A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
A fast algorithm for local minimum and maximum filters on rectangular and octagonal kernels
Pattern Recognition Letters
Adaptive thresholding algorithm and its hardware implementation
Pattern Recognition Letters
Evaluation of Binarization Methods for Document Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Document Image Binarization Based on Texture Features
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Introduction to Digital Image Processing
An Introduction to Digital Image Processing
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Adaptive degraded document image binarization
Pattern Recognition
Binarization of Badly Illuminated Document Images through Shading Estimation and Compensation
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 01
ICDAR 2009 Document Image Binarization Contest (DIBCO 2009)
ICDAR '09 Proceedings of the 2009 10th International Conference on Document Analysis and Recognition
Iterative Cross Section Sequence Graph for Handwritten Character Segmentation
IEEE Transactions on Image Processing
Development of Nom character segmentation for collecting patterns from historical document pages
Proceedings of the 2011 Workshop on Historical Document Imaging and Processing
A design of a preprocessing framework for large database of historical documents
Proceedings of the 2011 Workshop on Historical Document Imaging and Processing
Restoration of motion blurred document images
Proceedings of the 27th Annual ACM Symposium on Applied Computing
A learning framework for the optimization and automation of document binarization methods
Computer Vision and Image Understanding
Historical document binarization based on phase information of images
ACCV'12 Proceedings of the 11th international conference on Computer Vision - Volume 2
Proceedings of the 2013 ACM symposium on Document engineering
A combined approach for the binarization of handwritten document images
Pattern Recognition Letters
A new thresholding algorithm for document images based on the perception of objects by distance
Integrated Computer-Aided Engineering
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This paper presents a new document image binarization technique that segments the text from badly degraded historical document images. The proposed technique makes use of the image contrast that is defined by the local image maximum and minimum. Compared with the image gradient, the image contrast evaluated by the local maximum and minimum has a nice property that it is more tolerant to the uneven illumination and other types of document degradation such as smear. Given a historical document image, the proposed technique first constructs a contrast image and then detects the high contrast image pixels which usually lie around the text stroke boundary. The document text is then segmented by using local thresholds that are estimated from the detected high contrast pixels within a local neighborhood window. The proposed technique has been tested over the dataset that is used in the recent Document Image Binarization Contest (DIBCO) 2009. Experiments show its superior performance.