SCENE TEXT RECOGNITION IN IMAGES BY CHARACTER STRUCTURE CONFIGURATION AND DESCRIPTOR

Camera-Based text information serves as effective tags or clues for many mobile applications associated with media analysis, content retrieval, scene understanding, and assistant navigation. In natural scene images, text characters and strings usually appear in nearby sign boards and provide significant knowledge of surrounding environment and objects. Text characters and strings in natural scene can provide valuable information for many applications. Extracting text directly from natural scene images is a challenging task because of diverse text patterns and variant background interferences. This paper proposes a method of scene text recognition from detected text regions. In text detection, the previously proposed algorithms are applied to obtain text regions from scene image. The paper designs a discriminative character descriptor by combining several state-of-the-art feature detectors and descriptors. Second, it models character structure at each character class by designing stroke configuration maps. The design is compatible with the application of scene text extraction in images. The system is developed to show the effectiveness of our proposed method on scene text information extraction from nearby objects.

[1]  David A. McAllester,et al.  Object Detection with Discriminatively Trained Part Based Models , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  Wenyu Liu,et al.  Skeleton Pruning by Contour Partitioning with Discrete Curve Evolution , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  Longin Jan Latecki,et al.  Convexity Rule for Shape Decomposition Based on Discrete Contour Evolution , 1999, Comput. Vis. Image Underst..

[4]  Andrew Y. Ng,et al.  Text Detection and Character Recognition in Scene Images with Unsupervised Feature Learning , 2011, 2011 International Conference on Document Analysis and Recognition.

[5]  Manik Varma,et al.  Character Recognition in Natural Images , 2009, VISAPP.

[6]  Bill Triggs,et al.  Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[7]  Shijian Lu,et al.  Document Image Retrieval through Word Shape Coding , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  Céline Mancas-Thillou,et al.  A Weighted Finite-State Framework for Correcting Errors in Natural Scene OCR , 2007, Ninth International Conference on Document Analysis and Recognition (ICDAR 2007).

[9]  Nikos A. Nikolaou,et al.  Color reduction for complex document images , 2009, Int. J. Imaging Syst. Technol..

[10]  Simon M. Lucas,et al.  ICDAR 2003 robust reading competitions , 2003, Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings..

[11]  Xilin Chen,et al.  Automatic detection and recognition of signs from natural scenes , 2004, IEEE Transactions on Image Processing.

[12]  C. Schmid,et al.  Learning shape prior models for object matching , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[13]  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.

[14]  Sunil Kumar,et al.  Text Extraction and Document Image Segmentation Using Matched Wavelets and MRF Model , 2007, IEEE Transactions on Image Processing.

[15]  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.