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Recognition of text with known geometric and grammatical structure
|Ranchordas, A.-K.N. ; Institute for Systems and Technologies of Information, Control and Communication -INSTICC-, Setubal:|
Third International Conference on Computer Vision Theory and Applications, VISAPP 2008. Proceedings. Vol.2 : Funchal, Madeira, Portugal, 22 - 25 January 2008
Setúbal: INSTICC Press, 2008
|International Conference on Computer Vision Theory and Applications (VISAPP) <3, 2008, Funchal>|
| Conference Paper|
|Fraunhofer FIRST ()|
The optical character recognition (OCR) module is a fundamental part of each automated text processing system. The OCR module translates an input image with a text line into a string of symbols. In many applications (e.g. license plate recognition) the text has some a priori known geometric and grammatical structure. This article proposes an OCR method exploiting this knowledge which restricts the set of possible strings to a limited set of feasible combinations. The recognition task is formulated as maximization of a similarity function which uses character templates as reference. These templates are estimated by a support vector machine method from a set of examples. In contrast to the common approach, the proposed method performs character segmentation and recognition simultaneously. The method was successfully evaluated in a car license plate recognition system.