DocumentCode
594709
Title
A skeleton based descriptor for detecting text in real scene images
Author
Felhi, Mehdi ; Bonnier, N. ; Tabbone, Salvatore
Author_Institution
LORIA, Univ. de Lorraine, Vandœuvre-lès-Nancy, France
fYear
2012
fDate
11-15 Nov. 2012
Firstpage
282
Lastpage
285
Abstract
In this paper, we present a new method for text extraction in real scene images. We propose first a skeleton based descriptor to describe the strokes of the text candidates that compose a spatial relation graph. We then apply the graph cuts algorithm to label the nodes of the graph as text or non-text. We finally refine the resulted text lines candidates by classifying them using a kernel SVM. To validate this approach we perform a set of tests on the public datasets ICDAR 2003 and 2011.
Keywords
graph theory; image classification; natural scenes; text detection; graph cuts algorithm; kernel SVM; nontext graph; public datasets ICDAR 2003; public datasets ICDAR 2011; real scene images; skeleton-based descriptor; spatial relation graph; text candidates; text detection; text extraction; text graph; text lines candidates; Image color analysis; Image edge detection; Image segmentation; Robustness; Skeleton; Support vector machines; Transforms;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location
Tsukuba
ISSN
1051-4651
Print_ISBN
978-1-4673-2216-4
Type
conf
Filename
6460127
Link To Document