Video is an increasingly important source of information to the intelligence analyst. Recognizing text that appears in real-world scenery is potentially useful for characterizing the contents of video imagery. Previous research in text recognition for both printed documents and other sources of imagery has generally assumed that the text lies in a plane that is oriented roughly perpendicular to the optical axis of the camera. However, text such as street signs, name plates, and billboards appearing in captured video imagery often lies in a plane that is oriented at an oblique angle. SRI International (SRI) is developing an approach that takes advantage of 3-D scene geometry to detect the orientation of the plane on which text is printed. The text recognition process will then be able to transform the video image of the text to a normalized coordinate system before performing OCR, yielding more robust recognition performance. Our approach applies full-perspective projections and image-to-image homographies that capture the appearance of a plane viewed through perspective optics. We describe our approach and present some preliminary results. PROBLEM STATEMENT
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