Extraction of binary character/graphics images from grayscale document images
CVGIP: Graphical Models and Image Processing
An adaptive conjugate gradient learning algorithm for efficient training of neural networks
Applied Mathematics and Computation
Machine learning: neural networks, genetic algorithms, and fuzzy systems
Machine learning: neural networks, genetic algorithms, and fuzzy systems
A Survey of Methods and Strategies in Character Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Low resolution, degraded document recognition using neural networks and hidden Markov models
Pattern Recognition Letters
An Introduction to Digital Image Processing
An Introduction to Digital Image Processing
The Perception of Visual Information, 2e
The Perception of Visual Information, 2e
Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
Modelling the Sensory Abilities of Intelligent Virtual Agents
Autonomous Agents and Multi-Agent Systems
Document Image Retrieval Based on Density Distribution Feature and Key Block Feature
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Text line segmentation of historical documents: a survey
International Journal on Document Analysis and Recognition
A new Tsallis entropy-based thresholding algorithm for images of historical documents
Proceedings of the 2007 ACM symposium on Document engineering
Visual perception in design and robotics
Integrated Computer-Aided Engineering - Informatics in Control, Automation and Robotics
An Objective Evaluation Methodology for Document Image Binarization Techniques
DAS '08 Proceedings of the 2008 The Eighth IAPR International Workshop on Document Analysis Systems
Recognition strategies for general handwritten text documents
Integrated Computer-Aided Engineering
Binarization of historical document images using the local maximum and minimum
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
Integrated Computer-Aided Engineering
ICDAR 2011 Document Image Binarization Contest (DIBCO 2011)
ICDAR '11 Proceedings of the 2011 International Conference on Document Analysis and Recognition
Digital Document Analysis and Processing
Digital Document Analysis and Processing
A quadsection algorithm for grammar-based image compression
Integrated Computer-Aided Engineering - Anniversary Volume: Celebrating 20 Years of Excellence
A generalization of quad-trees applied to image coding
Integrated Computer-Aided Engineering
Efficient blind image deconvolution using spectral non-Gaussianity
Integrated Computer-Aided Engineering
A genetic programming based system for the automatic construction of image filters
Integrated Computer-Aided Engineering
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In this work a new method to enhance and binarize document images with several kind of degradation is proposed. The method is based on the idea that by the absolute difference between a document image and its background it is possible to effectively emphasize the text and attenuate degraded regions. To generate the background of a document our work was inspired on the human visual system and on the perception of objects by distance. Snellen's visual acuity notation was used to define how far an image must be from an observer so that the details of the characters are not perceived anymore, remaining just the background. A scheme that combines k-means clustering algorithm and Otsu's thresholding method is also used to perform binarization. The proposed method has been tested on two different datasets of document images DIBCO 2011 and a real historical document image dataset with very satisfactory results.