OCR binarization and image pre-processing for searching historical documents

• Published in: Pattern recognition Vol. 40; no. 2; pp. 389 - 397
• Main Authors: Gupta, Maya R., Jacobson, Nathaniel P., Garcia, Eric K.
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01-02-2007; Elsevier Science
• Subjects: Applied sciences; Binarization; Detection, estimation, filtering, equalization, prediction; Exact sciences and technology; Halftoning; Image processing; Information, signal and communications theory; Miscellaneous; Multiresolutional; OCR; Pattern recognition; Signal and communications theory; Signal processing; Signal, noise; Telecommunications and information theory; Halftoning; Binarization; Multiresolutional; OCR; Performance evaluation; Filtering; Keyword; Image processing; Dithering; Noise reduction; Pattern recognition; Printed document; Multiresolution analysis; Implementation; Despeckling; Optical character recognition; Binary image; Signal processing; Error diffusion
• ISSN: 0031-3203; 1873-5142
• DOI: 10.1016/j.patcog.2006.04.043

We consider the problem of document binarization as a pre-processing step for optical character recognition (OCR) for the purpose of keyword search of historical printed documents. A number of promising techniques from the literature for binarization, pre-filtering, and post-binarization denoising were implemented along with newly developed methods for binarization: an error diffusion binarization, a multiresolutional version of Otsu's binarization, and denoising by despeckling. The OCR in the ABBYY FineReader 7.1 SDK is used as a black box metric to compare methods. Results for 12 pages from six newspapers of differing quality show that performance varies widely by image, but that the classic Otsu method and Otsu-based methods perform best on average.