Year: 2013
Type: preprint
Abstract: 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.
Source: arXiv (Cornell University)
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W194374481