DocumentCode :
2353343
Title :
Text identification in complex background using SVM
Author :
Chen, Datong ; Bourlard, Hervé ; Thiran, Jean-Philippe
Author_Institution :
Dalle Molle Inst. for Perceptual Artificial Intelligence, Switzerland
Volume :
2
fYear :
2001
fDate :
2001
Abstract :
The paper presents a fast and robust algorithm to identify text in image or video frames with complex backgrounds and compression effects. The algorithm first extracts the candidate text line on the basis of edge analysis, baseline location and heuristic constraints. Support Vector Machine (SVM) is then used to identify text line from the candidates in edge-based distance map feature space. Experiments based on a large amount of images and video frames from different sources showed the advantages of this algorithm compared to conventional methods in both identification quality and computation time.
Keywords :
data compression; edge detection; learning automata; optical character recognition; text analysis; video signal processing; SVM; Support Vector Machine; baseline location; candidate text line extraction; complex background; compression effects; computation time; edge analysis; edge-based distance map feature space; fast robust algorithm; heuristic constraints; identification quality; image frames; text identification; video OCR; video frames; Artificial intelligence; Clustering algorithms; Image coding; Image edge detection; Image segmentation; Robustness; Signal processing algorithms; Support vector machines; Video compression; Video signal processing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on
ISSN :
1063-6919
Print_ISBN :
0-7695-1272-0
Type :
conf
DOI :
10.1109/CVPR.2001.991021
Filename :
991021
Link To Document :
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