Text segmentation in color images using tensor voting

In natural scene, text elements are corrupted by many types of noise, such as streaks, highlights, or cracks. These effects make the clean and automatic segmentation very difficult and can reduce the accuracy of further analysis such as optical character recognition. We propose a method to drastically improve segmentation using tensor voting as the main filtering step. We first decompose an image into chromatic and achromatic regions. We then identify text layers using tensor voting, and remove noise using adaptive median filter iteratively. Finally, density estimation for center modes detection and K-means clustering algorithm is performed later for segmentation of values according to hue or intensity component in the improved image. Excellent results are achieved in experiments on real images.

[1]  Carl E. Rasmussen,et al.  The Infinite Gaussian Mixture Model , 1999, NIPS.

[2]  Ismail Haritaoglu.  Scene text extraction and translation for handheld devices , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[3]  Patrick Shen-Pei Wang,et al.  A new method of color image segmentation based on intensity and hue clustering , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[4]  Sankar K. Pal,et al.  A review on image segmentation techniques , 1993, Pattern Recognit..

[5]  David Suter,et al.  A novel robust method for large numbers of gross errors , 2002, 7th International Conference on Control, Automation, Robotics and Vision, 2002. ICARCV 2002..

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

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

[8]  S. Mitra,et al.  Unsupervised segmentation of color images based on k-means clustering in the chromaticity plane , 1999, Proceedings IEEE Workshop on Content-Based Access of Image and Video Libraries (CBAIVL'99).

[9]  Chuang Li,et al.  Automatic text location in natural scene images , 2001, Proceedings of Sixth International Conference on Document Analysis and Recognition.

[10]  Nikolaos G. Bourbakis,et al.  A fuzzy region growing approach for segmentation of color images , 1997, Pattern Recognit..

[11]  Naonori Ueda,et al.  Deterministic annealing EM algorithm , 1998, Neural Networks.

[12]  Ching Y. Suen,et al.  Color segmentation for text extraction , 2003, Document Analysis and Recognition.

[13]  Sang Uk Lee,et al.  Integrated Position Estimation Using Aerial Image Sequences , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[14]  Ying Zhang,et al.  Automatic detection and translation of text from natural scenes , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[15]  Chi-Keung Tang,et al.  Inference of segmented color and texture description by tensor voting , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[16]  Chi-Keung Tang,et al.  Image repairing: robust image synthesis by adaptive ND tensor voting , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[17]  Mi-Suen Lee,et al.  A Computational Framework for Segmentation and Grouping , 2000 .

[18]  Shamik Sural,et al.  Segmentation and histogram generation using the HSV color space for image retrieval , 2002, Proceedings. International Conference on Image Processing.

[19]  Wen Gao,et al.  Fast and robust text detection in images and video frames , 2005, Image Vis. Comput..

[20]  Shi Peng-fei,et al.  Natural color image segmentation , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

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

[22]  Xilin Chen,et al.  A PDA-based sign translator , 2002, Proceedings. Fourth IEEE International Conference on Multimodal Interfaces.

[23]  Jean-Philippe Thiran,et al.  Text identification in complex background using SVM , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[24]  Dorin Comaniciu,et al.  Mean Shift: A Robust Approach Toward Feature Space Analysis , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[25]  Jing Li Wang,et al.  Color image segmentation: advances and prospects , 2001, Pattern Recognit..

[26]  Anil K. Jain,et al.  Locating text in complex color images , 1995, Pattern Recognit..

[27]  Mi-Suen Lee,et al.  Grouping ., -, ->, [formula], into Regions, Curves, and Junctions , 1999, Comput. Vis. Image Underst..

[28]  Anil K. Jain,et al.  Automatic text location in images and video frames , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

[29]  Gérard G. Medioni,et al.  First order augmentation to tensor voting for boundary inference and multiscale analysis in 3D , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[30]  David Suter,et al.  Color Image Segmentation Using Global Information and Local Homogeneity , 2003, DICTA.