Image Distance Measure Based on Adaptive Patch Matching

2014 ◽  
Author(s):  
Yan Yu ◽  
Tianjiang Wang ◽  
Ying Chen ◽  
Jinsheng Li ◽  
Tan Liu
Keyword(s):  
Distance Measure ◽  
Image Distance ◽  
Patch Matching

An image distance measure insensitive to amplitude and mean value variations

1991 ◽  
Vol 32 (1-5) ◽  
pp. 453-460
Author(s):  
Roberto Jezieniecki ◽  
Eduardo Rovaris
Keyword(s):  
Distance Measure ◽  
Mean Value ◽  
Image Distance

Feature selection of the armature winding broken coils in synchronous motor using genetic algorithm and mahalanobis distance

2012 ◽  
Vol 57 (3) ◽  
pp. 829-835 ◽  
Author(s):  
Z. Głowacz ◽  
J. Kozik
Keyword(s):  
Genetic Algorithm ◽  
Feature Selection ◽  
Mahalanobis Distance ◽  
Distance Measure ◽  
Synchronous Motor ◽  
Medical Diagnostics ◽  
Motor Current ◽  
Feature Spaces ◽  
Multidimensional Feature Spaces ◽  
Selection Of

The paper describes a procedure for automatic selection of symptoms accompanying the break in the synchronous motor armature winding coils. This procedure, called the feature selection, leads to choosing from a full set of features describing the problem, such a subset that would allow the best distinguishing between healthy and damaged states. As the features the spectra components amplitudes of the motor current signals were used. The full spectra of current signals are considered as the multidimensional feature spaces and their subspaces are tested. Particular subspaces are chosen with the aid of genetic algorithm and their goodness is tested using Mahalanobis distance measure. The algorithm searches for such a subspaces for which this distance is the greatest. The algorithm is very efficient and, as it was confirmed by research, leads to good results. The proposed technique is successfully applied in many other fields of science and technology, including medical diagnostics.

scholarly journals Superpixel Segmentation Based on Anisotropic Edge Strength

2019 ◽  
Vol 5 (6) ◽  
pp. 57 ◽  
Author(s):  
Gang Wang ◽  
Bernard De Baets
Keyword(s):  
Distance Measure ◽  
Saliency Detection ◽  
Experimental Results ◽  
Segmentation Method ◽  
Superpixel Segmentation ◽  
Gaussian Kernels ◽  
First Derivative ◽  
Edge Strength

Superpixel segmentation can benefit from the use of an appropriate method to measure edge strength. In this paper, we present such a method based on the first derivative of anisotropic Gaussian kernels. The kernels can capture the position, direction, prominence, and scale of the edge to be detected. We incorporate the anisotropic edge strength into the distance measure between neighboring superpixels, thereby improving the performance of an existing graph-based superpixel segmentation method. Experimental results validate the superiority of our method in generating superpixels over the competing methods. It is also illustrated that the proposed superpixel segmentation method can facilitate subsequent saliency detection.

scholarly journals A Dynamic Distance Measure of Picture Fuzzy Sets and Its Application

Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 436
Author(s):  
Ruirui Zhao ◽  
Minxia Luo ◽  
Shenggang Li
Keyword(s):  
Fuzzy Sets ◽  
Distance Measure ◽  
Distance Measures ◽  
Numerical Comparison ◽  
Mathematical Tool ◽  
Practical Applications ◽  
Fuzzy Point ◽  
Point Operator ◽  
The Difference ◽  
Picture Fuzzy Sets

Picture fuzzy sets, which are the extension of intuitionistic fuzzy sets, can deal with inconsistent information better in practical applications. A distance measure is an important mathematical tool to calculate the difference degree between picture fuzzy sets. Although some distance measures of picture fuzzy sets have been constructed, there are some unreasonable and counterintuitive cases. The main reason is that the existing distance measures do not or seldom consider the refusal degree of picture fuzzy sets. In order to solve these unreasonable and counterintuitive cases, in this paper, we propose a dynamic distance measure of picture fuzzy sets based on a picture fuzzy point operator. Through a numerical comparison and multi-criteria decision-making problems, we show that the proposed distance measure is reasonable and effective.

scholarly journals Inferring Modes of Colonization for Pest Species Using Heterozygosity Comparisons and a Shared-Allele Test

Genetics ◽  
2003 ◽  
Vol 163 (2) ◽  
pp. 823-831
Author(s):  
J A Sved ◽  
H Yu ◽  
B Dominiak ◽  
A S Gilchrist
Keyword(s):  
Distance Measure ◽  
Fruit Fly ◽  
Small Samples ◽  
Pest Species ◽  
Long Distance ◽  
Resampling Methods ◽  
Shared Allele ◽  
The Core ◽  
Direct Sampling ◽  
Long Distance Movement

Abstract Long-range dispersal of a species may involve either a single long-distance movement from a core population or spreading via unobserved intermediate populations. Where the new populations originate as small propagules, genetic drift may be extreme and gene frequency or assignment methods may not prove useful in determining the relation between the core population and outbreak samples. We describe computationally simple resampling methods for use in this situation to distinguish between the different modes of dispersal. First, estimates of heterozygosity can be used to test for direct sampling from the core population and to estimate the effective size of intermediate populations. Second, a test of sharing of alleles, particularly rare alleles, can show whether outbreaks are related to each other rather than arriving as independent samples from the core population. The shared-allele statistic also serves as a genetic distance measure that is appropriate for small samples. These methods were applied to data on a fruit fly pest species, Bactrocera tryoni, which is quarantined from some horticultural areas in Australia. We concluded that the outbreaks in the quarantine zone came from a heterogeneous set of genetically differentiated populations, possibly ones that overwinter in the vicinity of the quarantine zone.

Interval Distribution Power Flow with Relative-Distance-Measure Arithmetic

2021 ◽  
pp. 1-1
Author(s):  
Viet Cuong Ngo ◽  
Wenchuan Wu ◽  
Bing Wang ◽  
Yanling Du ◽  
Tuan Nguyen Ngoc
Keyword(s):  
Power Flow ◽  
Distance Measure ◽  
Relative Distance ◽  
Interval Distribution
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