Scene Text Extraction in IHLS Color Space Using Support Vector Machine

Scene text extraction is challenging research area due to variety of image degradations caused by imaging conditions and low cost consumer devices. In this paper we propose text extraction method that uses chroma and lightness component for generation of extraction hypotheses and incorporates SVM (support vector machine) based text detection stage as tool for hypotheses verification.  Choice of chroma and lightness components is based on their complementarity with respect to image degradations like shadows and highlights. Another novelty is usage of IHLS color space for text extraction task which is motivated by saturation definition that eliminates instability of this component at low lightness values. Results obtained on the ICDAR 2011 dataset confirm complementarity of chroma and lightness. Compared to the state-of-the-art methods proposed algorithm achieves higher correct recognition rate and comparable total edit distance. DOI: http://dx.doi.org/10.5755/j01.itc.44.1.5757

[1]  Luis Miguel Bergasa,et al.  A text reading algorithm for natural images , 2013, Image Vis. Comput..

[2]  Jin Hyung Kim,et al.  Texture-Based Approach for Text Detection in Images Using Support Vector Machines and Continuously Adaptive Mean Shift Algorithm , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Allan Hanbury,et al.  A 3D-Polar Coordinate Colour Representation Well Adapted to Image Analysis , 2003, SCIA.

[4]  Luca Zini,et al.  A Classification Architecture Based on Connected Components for Text Detection in Unconstrained Environments , 2009, 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance.

[5]  Jiri Matas,et al.  A Method for Text Localization and Recognition in Real-World Images , 2010, ACCV.

[6]  Huizhong Chen,et al.  Robust text detection in natural images with edge-enhanced Maximally Stable Extremal Regions , 2011, 2011 18th IEEE International Conference on Image Processing.

[7]  H. Dujmic,et al.  Scene text extraction using modified cylindrical distance , 2011 .

[8]  Andreas Dengel,et al.  ICDAR 2011 Robust Reading Competition Challenge 2: Reading Text in Scene Images , 2011, 2011 International Conference on Document Analysis and Recognition.

[9]  Martin Grötschel,et al.  An Application of Combinatorial Optimization to Statistical Physics and Circuit Layout Design , 1988, Oper. Res..

[10]  Yonatan Wexler,et al.  Detecting text in natural scenes with stroke width transform , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[11]  Cheng-Lin Liu,et al.  A Hybrid Approach to Detect and Localize Texts in Natural Scene Images , 2011, IEEE Transactions on Image Processing.

[12]  Toru Wakahara,et al.  Binarization of Color Character Strings in Scene Images Using K-Means Clustering and Support Vector Machines , 2011, 2011 International Conference on Document Analysis and Recognition.

[13]  Kai Wang,et al.  End-to-end scene text recognition , 2011, 2011 International Conference on Computer Vision.

[14]  Bernard Gosselin,et al.  An Embedded Application for Degraded Text Recognition , 2005, EURASIP J. Adv. Signal Process..

[15]  Christof Koch,et al.  Toward color image segmentation in analog VLSI: Algorithm and hardware , 1994, International Journal of Computer Vision.

[16]  Anil K. Jain,et al.  Text information extraction in images and video: a survey , 2004, Pattern Recognit..

[17]  Alain Trémeau,et al.  A Novel Algorithm for Text Detection and Localization in Natural Scene Images , 2010, 2010 International Conference on Digital Image Computing: Techniques and Applications.

[18]  Jin Hyung Kim,et al.  2009 10th International Conference on Document Analysis and Recognition Scene Text Extraction using Focus of Mobile Camera , 2022 .

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

[20]  Din-Chang Tseng,et al.  Color segmentation using perceptual attributes , 1992, Proceedings., 11th IAPR International Conference on Pattern Recognition. Vol. III. Conference C: Image, Speech and Signal Analysis,.

[21]  Apostolos Antonacopoulos,et al.  Colour text segmentation in web images based on human perception , 2007, Image Vis. Comput..

[22]  C. Garcia,et al.  Text detection and segmentation in complex color images , 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).

[23]  A.W.M. Smeulders,et al.  An introduction to image processing , 1991 .

[24]  Rainer Lienhart,et al.  Localizing and segmenting text in images and videos , 2002, IEEE Trans. Circuits Syst. Video Technol..

[25]  Bernard Gosselin,et al.  Natural Scene Text Understanding , 2007 .

[26]  Bernard Gosselin,et al.  Color binarization for complex camera-based images , 2005, IS&T/SPIE Electronic Imaging.

[27]  C. V. Jawahar,et al.  Top-down and bottom-up cues for scene text recognition , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[28]  Li Xu,et al.  Automatic character detection and segmentation in natural scene images , 2007 .

[29]  Allan Hanbury,et al.  Colour Image Analysis in 3D-Polar Coordinates , 2003, DAGM-Symposium.