In a binary image contours may be seen as the discriminating curve between objects and background. Contours of connected components are always a Jordan curve. One symbol (e.g., a character) may consist of more than one such curve. Processing these curves is a one-dimensional task. Almost all common processing steps can be designed to work on contours rather than on the two-dimensional image. Moreover, contour processing gives new insight to well know problems and enables new processing steps or produces more information about the relations between connected components or objects of the image. The authors present preprocessing operations which work directly on the level of contours. Compared to the corresponding iconic operations, algorithms working on the contour level are mostly more efficient. Based on the contours of the connected components methods for filtering and slant normalization are described.


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    Title :

    Preprocessing raw binary images by means of contours


    Contributors:
    Braun, A. (author) / Caesar, T. (author) / Gloger, J.M. (author) / Mandler, E. (author)


    Publication date :

    1995-01-01


    Size :

    372903 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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