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Proceedings Paper

Detection of text strings from mixed text/graphics images
Author(s): Chien-Hua Tsai; Christos A. Papachristou
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Paper Abstract

A robust system for text strings separation from mixed text/graphics images is presented. Based on a union-find (region growing) strategy the algorithm is thus able to classify the text from graphics and adapts to changes in document type, language category (e.g., English, Chinese and Japanese), text font style and size, and text string orientation within digital images. In addition, it allows for a document skew that usually occurs in documents, without skew correction prior to discrimination while these proposed methods such a projection profile or run length coding are not always suitable for the condition. The method has been tested with a variety of printed documents from different origins with one common set of parameters, and the experimental results of the performance of the algorithm in terms of computational efficiency are demonstrated by using several tested images from the evaluation.

Paper Details

Date Published: 21 December 2000
PDF: 11 pages
Proc. SPIE 4307, Document Recognition and Retrieval VIII, (21 December 2000); doi: 10.1117/12.410838
Show Author Affiliations
Chien-Hua Tsai, Case Western Reserve Univ. (Taiwan)
Christos A. Papachristou, Case Western Reserve Univ. (United States)

Published in SPIE Proceedings Vol. 4307:
Document Recognition and Retrieval VIII
Paul B. Kantor; Daniel P. Lopresti; Jiangying Zhou, Editor(s)

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