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Author Cunzhao Shi ♦ Chunheng Wang ♦ Baihua Xiao ♦ Yang Zhang ♦ Song Gao ♦ Zhong Zhang
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2013
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Character recognition ♦ Cost function ♦ Text recognition ♦ Computational modeling ♦ Feature extraction ♦ Training ♦ Computer vision
Abstract Scene text recognition has inspired great interests from the computer vision community in recent years. In this paper, we propose a novel scene text recognition method using part-based tree-structured character detection. Different from conventional multi-scale sliding window character detection strategy, which does not make use of the character-specific structure information, we use part-based tree-structure to model each type of character so as to detect and recognize the characters at the same time. While for word recognition, we build a Conditional Random Field model on the potential character locations to incorporate the detection scores, spatial constraints and linguistic knowledge into one framework. The final word recognition result is obtained by minimizing the cost function defined on the random field. Experimental results on a range of challenging public datasets (ICDAR 2003, ICDAR 2011, SVT) demonstrate that the proposed method outperforms state-of-the-art methods significantly both for character detection and word recognition.
Description Author affiliation: State Key Lab. of Manage. & Control for Complex Syst., CASIA, Beijing, China (Cunzhao Shi; Chunheng Wang; Baihua Xiao; Yang Zhang; Song Gao; Zhong Zhang)
ISBN 9780769549897
ISSN 10636919
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2013-06-23
Publisher Place USA
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 723.15 kB
Page Count 8
Starting Page 2961
Ending Page 2968

Source: IEEE Xplore Digital Library