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Proceedings Paper

Text quality estimation in video
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Paper Abstract

Text quality can significantly affect the results of text detection and recognition in digital video. In this paper we address the problem of estimating text quality. The quality of text that appears in video is often much lower than that in document images, and can be degraded by factors such as low resolution, background variation, uneven lighting, motion of the text and camera, and in the case of scene text, projection from 3D. Features based on text resolution, background noise, contrast, illumination and texture are selected to describe the text quality, normalized and fed into a trained RBF network to estimate the text quality. The performance using different training schemes are compared.

Paper Details

Date Published: 18 December 2001
PDF: 12 pages
Proc. SPIE 4670, Document Recognition and Retrieval IX, (18 December 2001); doi: 10.1117/12.450732
Show Author Affiliations
Huiping Li, Univ. of Maryland/College Park (United States)
David Scott Doermann, Univ. of Maryland/College Park (United States)


Published in SPIE Proceedings Vol. 4670:
Document Recognition and Retrieval IX
Paul B. Kantor; Tapas Kanungo; Jiangying Zhou, Editor(s)

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