Reading Ancient Coin Legends: Object Recognition vs. OCR

نویسندگان

  • Albert Kavelar
  • Sebastian Zambanini
  • Martin Kampel
چکیده

Standard OCR is a well-researched topic of computer vision and can be considered solved for machine-printed text. However, when applied to unconstrained images, the recognition rates drop drastically. Therefore, the employment of object recognition-based techniques has become state of the art in scene text recognition applications. This paper presents a scene text recognition method tailored to ancient coin legends and compares the results achieved in character and word recognition experiments to a standard OCR engine. The conducted experiments show that the proposed method outperforms the standard OCR engine on a set of 180 cropped coin legend words.

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عنوان ژورنال:
  • CoRR

دوره abs/1304.7184  شماره 

صفحات  -

تاریخ انتشار 2013