DocumentCode :
2179792
Title :
Graph-Based Text Segmentation Using a Selected Channel Image
Author :
Zeng, Chao ; Jia, Wenjing ; He, Xiangjian ; Yang, Jie
Author_Institution :
FEIT, iNEXT, Univ. of Technol., Sydney, Sydney, NSW, Australia
fYear :
2010
fDate :
1-3 Dec. 2010
Firstpage :
535
Lastpage :
539
Abstract :
This paper proposes a graph-based method for segmentation of a text image using a selected colour-channel image. The text colour information usually presents a two polarity trend. According to the observation that the histogram distributions of the respective colour channel images are usually different from each other, we select the colour channel image with the histogram having the biggest distance between the two main peaks, which represents the main foreground colour strength and background colour strength respectively. The peak distance is estimated by the mean-shift procedure performed on each individual channel image. Then, a graph model is constructed on a selected channel image to segment the text image into foreground and background. The proposed method is tested on a public database, and its effectiveness is demonstrated by the experimental results.
Keywords :
graph theory; image colour analysis; image segmentation; text analysis; background colour strength; colour-channel image; foreground colour strength; graph-based text segmentation; histogram distribution; mean-shift procedure; peak distance estimation; selected channel image; text image segmentation; Histograms; Image color analysis; Image segmentation; Kernel; Lighting; Pixel; Text recognition; colour channel image; graph cut; histogram; mean-shift; text segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Image Computing: Techniques and Applications (DICTA), 2010 International Conference on
Conference_Location :
Sydney, NSW
Print_ISBN :
978-1-4244-8816-2
Electronic_ISBN :
978-0-7695-4271-3
Type :
conf
DOI :
10.1109/DICTA.2010.95
Filename :
5692616
Link To Document :
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