Document Type: Research Paper
Faculty of Computer Engineering, Shahrood University of Technology, Shahrood, Iran
Faculty of Electrical and Robotic Engineering, Shahrood University of Technology, Shahrood, Iran
Localizing text regions in images taken from natural scenes is one of the challenging problems due
to variations in font, size, color and orientation of text. In this paper, we introduce a new concept so
called Edge Color Signature for localizing text regions in an image. This method is able to localize
both Farsi and English texts. In the proposed method rst a pyramid using different scales of the
input image is created. Then for each level of the pyramid an edge map is extracted. Afterward,
several geometric features are employed to lter out the non-text edges from the extracted edges.
At this stage we describe an edge using colors of its neighboring pixels. We use the mean-Shift
algorithm to obtain the color modes surrounding each edge pixel. Subsequently, the connected
edge pixels with similar color signatures are clustered using Single-Linkage clustering algorithm to
construct meaningful groups. Finally, each of the clusters is labeled as text or non-text using an
MLP based cascade classier. The proposed method has been evaluated on well-known ICDAR 2013
and our Farsi dataset, the result is very promising.