Characterization of Signals from Multiscale Edges
IEEE Transactions on Pattern Analysis and Machine Intelligence
CVGIP: Graphical Models and Image Processing
A Survey of Methods and Strategies in Character Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Document Image Binarization Based on Texture Features
IEEE Transactions on Pattern Analysis and Machine Intelligence
Twenty Years of Document Image Analysis in PAMI
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Introduction to Digital Image Processing
An Introduction to Digital Image Processing
Multiscale Segmentation of Unstructured Document Pages Using Soft Decision Integration
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Evaluation of Document Analysis Components by Recall, Precision, and Accuracy
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
A Wavelet Approach to Extracting Contours of Document Images
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
Character Extraction from Noisy Background for an Automatic Reference System
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
A noise attribute thresholding method for document image binarization
ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 1) - Volume 1
De-noising by soft-thresholding
IEEE Transactions on Information Theory
Show-through cancellation in scans of duplex printed documents
IEEE Transactions on Image Processing
Text Identification in Noisy Document Images Using Markov Random Field
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Directional Wavelet Approach to Remove Document Image Interference
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
A quantitative method for assessing algorithms to remove back-to-front interference in documents
Proceedings of the 2007 ACM symposium on Applied computing
User-assisted ink-bleed correction for handwritten documents
Proceedings of the 8th ACM/IEEE-CS joint conference on Digital libraries
DIAR: Advances in Degradation Modeling and Processing
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
An algorithm for foreground-background separation in low quality patrimonial document images
CIARP'07 Proceedings of the Congress on pattern recognition 12th Iberoamerican conference on Progress in pattern recognition, image analysis and applications
Multichannel blind separation and deconvolution of images for document analysis
IEEE Transactions on Image Processing
Color space transformations for analysis and enhancement of ancient degraded manuscripts
Pattern Recognition and Image Analysis
User-assisted ink-bleed reduction
IEEE Transactions on Image Processing - Special section on distributed camera networks: sensing, processing, communication, and implementation
Visual enhancement of old documents with hyperspectral imaging
Pattern Recognition
DAS'06 Proceedings of the 7th international conference on Document Analysis Systems
A novel ring radius transform for video character reconstruction
Pattern Recognition
Methods for written ancient music restoration
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
Hi-index | 0.14 |
This paper addresses a problem of restoring handwritten archival documents by recovering their contents from the interfering handwriting on the reverse side caused by the seeping of ink. We present a novel method that works by first matching both sides of a document such that the interfering strokes are mapped with the corresponding strokes originating from the reverse side. This facilitates the identification of the foreground and interfering strokes. A wavelet reconstruction process then iteratively enhances the foreground strokes and smears the interfering strokes so as to strengthen the discriminating capability of an improved Canny edge detector against the interfering strokes. The method has been shown to restore the documents effectively with average precision and recall rates for foreground text extraction at 84 percent and 96 percent, respectively.