TEXT SEGMENTATION FROM WEB IMAGES USING TWO-LEVEL VARIANCE MAPS

Insook Jung, Il-Seok Oh

2009

Abstract

Variance map can be used to detect and distinguish texts from the background in images. However previous variance maps work as one level and they revealed a limitation in dealing with diverse size, slant, orientation, translation and color of texts. In particular, they have difficulties in locating texts of large size or texts with severe color gradation due to specific value in mask sizes. We present a method of robustly segmenting text regions in complex web color images using two-level variance maps. The two-level variance maps works hierarchically. The first level finds the approximate locations of text regions using global horizontal and vertical color variances with the specific mask sizes. Then the second level segments each text region using intensity variation with a local new mask size, in which a local new mask size is determined adaptively. By the second process, backgrounds tend to disappear in each region and segmentation can be accurate. Highly promising experimental results have been obtained using the our method in 400 web images.

References

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Paper Citation


in Harvard Style

Jung I. and Oh I. (2009). TEXT SEGMENTATION FROM WEB IMAGES USING TWO-LEVEL VARIANCE MAPS . In Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2009) ISBN 978-989-8111-69-2, pages 363-370. DOI: 10.5220/0001808303630370


in Bibtex Style

@conference{visapp09,
author={Insook Jung and Il-Seok Oh},
title={TEXT SEGMENTATION FROM WEB IMAGES USING TWO-LEVEL VARIANCE MAPS },
booktitle={Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2009)},
year={2009},
pages={363-370},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001808303630370},
isbn={978-989-8111-69-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2009)
TI - TEXT SEGMENTATION FROM WEB IMAGES USING TWO-LEVEL VARIANCE MAPS
SN - 978-989-8111-69-2
AU - Jung I.
AU - Oh I.
PY - 2009
SP - 363
EP - 370
DO - 10.5220/0001808303630370