A new PDE-based approach for singularity-preserving regularization: application to degraded characters restoration

The massive digitization of heritage documents has raised new prospects for research like degraded document image restoration. Degradations harm the legibility of the digitized documents and limit their processing. As a solution, we propose to tackle the problem of degraded text characters with PDE (partial differential equation)-based approaches. Existing PDE approaches do not preserve singularities and edge continuities while smoothing. Hence, we propose a new anisotropic diffusion by adding new constraints to the Weickert coherence-enhancing diffusion filter in order to control the diffusion process and to eliminate the inherent corner rounding. A qualitative improvement in the singularity preservation is thus achieved. Experiments conducted on degraded document images illustrate the effectiveness of the proposed method compared with other anisotropic diffusion approaches. We illustrate the performance with the study of the optical recognition accuracy rates.

[1]  Jitendra Malik,et al.  Scale-Space and Edge Detection Using Anisotropic Diffusion , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Robert M. Haralick,et al.  Document image restoration using binary morphological filters , 1996, Electronic Imaging.

[3]  Wilfried Philips,et al.  A fast non-local image denoising algorithm , 2008, Electronic Imaging.

[4]  Venu Govindaraju,et al.  Historical document image enhancement using background light intensity normalization , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[5]  Christian Wolf,et al.  Document Ink Bleed-Through Removal with Two Hidden Markov Random Fields and a Single Observation Field , 2010, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Jörg Weule,et al.  Non-Linear Gaussian Filters Performing Edge Preserving Diffusion , 1995, DAGM-Symposium.

[7]  Venu Govindaraju,et al.  PDE-Based Enhancement of Low Quality Documents , 2007, Ninth International Conference on Document Analysis and Recognition (ICDAR 2007).

[8]  Fadoua Drira,et al.  Towards restoring historic documents degraded over time , 2006, Second International Conference on Document Image Analysis for Libraries (DIAL'06).

[9]  Frank Lebourgeois,et al.  Document Images Restoration by a New Tensor Based Diffusion Process: Application to the Recognition of Old Printed Documents , 2009, 2009 10th International Conference on Document Analysis and Recognition.

[10]  Peyman Milanfar,et al.  A generalization of non-local means via kernel regression , 2008, Electronic Imaging.

[11]  David B. H. Tay,et al.  Enhancement of document images using multiresolution and fuzzy logic techniques , 1999, IEEE Signal Processing Letters.

[12]  Jean-Michel Morel,et al.  A non-local algorithm for image denoising , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[13]  Etienne E. Kerre,et al.  Greyscale Image Interpolation Using Mathematical Morphology , 2006, ACIVS.

[14]  Joachim Weickert,et al.  Anisotropic diffusion in image processing , 1996 .

[15]  Ron Kimmel,et al.  A general framework for low level vision , 1998, IEEE Trans. Image Process..

[16]  J. Weickert Scale-Space Properties of Nonlinear Diffusion Filtering with a Diffusion Tensor , 1994 .

[17]  Michael J. Black,et al.  Fields of Experts , 2009, International Journal of Computer Vision.

[18]  P. Lions,et al.  Axioms and fundamental equations of image processing , 1993 .

[19]  Elisa H. Barney Smith,et al.  Pre-Processing of Degraded Printed Documents by Non-local Means and Total Variation , 2009, 2009 10th International Conference on Document Analysis and Recognition.

[20]  Joachim Weickert,et al.  Coherence-enhancing diffusion of colour images , 1999, Image Vis. Comput..

[21]  J. Weickert,et al.  A ROTATIONALLY INVARIANT BLOCK MATCHING STRATEGY IMPROVING IMAGE DENOISING WITH NON-LOCAL MEANS , 2008 .

[22]  Anna Tonazzini,et al.  Fast correction of bleed-through distortion in grayscale documents by a blind source separation technique , 2007, International Journal of Document Analysis and Recognition (IJDAR).

[23]  Anna Tonazzini,et al.  Analysis and recognition of highly degraded printed characters , 2003, Document Analysis and Recognition.

[24]  Rachid Deriche,et al.  Vector-valued image regularization with PDE's: a common framework for different applications , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[25]  Hong Yan,et al.  Linking broken character borders with variable sized masks to improve recognition , 1996, Pattern Recognit..

[26]  Hirobumi Nishida Restoring high-resolution binary images for text enhancement , 2005, IEEE International Conference on Image Processing 2005.

[27]  C. Hale,et al.  Human Image Preference and Document Degradation Models , 2007 .

[28]  A. Bruckstein,et al.  K-SVD : An Algorithm for Designing of Overcomplete Dictionaries for Sparse Representation , 2005 .

[29]  L. Rudin,et al.  Nonlinear total variation based noise removal algorithms , 1992 .

[30]  Pierrick Coupé,et al.  An Optimized Blockwise Nonlocal Means Denoising Filter for 3-D Magnetic Resonance Images , 2008, IEEE Transactions on Medical Imaging.

[31]  Aggelos K. Katsaggelos,et al.  A VQ-based blind image restoration algorithm , 2003, IEEE Trans. Image Process..

[32]  Michael Elad,et al.  Sparse Representation for Color Image Restoration , 2008, IEEE Transactions on Image Processing.

[33]  Tony Lindeberg,et al.  Scale-Space Theory in Computer Vision , 1993, Lecture Notes in Computer Science.

[34]  Hubert Emptoz,et al.  A Modified Mean Shift Algorithm For Efficient Document Image Restoration , 2008 .

[35]  Jitendra Malik,et al.  Anisotropic Diffusion , 1994, Geometry-Driven Diffusion in Computer Vision.

[36]  Ron Kimmel,et al.  Images as Embedded Maps and Minimal Surfaces: Movies, Color, Texture, and Volumetric Medical Images , 2000, International Journal of Computer Vision.

[37]  Tin Kam Ho,et al.  Enhancing degraded document images via bitmap clustering and averaging , 1997, Proceedings of the Fourth International Conference on Document Analysis and Recognition.

[38]  Bart M. ter Haar Romeny,et al.  Geometry-Driven Diffusion in Computer Vision , 1994, Computational Imaging and Vision.

[39]  Frank Lebourgeois,et al.  Restoring Ink Bleed-Through Degraded Document Images Using a Recursive Unsupervised Classification Technique , 2006, Document Analysis Systems.

[40]  Xiaohu Zhang,et al.  Training on severely degraded text-line images , 2003, Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings..

[41]  M. Elad,et al.  $rm K$-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation , 2006, IEEE Transactions on Signal Processing.

[42]  C. V. Jawahar,et al.  Contextual restoration of severely degraded document images , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[43]  Rachid Deriche,et al.  Vector-valued image regularization with PDEs: a common framework for different applications , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[44]  Elisa H. Barney Smith,et al.  Text degradations and OCR training , 2005, Eighth International Conference on Document Analysis and Recognition (ICDAR'05).

[45]  P. Lions,et al.  Image selective smoothing and edge detection by nonlinear diffusion. II , 1992 .

[46]  Jean-Michel Morel,et al.  A Review of Image Denoising Algorithms, with a New One , 2005, Multiscale Model. Simul..

[47]  Tapas Kanungo,et al.  Morphological degradation models and their use in document image restoration , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[48]  Mohamed Cheriet,et al.  RSLDI: Restoration of single-sided low-quality document images , 2009, Pattern Recognit..

[49]  Joachim Weickert,et al.  A Review of Nonlinear Diffusion Filtering , 1997, Scale-Space.

[50]  Wilfried Philips,et al.  Non-Local Text Image Reconstruction , 2007, Ninth International Conference on Document Analysis and Recognition (ICDAR 2007).

[51]  Elisa H. Barney Smith,et al.  Human Image Preference and Document Degradation Models , 2007, Ninth International Conference on Document Analysis and Recognition (ICDAR 2007).

[52]  Patrick Kelly,et al.  Quality assessment and restoration of typewritten document images , 1999, International Journal on Document Analysis and Recognition.