DocumentCode :
3140774
Title :
Visual Text Features for Image Matching
Author :
Tsai, Shauhyuarn Sean ; Huizhong Chen ; Chen, D. ; Parameswaran, Vinod ; Grzeszczuk, R. ; Girod, B.
Author_Institution :
Dept. of Electr. Eng., Stanford Univ., Stanford, CA, USA
fYear :
2012
fDate :
10-12 Dec. 2012
Firstpage :
408
Lastpage :
412
Abstract :
We present a new class of visual text features that are based on text in camera phone images. A robust text detection algorithm locates individual text lines and feeds them to a recognition engine. From the recognized characters, we generate the visual text features in a way that resembles image features. We calculate their location, scale, orientation, and a descriptor that describes the character and word information. We apply visual text features to image matching. To disambiguate false matches, we developed a word-distance matching method. Our experiments with image that contain text show that the new visual text feature based image matching pipeline performs on par or better than a conventional image feature based pipeline while requiring less than 10 bits per feature. This is 4.5× smaller than state-of-the-art visual feature descriptors.
Keywords :
feature extraction; image matching; text detection; camera phone images; character information; image feature based pipeline; image matching; recognition engine; text detection algorithm; text lines; visual feature descriptors; visual text features; word information; word-distance matching method; Character recognition; Feature extraction; Image coding; Image matching; Pipelines; Text recognition; Visualization; visual search; visual text features;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia (ISM), 2012 IEEE International Symposium on
Conference_Location :
Irvine, CA
Print_ISBN :
978-1-4673-4370-1
Type :
conf
DOI :
10.1109/ISM.2012.84
Filename :
6424698
Link To Document :
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