform evaluations of the developed prototypes Subsequently, successful results will be commercialized and brought to the larger patient body (as have previous developments at Wilmer). Fundamental research problems to be addressed include: real-time algorithms for detection and rectification of text on planes and cylinders subject to perspective distortions; OCR from digital video, and OCR for text on textured backgrounds; and more robust and efficient algorithms and systems for stabilization and super-resolution of text blocks from video streams.