Complex scene text binarization based on graph cut

Text binarization is a part of the system of natural scene text extraction. Owing to the effect of uneven light, complex background, low contrast etc., the problem of complex scene text binarization is very challenging. Consequently, a new scheme of scene text binarization is proposed in this paper adopting a two-step strategy. Firstly, K-Means cluster algorithm is employed in color space of RGB by using of two different distance metrics, and the better result is selected as the initial binarization result. Secondly, graph cut is employed for re-labeling verification in the minimum energy framework. Experimental results show the satisfactory performance of the proposed method.

[1]  S.M. Lucas,et al.  ICDAR 2005 text locating competition results , 2005, Eighth International Conference on Document Analysis and Recognition (ICDAR'05).

[2]  C. V. Jawahar,et al.  An MRF Model for Binarization of Natural Scene Text , 2011, 2011 International Conference on Document Analysis and Recognition.

[3]  Patrick Pérez,et al.  Interactive Image Segmentation Using an Adaptive GMMRF Model , 2004, ECCV.

[4]  Olga Veksler,et al.  Fast Approximate Energy Minimization via Graph Cuts , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Umapada Pal,et al.  Recent Advances in Video Based Document Processing: A Review , 2012, 2012 10th IAPR International Workshop on Document Analysis Systems.

[6]  Qifeng Liu,et al.  A new approach for text segmentation using a stroke filter , 2008, Signal Process..

[7]  Chunheng Wang,et al.  Adaptive Graph Cut Based Binarization of Video Text Images , 2012, 2012 10th IAPR International Workshop on Document Analysis Systems.

[8]  Wen Gao,et al.  Automatic text segmentation from complex background , 2004, 2004 International Conference on Image Processing, 2004. ICIP '04..

[9]  Volker Märgner,et al.  New Binarization Approach Based on Text Block Extraction , 2011, 2011 International Conference on Document Analysis and Recognition.

[10]  Jun Guo,et al.  Text extraction from natural scene image: A survey , 2013, Neurocomputing.

[11]  Bernard Gosselin,et al.  Color text extraction with selective metric-based clustering , 2007, Comput. Vis. Image Underst..

[12]  Derek Bradley,et al.  Adaptive Thresholding using the Integral Image , 2007, J. Graph. Tools.

[13]  Tatiana Novikova,et al.  Image Binarization for End-to-End Text Understanding in Natural Images , 2013, 2013 12th International Conference on Document Analysis and Recognition.

[14]  Youngsu Moon,et al.  Text segmentation based on stroke filter , 2006, MM '06.