Performance Estimate of Range Profile Feature Extraction by Means of Interclass Metric Histograms Analysis

2019 ◽  
Author(s):  
F. B. Baulin ◽  
E. V. Buryi
Keyword(s):  
Feature Extraction ◽  
Performance Estimate ◽  
Range Profile

Translation Compensation Based on Cycle Subtracting of Micro-Doppler Curve

2015 ◽  
Vol 742 ◽  
pp. 281-285
Author(s):  
Dong Zhang ◽  
Cun Qian Feng ◽  
Yong Shun Zhang ◽  
Jing Qing Li
Keyword(s):  
Feature Extraction ◽  
Least Squares ◽  
Viterbi Algorithm ◽  
Single Cycle ◽  
Rule Based ◽  
Scattering Model ◽  
Range Profile ◽  
Feature Extraction Algorithm ◽  
Extraction Algorithm ◽  
Simulation Results

To solve the problem of translation compensation on ballistic target under complex scattering model in midcourse, a novel rule based on cycle subtracting of micro-Doppler curve is proposed. Firstly, the period is estimated by the period feature extraction algorithm which is based on the correlation of range profile envelopes. Then, extract the Doppler curve of the strongest scattering point through the Viterbi algorithm. Lastly, do the cycle subtracting and single cycle integral to the curve, the precious translation parameters can be got by the least squares estimating. This method is not only suitable for the rotating model, but also valuable for the precession model and the sliding model. The effectiveness of the proposed rule is verified by simulation results.

An Improved Quantitative Image Analyser

1977 ◽  
Vol 35 ◽  
pp. 226-227
Author(s):  
J.P. Fallon ◽  
P.J. Gregory ◽  
C.J. Taylor
Keyword(s):  
Feature Extraction ◽  
Quantitative Analysis ◽  
Frequency Content ◽  
General Sense ◽  
Physical Measurements ◽  
Quantitative Image ◽  
Image Analyser ◽  
Automatic Methods ◽  
Quantitative Results

Quantitative image analysis systems have been used for several years in research and quality control applications in various fields including metallurgy and medicine. The technique has been applied as an extension of subjective microscopy to problems requiring quantitative results and which are amenable to automatic methods of interpretation.Feature extraction. In the most general sense, a feature can be defined as a portion of the image which differs in some consistent way from the background. A feature may be characterized by the density difference between itself and the background, by an edge gradient, or by the spatial frequency content (texture) within its boundaries. The task of feature extraction includes recognition of features and encoding of the associated information for quantitative analysis.Quantitative Analysis. Quantitative analysis is the determination of one or more physical measurements of each feature. These measurements may be straightforward ones such as area, length, or perimeter, or more complex stereological measurements such as convex perimeter or Feret's diameter.

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