DocumentCode :
2795296
Title :
A low complexity method for detection of text area in natural images
Author :
Bouman, Katherine L. ; Abdollahian, Golnaz ; Boutin, Mireille ; Delp, Edward J.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Univ. of Michigan, Ann Arbor, MI, USA
fYear :
2010
fDate :
14-19 March 2010
Firstpage :
1050
Lastpage :
1053
Abstract :
We propose a low complexity method for segmentation of text regions in natural images. This algorithm is designed for mobile applications (e.g. unmanned or hand-held devices) in which computational and energy resources are limited. No prior assumption is made regarding the text size, font, language, character set or the camera angle. However, the text is assumed to be located on a piecewise homogeneous background with a contrasting color. We have deployed our method on a Nokia N800 Internet tablet as part of a system for automatic detection and translation of outdoor signs. Our experiments show that the 0.3 megapixel images taken by the phone camera can be accurately segmented within the device in a fraction of a second.
Keywords :
computational complexity; image recognition; text analysis; Internet tablet; hand held devices; low complexity method; mobile applications; natural images; text area detection; text regions; Algorithm design and analysis; Application software; Cameras; Handheld computers; Image edge detection; Image processing; Image segmentation; Laboratories; Mobile computing; Power engineering and energy; Mobile Devices; Sign Detection; Text Detection; Text Segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on
Conference_Location :
Dallas, TX
ISSN :
1520-6149
Print_ISBN :
978-1-4244-4295-9
Electronic_ISBN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2010.5495331
Filename :
5495331
Link To Document :
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