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2001 IEEE International Conference on Multimedia and Expo (ICME'01)
A VIDEO TEXT DETECTION AND RECOGNITION SYSTEM
Tokyo, Japan
August 22-August 25
ISBN: 0-7695-1198-8
ASCII Text
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Jie Xi, Xian-Sheng Hua, Xiang-Rong Chen, Liu Wenyin, Hong-Jiang Zhang, "A VIDEO TEXT DETECTION AND RECOGNITION SYSTEM," Multimedia and Expo, IEEE International Conference on, pp. 222, 2001 IEEE International Conference on Multimedia and Expo (ICME'01), 2001.
 
 
BibTex
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@article{ 10.1109/ICME.2001.1237861,
author = {Jie Xi and Xian-Sheng Hua and Xiang-Rong Chen and Liu Wenyin and Hong-Jiang Zhang},
title = {A VIDEO TEXT DETECTION AND RECOGNITION SYSTEM},
journal ={Multimedia and Expo, IEEE International Conference on},
volume = {0},
year = {2001},
isbn = {0-7695-1198-8},
pages = {222},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICME.2001.1237861},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Multimedia and Expo, IEEE International Conference on
TI - A VIDEO TEXT DETECTION AND RECOGNITION SYSTEM
SN - 0-7695-1198-8
SP
EP
A1 - Jie Xi,
A1 - Xian-Sheng Hua,
A1 - Xiang-Rong Chen,
A1 - Liu Wenyin,
A1 - Hong-Jiang Zhang,
PY - 2001
KW - null
VL - 0
JA - Multimedia and Expo, IEEE International Conference on
ER -
 
Jie Xi, Department of Computer Science Fudan University, Shanghai 200433, China
Xian-Sheng Hua, National Lab. on Machine Perception Peking University, Beijing 100871, China
Xiang-Rong Chen, Microsoft Research China
Liu Wenyin, Microsoft Research China
Hong-Jiang Zhang, Microsoft Research China
In this paper, we propose a new system for text information extraction from news videos. First of all, a method that integrates text detecting and text tracking is developed to locate text areas in the key-frames (images), together with a scheme to evaluate the performance of this approach. To get better recognition results, we then enhance the quality of the detected text blocks by multi-frame averaging. Finally, we use an adaptive thresholding method to binarize the text blocks and recognize the text using an off-the-shelf OCR module. The detection and recognition rate of the proposed system are 94.7% and 67.5% respectively.
Citation:
Jie Xi, Xian-Sheng Hua, Xiang-Rong Chen, Liu Wenyin, Hong-Jiang Zhang, "A VIDEO TEXT DETECTION AND RECOGNITION SYSTEM," icme, pp.222, 2001 IEEE International Conference on Multimedia and Expo (ICME'01), 2001
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