DocumentCode :
163195
Title :
Saliency-weighted holistic scene text recognition for unseen place categorization
Author :
Thammasorn, Phawis ; Patanukhom, Karn ; Pimup, Rapeeporn
Author_Institution :
Dept. of Comput. Eng., Chiang Mai Univ., Chiang Mai, Thailand
fYear :
2014
fDate :
14-16 May 2014
Firstpage :
12
Lastpage :
17
Abstract :
An improvement in framework for unseen place categorization using scene text is proposed. Category score calculation using visual saliency weighting method is proposed to cope with problem of different importance of word locations on scene images. Additionally, a HOG feature extraction using sliding window is proposed to obtain better holistic word recognition on scene images. As the result, the proposed method outperforms PHOG baseline in unseen place categorization with greater than 10 % improvement in the accuracy.
Keywords :
character recognition; feature extraction; HOG feature extraction; category score calculation; holistic word recognition; saliency-weighted holistic scene text recognition; sliding window; unseen place categorization; visual saliency weighting method; word locations; HOG feature; Holistic Scene Text Recognition; Sliding window; Unseen Place Categorization; Visual Saliency;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Software Engineering (JCSSE), 2014 11th International Joint Conference on
Conference_Location :
Chon Buri
Print_ISBN :
978-1-4799-5821-4
Type :
conf
DOI :
10.1109/JCSSE.2014.6841834
Filename :
6841834
Link To Document :
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