Results 231 to 240 of about 880,054 (288)

A multistage adaptive thresholding method

Pattern Recognition Letters, 2005
Thresholding is a simple but effective technique for image segmentation. In this paper, a general locally adaptive thresholding method using neighborhood processing is presented. The method makes use of local image statistics of mean and variance within a variable neighborhood and two thresholds obtained from the global intensity distribution.
Feixiang Yan, Hong Zhang 0013, C. Ronald Kube   +2 more
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Adaptive Thresholds

Journal of the American Statistical Association, 2006
This article describes a fast, statistically principled method for monitoring streams of network counts, which have long-term trends, rough cyclical patterns, outliers, and missing data. The key step is to build a reference (predictive) model for the counts that captures their complex, salient features but has just a few parameters that can be kept up ...
Lambert, Diane, Liu, Chuanhai
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Gradient based adaptive thresholding

Journal of Visual Communication and Image Representation, 2013
For images with poor and non-uniform illumination, adaptive thresholding is required to separate the objects of interest from the background. In this paper a new approach to create an adaptive threshold surface is proposed to segment an image. The technique is inspired by the Yanowitz's method and is improved upon by the introduction of a simpler and ...
Haniza Yazid, Hamzah Arof
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An adaptive method for image thresholding

Proceedings., 11th IAPR International Conference on Pattern Recognition. Vol. IV. Conference D: Architectures for Vision and Pattern Recognition,, 2003
Thresholding is a traditional tool for image regions classification based on their grey-level properties, especially when there are two kinds of homogeneous regions of intensity say, object and background. A new global thresholding scheme is described in this paper.
Vladimir A. Shapiro, P. K. Veleva, Vassil Stoyanov Sgurev   +2 more
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An Adaptable Threshold Decision Method

2009 Fifth International Conference on Information Assurance and Security, 2009
Otsu’s thresholding method (OTM) is one of the most commonly used thresholding methods. Unfortunately, the threshold obtained by OTM is biased in favor of the class, whose standard deviation or quantity of data is larger. Besides, one may adopt distinct thresholds in different applications for a same data set.
Meng-Hsiun Tsai, Ming-Hung Wang, Ting-Yuan Chang, Pei-Yan Pai, Yung-Kuan Chan   +4 more
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Threshold setting in adaptive filtering

Journal of Documentation, 2000
A major problem in using current best‐match methods in a filtering task is that of setting appropriate thresholds, which are required in order to force a binary decision on notifying a user of a document. We discuss methods for setting such thresholds and adapting them as a result of feedback information on the performance of the profile. These methods
Stephen E. Robertson, Stephen Walker
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Adaptive Threshold Procedures: BUDTIF

The Journal of the Acoustical Society of America, 1968
Consideration of recent psychoacoustic research reveals that, independent of the general acceptance of the theory of signal detectability, threshold methodology continues to play a major rôle in the acquisition of psychoacoustic data. Although adaptive methods are widely used, the newer, finite-trial, adaptive methods are not—possibly owing to a ...
R A, Campbell, E Z, Lasky
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Increment thresholds and dark adaptation

Journal of Theoretical Biology, 1964
Abstract A quantitative theory of the increment thresholds and dark adaptation of the rod receptors in the human eye has been developed which gives an accurate fit with experimental data from the initial threshold to the saturation level of intensity with various amounts of rhodopsin bleaching.
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Adaptive Thresholding using the Integral Image

Journal of Graphics Tools, 2007
Image thresholding is a common task in many computer vision and graphics applications. The goal of thresholding an image is to classify pixels as either "dark" or "light." Adaptive thresholding is a form of thresholding that takes into account spatial variations in illumination.
Bradley, D., Roth, Gerhard
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Adaptive estimation of hysteresis thresholds

Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2002
It is shown that the hitherto heuristic hysteresis linking idea of J.F. Canny (1986) can be formulated as a Bayesian contextual decision process. This approach draws on an explicit image model which accounts both for the way in which noisy raw-edge information is characterized via filtering operations and how the required edge-connectivity information ...
Edwin R. Hancock, Josef Kittler
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