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
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;
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location :
Tsukuba
Print_ISBN :
978-1-4673-2216-4
