Document image de-warping for text/graphics recognition

Abstract

Document analysis and graphics recognition algorithms are normally applied to the processing of images of 2D documents scanned when flattened against a planar surface. Technological advancements in recent years have led to a situation in which digital cameras with high resolution are widely available. Consequently, traditional graphics recognition tasks may be updated to accommodate document images captured through a hand-held camera in an uncontrolled environment. In this paper the problem of perspective and geometric deformations correction in document images is discussed. The proposed approach uses the texture of a document image so as to infer the document structure distortion. A two-pass image warping algorithm is then used to correct the images. In addition to being language independent, the proposed approach may handle document images that include multiple fonts, math notations, and graphics. The de-warped images contain less distortions and so are better suited for existing text/graphics recognition techniques.