DocumentCode :
178459
Title :
Real-Time Scene Text Detection Based on Stroke Model
Author :
Yi Liu ; Dongming Zhang ; Yongdong Zhang ; Shouxun Lin
Author_Institution :
Key Lab. of Intell. Inf. Process., Inst. of Comput. Technol., Beijing, China
fYear :
2014
fDate :
24-28 Aug. 2014
Firstpage :
3116
Lastpage :
3120
Abstract :
In this paper we bring forth a novel stroke-based method which is simple and effective to detect texts in natural scenes. We first introduce a general mathematical model to describe character strokes from the perspective of the scale space along with difference of Gaussian filters. Then we detail a text line aggregation approach utilizing the inherent text layout. Afterwards, we set up the whole scheme with three main steps, i.e. stroke extraction, text line aggregation and verification. Finally, experiments show the advantage of our method. As strokes are considered to be the fundamental component of characters, compared to edge- or other connected-component-based methods, our method is much more reasonable.
Keywords :
filtering theory; statistical analysis; text detection; Gaussian filters; connected-component-based methods; edge-component-based methods; general mathematical model; novel stroke-based method; real-time scene text detection; stroke extraction; text line aggregation; text line aggregation approach; Computer vision; Feature extraction; Image edge detection; Kernel; Layout; Pattern recognition; Semantics; character layout; scene text detection; stroke feature;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition (ICPR), 2014 22nd International Conference on
Conference_Location :
Stockholm
ISSN :
1051-4651
Type :
conf
DOI :
10.1109/ICPR.2014.537
Filename :
6977249
Link To Document :
بازگشت