Pattern Recognition
A survey of thresholding techniques
Computer Vision, Graphics, and Image Processing
A Spatial Thresholding Method for Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic thresholding of gray-level pictures using two-dimensional entropy
Computer Vision, Graphics, and Image Processing
A new method for image segmentation
Computer Vision, Graphics, and Image Processing
Segmentation of Document Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Binarization and multithresholding of document images using connectivity
CVGIP: Graphical Models and Image Processing
Correcting for negative weights in ordinary kriging
Computers & Geosciences
Volumetric segmentation of medical images by three-dimensional bubbles
Computer Vision and Image Understanding - Special issue on physics-based modeling and reasoning in computer vision
An Introduction to Digital Image Processing
An Introduction to Digital Image Processing
Goal-Directed Evaluation of Binarization Methods
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automated algorithms for multiscale morphometry of neuronal dendrites
Neural Computation
Kriging filters for multidimensional signal processing
Signal Processing - Special section on content-based image and video retrieval
Locally adaptive block thresholding method with continuity constraint
Pattern Recognition Letters
Investigation of 3D geometry of bulk wheat and pea pores using X-ray computed tomography images
Computers and Electronics in Agriculture
Analysis of the vesicular structure of basalts
Computers & Geosciences
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Improved segmentation of X-ray tomography data from porous rocks using a dual filtering approach
Computers & Geosciences
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We consider the problem of segmenting a digitized image consisting of two univariate populations. Assume a priori knowledge allows incomplete assignment of voxels in the image, in the sense that a fraction of the voxels can be identified as belonging to population $\Pi_0$, a second fraction to $\Pi_1$, and the remaining fraction have no a priori identification. Based upon estimates of the short length scale spatial covariance of the image, we develop a method utilizing indicator kriging to complete the image segmentation.