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Proceedings Paper

Text location in color documents
Author(s): Anil K. Jain; Anoop M. Namboodiri; Keechul Jung
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Paper Abstract

Many document images contain both text and non-text (images, line drawings, etc.) regions. An automatic segmentation of such an image into text and non-text regions is extremely useful in a variety of applications. Identification of text regions helps in text recognition applications, while the classification of an image into text and non-text regions helps in processing the individual regions differently in applications like page reproduction and printing. One of the main approaches to text detection is based on modeling the text as a texture. We present a method based on a combination of neural networks (texture-based) and connected component analysis to detect text in color documents with busy foreground and background. The proposed method achieves an accuracy of 96% (by area) on a test set of 40 documents.

Paper Details

Date Published: 13 January 2003
PDF: 8 pages
Proc. SPIE 5010, Document Recognition and Retrieval X, (13 January 2003); doi: 10.1117/12.476021
Show Author Affiliations
Anil K. Jain, Michigan State Univ. (United States)
Anoop M. Namboodiri, Michigan State Univ. (United States)
Keechul Jung, SungKyunKwan Univ. (South Korea)


Published in SPIE Proceedings Vol. 5010:
Document Recognition and Retrieval X
Tapas Kanungo; Elisa H. Barney Smith; Jianying Hu; Paul B. Kantor, Editor(s)

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