Extraction of binary character/graphics images from grayscale document images
CVGIP: Graphical Models and Image Processing
Binarization and multithresholding of document images using connectivity
CVGIP: Graphical Models and Image Processing
Noise reduction in a statistical approach to text categorization
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
A New Methodology for Gray-Scale Character Segmentation and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Introduction to Digital Image Processing
An Introduction to Digital Image Processing
Enhancement and Restoration of Digital Documents: Statistical Design of Nonlinear Algorithms
Enhancement and Restoration of Digital Documents: Statistical Design of Nonlinear Algorithms
Direct Gray-Scale Extraction of Features for Character Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Color image processing by using binary quaternion-moment-preserving thresholding technique
IEEE Transactions on Image Processing
Modern approaches in detection of page separators for image clustering
WSEAS Transactions on Computers
Methods of bitonal image conversion for modern and classic documents
WSEAS Transactions on Computers
Normalized text font resemblance method aimed at document image page clustering
WSEAS Transactions on Computers
Benchmark database and GUI environment for printed Arabic text recognition research
WSEAS Transactions on Information Science and Applications
Document layout analyze using hierarchical processing
VIS'08 Proceedings of the 1st WSEAS international conference on Visualization, imaging and simulation
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In this paper we address the problem of binarization of scanned documents which is a preprocessing requirement for most algorithms aimed at document image analysis. Two new approaches which focus on problem areas like low contrast documents, noise, and backside image showing through the paper sheet are presented in the following. First of all we propose a technique which is based on an initial preprocessing step followed by a conversion from the continuous space to the bitonal document. The first stage of this process focuses on document characteristics enhancement through contrast stretching for each color channel. The second step is a locally adaptive binarization process using color thresholding based on a Gaussian blur effect. Apart from that we present a noise-removal conversion technique based on combining the result of a series of threshold masks. Experimental results are given in order to verify the effectiveness of the proposed technique.