Pattern Recognition
Practical methods of optimization; (2nd ed.)
Practical methods of optimization; (2nd ed.)
A survey of thresholding techniques
Computer Vision, Graphics, and Image Processing
A new method for image segmentation
Computer Vision, Graphics, and Image Processing
Machine vision
A Hopfield neural network for adaptive image segmentation: an active surface paradigm
Pattern Recognition Letters
An Introduction to Digital Image Processing
An Introduction to Digital Image Processing
Fuzzy Models and Algorithms for Pattern Recognition and Image Processing
Fuzzy Models and Algorithms for Pattern Recognition and Image Processing
Comparing Different Thresholding Algorithms for Segmenting Auroras
ITCC '04 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'04) Volume 2 - Volume 2
Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
A multistage adaptive thresholding method
Pattern Recognition Letters
Nonlinear Optimization
Adaptive thresholding by variational method
IEEE Transactions on Image Processing
Solidity based local threshold for oil sand image segmentation
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Adaptive local threshold with shape information and its application to object segmentation
ROBIO'09 Proceedings of the 2009 international conference on Robotics and biomimetics
Maximum similarity thresholding
Digital Signal Processing
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In this paper we introduce an adaptive image thresholding technique via minimax optimization of a novel energy functional that consists of a non-linear convex combination of an edge sensitive data fidelity term and a regularization term. While the proposed data fidelity term requires the threshold surface to intersect the image surface only at places with large image gradient magnitude, the regularization term enforces smoothness in the threshold surface. To the best of our knowledge, all the previously proposed energy functional-based adaptive image thresholding algorithms rely on manually set weighting parameters to achieve a balance between the data fidelity and the regularization terms. In contrast, we use minimax principle to automatically find this weighting parameter value, as well as the threshold surface. Our conscious choice of the energy functional permits a variational formulation within the minimax principle leading to a globally optimum solution. The proposed variational minimax optimization is carried out by an iterative gradient descent with exact line search technique that we experimentally demonstrate to be computationally far more attractive than the Fibonacci search applied to find the minimax solution. Our method shows promising results to preserve edge/texture structures in different benchmark images over other competing methods. We also demonstrate the efficacy of the proposed method for delineating lung boundaries from magnetic resonance imagery (MRI).