DocumentCode :
2929672
Title :
The image Text Recognition Graph (iTRG)
Author :
Saidane, Zohra ; Garcia, Christophe ; Dugelay, Jean Luc
Author_Institution :
Orange Labs., Cesson-Sevigne, France
fYear :
2009
fDate :
June 28 2009-July 3 2009
Firstpage :
266
Lastpage :
269
Abstract :
This paper presents a graph based scheme for color text recognition in images and videos, which is particularly robust to complex background, low resolution or video coding artifacts. This scheme is based on a novel method named the image text recognition graph (iTRG) composed of five main modules: an image text segmentation module, a graph connection builder module, a character recognition module, a graph weight calculator module and an optimal path search module. The first two modules are based on convolutional neural networks so that the proposed system automatically learns how to robustly perform segmentation and recognition. The proposed method is evaluated on the public ICDAR 2003 test word dataset.
Keywords :
graph theory; image colour analysis; image recognition; image resolution; image segmentation; neural nets; text analysis; video coding; character recognition module; convolutional neural networks; image text recognition graph; low-resolution image; optimal path search; public ICDAR 2003 test word dataset; video coding; Character recognition; Image recognition; Image resolution; Image segmentation; Modular construction; Optical character recognition software; Robustness; Testing; Text recognition; Videos;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia and Expo, 2009. ICME 2009. IEEE International Conference on
Conference_Location :
New York, NY
ISSN :
1945-7871
Print_ISBN :
978-1-4244-4290-4
Electronic_ISBN :
1945-7871
Type :
conf
DOI :
10.1109/ICME.2009.5202486
Filename :
5202486
Link To Document :
بازگشت