A Robust Algorithm for Text String Separation from Mixed Text/Graphics Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Use of the Hough transformation to detect lines and curves in pictures
Communications of the ACM
An Overview of the Tesseract OCR Engine
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02
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Common OCR (Optical Character Recognition) systems fail to detect and recognize small text strings of few characters, in particular when a text line is not horizontal. Such text regions are typical for chart images. In this paper we present an algorithm that is able to detect small text regions regardless of string orientation and font size or style. We propose to use this algorithm as a preprocessing step for text recognition with a common OCR engine. According to our experimental results, one can get up to 20 times better text recognition rate, and 15 times higher text recognition precision when the proposed algorithm is used to detect text location, size and orientation, before using an OCR system. Experiments have been performed on a benchmark set of 1000 chart images created with the XML/SWF Chart tool, which contain about 14000 text regions in total.