Neural network-based text location for news video indexing
Ki-Young Jeong
Keechul Jung
Eun Yi Kim
Hang Joon Kim
Artificial Intelligence Lab., Kyungpook Nat. Univ., Taegu;
This paper appears in: Image Processing, 1999. ICIP 99. Proceedings. 1999 International Conference on
Publication Date: 1999
Volume: 3,
On page(s): 319-323 vol.3
Meeting Date: 10/24/1999 - 10/28/1999
Location: Kobe, Japan
ISBN: 0-7803-5467-2
References Cited: 6
INSPEC Accession Number: 6521898
Digital Object Identifier: 10.1109/ICIP.1999.817127
Current Version Published: 2002-08-06
Abstract
The retrieval of video clips from multimedia databases has been
increasingly spotlighted. Texts in videos include useful information for
automatic annotation or indexing. Text location is the first step for
recognizing the textual information. This paper proposes a neural
network-based text location method for news video indexing. Text can be
characterized by texture, location, alignment, and font size. The
proposed method classifies text pixels and non-text pixels using a
network that operates as a set of texture discrimination filters. We
find and locate text regions using histogram analysis after removing
errors in the classification results. Experimental results show that the
proposed method is effective at locating texts
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