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Coarse-fine bimodality analysis of circular histograms
Pattern Recognition Letters, 1989Abstract The bimodality of a population P can be measured by dividing its range into two intervals so as to maximize the Fischer distance between the resulting two subpopulations P 1 and P 2 . If P is a mixture of two (approximately) Gaussian subpopulations, then P 1 and P 2 are good approximations to the original Gaussians, if their ...
Jean-Michel Jolion, Azriel Rosenfeld
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The analysis and applications of adaptive-binning color histograms
Computer Vision and Image Understanding, 2004Histograms are commonly used in content-based image: retrieval systems to represent the distributions of colors in images. It is a common understanding that histograms that adapt to images can represent their color distributions more efficiently than do histograms with fixed binnings.
Leow, W.K., Li, R.
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Exploratory Data Analysis with Linked Dotplots and Histograms
1998Data sets are currently increasing in their number of variables as well as their number of observations. Standard exploratory tools for multivariate data analysis, like the scatterplot matrix, have problems when dealing with such data. The screen space available gives only enough resolution for a scatterplot matrix of four variables.
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Co-histogram and its application in video analysis
2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763), 2005The tool for video analysis addressed in this paper is called co-histogram, which is a statistic graph generated by counting the corresponding pixel pairs of two images. A co-histogram shows how the pixels are distributed among combinations of two image pixel values. By means of the co-histogram, we can have a visual perception of a widely used metric,
Pengwei Hao, Ying Chen
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From Histogram Data to Model Data Analysis
2010The aim of this work is to propose a new approach for dealing with histogram data in symbolic data analysis framework. The idea is to approximate histogram data using B-spline functions in order to synthetize the information within data trough some characteristic function parameters.
Marino M., Signoriello S.
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Fuzzy Thresholding and Histogram Analysis
2003This chapter provides a comprehensive discussion of several thresholding techniques that employ the concept of the measure of fuzziness. The basic concepts and ideas of the measures of fuzziness are introduced. A unified description of the fuzzy thresholding methods based on the measure of fuzziness is given.
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Principal axes analysis of symbolic histogram variables
Statistical Analysis and Data Mining: The ASA Data Science Journal, 2015We present a new method to perform a principal axes analysis of symbolic histogram variables. In the symbolic data analysis framework, several Histogram Principal component Analysis (Histogram PCA) have been proposed. Some approaches focus on the relationships between some specific features of histograms such as the means or the quantiles.
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Highlight Detection by 2D-Histogram Analysis
Conference on Colour in Graphics, Imaging, and Vision, 2004openaire +2 more sources
A Novel 3-D Color Histogram Equalization Method With Uniform 1-D Gray Scale Histogram
IEEE Transactions on Image Processing, 2011Sejung Yang, Byung-Uk Lee
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