Intelligent High level Video Processing (II)
Date Issued
2004-07-31
Date
2004-07-31
Author(s)
DOI
922219E002016
Abstract
In order to achieve good translating performance, we propose
a novel approach to detect text in color images with very low
false alarm rate. First of all, neural network color quantization is
used to compact text color. Second, 3D histogram analysis
chooses several colors candidates, and then extracted each of
these color candidates to obtain several bi-level images. For each
extracted bi-level image, connected component analysis and
several morphological operators are fed to hold some boxes that
are possible text regions. At last, we can use L.O.G edge
detector to authenticate accurate text regions from each possible
text regions. Meanwhile, in complex color images,
multiquantization layers can be integrated to reject non-text parts
and reduce false alarm rate.
Subjects
Text detection
color quantization
color images
neural network
Publisher
臺北市：國立臺灣大學電機工程學系暨研究所
Type
report
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