DocumentCode :
652551
Title :
Research on Born-Digital Image Text Extraction Based on Conditional Random Field
Author :
Jian Zhang ; Renhong Cheng ; Kai Wang ; Hong Zhao ; Jiao Jiao
Author_Institution :
Coll. of Inf. Tech. Sci., Nankai Univ., Tianjin, China
fYear :
2013
fDate :
28-30 Oct. 2013
Firstpage :
364
Lastpage :
368
Abstract :
Born-digital images are generated directly with the computer, the text in the images is important for fully understanding the images. Although there are many methods having been proposed over the past years for text extraction from natural scene images, text detection and extraction from born-digital images are still a challenge. This paper proposed an algorithm of text extraction from born-digital images based on conditional random field (CRF). CRF model not only considers unary component properties and binary contextual component relationships, but also learn parameter s with supervised. This paper combines features and relationships within the CRF framework and the experiment results show that this algorithm can extract text effectively from the born-digital images.
Keywords :
statistical analysis; text detection; CRF model; born-digital image text extraction; conditional random field; image understanding; natural scene images; text detection; Data mining; Digital images; Educational institutions; Feature extraction; Gray-scale; Image segmentation; Wavelet transforms; Binarization; Conditional Random Field; Connect Component; Text Extraction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC), 2013 Eighth International Conference on
Conference_Location :
Compiegne
Type :
conf
DOI :
10.1109/3PGCIC.2013.62
Filename :
6681255
Link To Document :
بازگشت