Title :
Dot Text Detection Based on FAST Points
Author :
Du, Yuning ; Ai, Haizhou ; Lao, Shihong
Author_Institution :
Comput. Sci. & Technol. Dept., Tsinghua Univ., Beijing, China
Abstract :
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.
Keywords :
image colour analysis; object detection; support vector machines; text analysis; FAST points; SVM; discontinuous text stroke; dot text detection; first order moments; general scene text detection; gray value similarity; non-dot text; second order moments; slant dot text; Data mining; Feature extraction; Histograms; Image edge detection; Support vector machines; Testing; SVM; dot text detection; slant text;
Conference_Titel :
Document Analysis and Recognition (ICDAR), 2011 International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4577-1350-7
Electronic_ISBN :
1520-5363
DOI :
10.1109/ICDAR.2011.94