DocumentCode :
2142745
Title :
Robust Vanishing Point Detection for MobileCam-Based Documents
Author :
Yin, Xu-Cheng ; Hao, Hong-Wei ; Sun, Jun ; Naoi, Satoshi
Author_Institution :
Dept. of Comput. Sci., Univ. of Sci. & Technol. Beijing, Beijing, China
fYear :
2011
fDate :
18-21 Sept. 2011
Firstpage :
136
Lastpage :
140
Abstract :
Document images captured by a mobile phone camera often have perspective distortions. In this paper, fast and robust vanishing point detection methods for such perspective documents are presented. Most of previous methods are either slow or unstable. Based on robust detection of text baselines and character tilt orientations, our proposed technology is fast and robust with the following features: (1) quick detection of vanishing point candidates by clustering and voting on the Gaussian sphere space, and (2) precise and efficient detection of the final vanishing points using a hybrid approach, which combines the results from clustering and projection analysis. The rectified image acceptance rate for Mobile Cam-based documents, signboards and posters is more than 98% with an average speed of about 100ms.
Keywords :
Gaussian processes; document image processing; mobile computing; object detection; pattern clustering; statistical analysis; text analysis; Gaussian sphere space; character tilt orientations; clustering analysis; mobile phone camera; mobilecam-based documents; projection analysis; robust vanishing point detection method; text baselines; Accuracy; Cameras; Estimation; Fitting; Mobile handsets; Robustness; Text analysis; MobileCam-based documents; Perspective document rectification; Vanishing point detection; clustering; the Gaussian sphere;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition (ICDAR), 2011 International Conference on
Conference_Location :
Beijing
ISSN :
1520-5363
Print_ISBN :
978-1-4577-1350-7
Electronic_ISBN :
1520-5363
Type :
conf
DOI :
10.1109/ICDAR.2011.36
Filename :
6065291
Link To Document :
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