Title :
A New Block Partitioned Text Feature for Text Verification
Author :
Wang, Xiufei ; Huang, Lei ; Liu, Changping
Author_Institution :
Inst. of Autom., Chinese Acad. of Sci..China, China
Abstract :
In this paper, a new feature for text verification is proposed. The difficulties for the selection of features for text verification (FTV) are first discussed, followed by two principles for the FTV: the FTV should minimize the influence of backgrounds, and it should also be expressive enough for all the texts varied in structures prominently. In this paper, we exploit different block partition methods and introduce two widely used features: the gray scale contrast (GSC) feature to eliminate the background difference, and the edge orient histogram (EOH) feature to distinguish the structure of texts from that of non-texts. A texture classifier can be got by SVM training of pre-labeled data. The candidate text lines can be verified by this classifier. Experimental results show that our feature performs well.
Keywords :
pattern classification; support vector machines; text analysis; SVM training; block partition method; edge orient histogram feature; gray scale contrast feature; pre-labeled data; support vector machine; text verification; texture classifier; Automation; Flowcharts; Histograms; Learning systems; Pattern classification; Support vector machine classification; Support vector machines; Text analysis; Text recognition; Videos;
Conference_Titel :
Document Analysis and Recognition, 2009. ICDAR '09. 10th International Conference on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-4500-4
Electronic_ISBN :
1520-5363
DOI :
10.1109/ICDAR.2009.61
