RESOLUTION ADJUSTMENT OF AN IMAGE THAT INCLUDES TEXT UNDERGOING AN OCR PROCESS

An optical character recognition process characterizes text lines in a textual image by their base-line, mean-line and x-height. The base-line for at least one text line in the image is determined by finding a parametric curve that maximizes a first fitness function that depends on the values of pix...

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Bibliographic Details
Main Authors DRESEVIC, Bodin, NIJEMCEVIC, Djordje, VUGDELIJA, Milan
Format Patent
LanguageEnglish
French
German
Published 26.04.2017
Subjects
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Summary:An optical character recognition process characterizes text lines in a textual image by their base-line, mean-line and x-height. The base-line for at least one text line in the image is determined by finding a parametric curve that maximizes a first fitness function that depends on the values of pixels through which the parametric curve passes and pixels below the parametric curve. The base-line corresponds to the parametric curve for which the first fitness function is maximized. The first fitness function is designed so that it increases with increasing lightless or brightness of pixels immediately below the parametric curve while also increasing with decreasing lightness of pixels through which the parametric curve passes. The mean-line is determined by incrementally shifting the base-line upward by predetermined amounts (e.g., a single pixel) until a second fitness function for the shifted base-line is maximized. The second fitness function is essentially the inverse of the first fitness function. Specifically, the second fitness function increases with increasing lightless of pixels immediately above the shifted base-line while also increasing with decreasing lightness of pixels through which the shifted base-line passes. The x-height is equal to the sum of the predetermined amounts by which the base-line is shifted upward in order to maximize the second fitness function. In some cases different groups of text-lines in the textual image may be characterized differently from one another. For example, each group may be characterized by a most probable x-height for that group.
Bibliography:Application Number: EP20110753864