Dot Text Detection Based on FAST Points

In this paper, we propose a method for dot text detection based on FAST points. This problem is different from general scene text detection because of discontinuous text stroke. Unlike many other methods which assume that text is horizontally oriented, our method is able to deal with slant dot text....

Full description

Saved in:
Bibliographic Details
Published in2011 International Conference on Document Analysis and Recognition pp. 435 - 439
Main Authors Yuning Du, Haizhou Ai, Shihong Lao
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2011
Subjects
Data mining
dot text detection
Feature extraction
Histograms
Image edge detection
slant text
Support vector machines
SVM
Testing
Online AccessGet full text

Cover

More Information
Summary:In this paper, we propose a method for dot text detection based on FAST points. This problem is different from general scene text detection because of discontinuous text stroke. Unlike many other methods which assume that text is horizontally oriented, our method is able to deal with slant dot text. We extract interesting patches from FAST points and define four features based on the stroke and gray value similarity of dot text to describe a patch. Then, we generate some candidate regions from these patches and utilize SVM to filter out non-dot text ones with the first and second order moments of FAST points in them. Experimental results show that the proposed method is effective and fast to detect dot text.
ISBN:1457713500
9781457713507
ISSN:1520-5363
2379-2140
DOI:10.1109/ICDAR.2011.94