Journal ArticleDOI
Pixel Classification Based on Gray Level and Local ``Busyness''
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TLDR
An image can be segmented by classifying its pixels using local properties as features, and two intuitively useful properties are the gray level of the pixel and the ``busyness,'' or gray level fluctuation, measured in its neighborhood.Abstract:
An image can be segmented by classifying its pixels using local properties as features. Two intuitively useful properties are the gray level of the pixel and the ``busyness,'' or gray level fluctuation, measured in its neighborhood. Busyness values tend to be highly vari-able in busy regions; but great improvements in classification accuracy can be obtained by smoothing these values prior to classifying. An alternative possibility is to classify probabilistically and use relaxation to adjust the probabilities.read more
Citations
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Journal ArticleDOI
A review on image segmentation techniques
Nikhil R. Pal,Sankar K. Pal +1 more
TL;DR: Attempts have been made to cover both fuzzy and non-fuzzy techniques including color image segmentation and neural network based approaches, which addresses the issue of quantitative evaluation of segmentation results.
Journal ArticleDOI
Automatic tracing of vocal-fold motion from high-speed digital images
Yuling Yan,Xin Chen,D. Bless +2 more
TL;DR: The objective of this study is to introduce a new approach for automatic tracing of vocal fold motion from image sequences acquired from high-speed digital imaging of the larynx, and to demonstrate the performance, effectiveness and validation of this approach using representative, high- speed imaging recordings of subjects having normal and pathological voices.
Patent
Digital image processing method and apparatus for brightness adjustment of digital images
TL;DR: In this article, a method of calculating a brightness balance value for a digital image including a plurality of pixels, comprising the steps of: calculating a spatial activity measure in the plurality of local neighborhoods of pixels of the digital image, each local neighborhood including a multiplicity of pixels.
Proceedings ArticleDOI
Texture feature based on local Fourier transform
Feng Zhou,Jufu Feng,Qing Yun Shi +2 more
TL;DR: A new texture feature named LFH is proposed based on the local-similarity and 8-neighbour gray-tone spatial dependencies by using local Fourier transform to be used for texture classification and texture retrieval.
Journal ArticleDOI
Image thresholding: some new techniques
TL;DR: Two algorithms based on a new conditional entropy measure of a partitioned image have been formulated using the Poisson distribution for the gray level instead of the commonly used normal distribution and are found to produce good results.
References
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Journal ArticleDOI
Scene Labeling by Relaxation Operations
TL;DR: This paper formulates the ambiguity-reduction process in terms of iterated parallel operations (i.e., relaxation operations) performed on an array of object, identification data.
Journal ArticleDOI
Image segmentation by clustering
G.B. Coleman,H.C. Andrews +1 more
TL;DR: The technique does not require training prototypes but operates in an "unsupervised" mode and is based on a mathematical-pattern recognition model, which achieves a maximum value that is postulated to represent an intrinsic number of clusters in the data.
Journal ArticleDOI
A Relaxation Method for Multispectral Pixel Classification
TL;DR: In experiments using a color image of a house, the relaxation approach gave markedly superior performance; relaxation eliminated 4-8 times as many errors as the other methods did.
Journal ArticleDOI
Some experiments in image segmentation by clustering of local feature values
TL;DR: Some attempts to segment textured black and white images by detecting clusters of local feature values and partitioning the feature space so as to separate these clusters.
Journal ArticleDOI
Neighbor gray levels as features in pixel classification
TL;DR: In segmenting an image by pixel classification, the sequence of gray levels of the pixel's neighbors can be used as a feature vector that yields classifications at least as good as those obtained using other local properties as features.
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