A new method for image segmentation
Computer Vision, Graphics, and Image Processing
Evaluation of Binarization Methods for Document Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
A multigrid tutorial: second edition
A multigrid tutorial: second edition
An Introduction to Digital Image Processing
An Introduction to Digital Image Processing
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
A double-threshold image binarization method based on edge detector
Pattern Recognition
Adaptive thresholding of tomograms by projection distance minimization
Pattern Recognition
Selection of local thresholds for tomogram segmentation by projection distance minimization
DGCI'08 Proceedings of the 14th IAPR international conference on Discrete geometry for computer imagery
A new binarization method for non-uniform illuminated document images
Pattern Recognition
Gradient based adaptive thresholding
Journal of Visual Communication and Image Representation
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The problem of binarization of gray level images, acquired under non-uniform illumination is reconsidered. Yanowitz and Bruckstein proposed to use for image binarization an adaptive threshold surface, determined by interpolation of the image gray levels at points where the image gradient is high. The rationale is that high image gradient indicates probable object edges, and there the image values are between the object and the background gray levels. The threshold surface was determined by successive over-relaxation as the solution of the Laplace equation. This work proposes a different method to determine an adaptive threshold surface. In this new method, inspired by multiresolution approximation, the threshold surface is constructed with considerably lower computational complexity and is smooth, yielding faster image binarizations and often better noise robustness.