scholarly journals Assessment of Camouflage Effectiveness Based on Perceived Color Difference and Gradient Magnitude

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4672
Author(s):  
Xueqiong Bai ◽  
Ningfang Liao ◽  
Wenmin Wu
Keyword(s):  
Real World ◽  
Information Entropy ◽  
Human Visual System ◽  
Similarity Index ◽  
Color Difference ◽  
Entropy Theory ◽  
Analysis Process ◽  
Gradient Magnitude ◽  
Color Similarity ◽  
Perceived Color

We propose a new model to assess the effectiveness of camouflage in terms of perceived color difference and gradient magnitude. The “image color similarity index” (ICSI) and gradient magnitude similarity deviation (GMSD) were employed to analyze color and texture differences, respectively, between background and camouflage images. Information entropy theory was used to calculate weights for each metric, yielding an overall camouflage effectiveness metric. During the analysis process, both spatial and color perceptions of the human visual system (HVS) were considered, to mimic real-world observations. Subjective tests were used to compare our proposed method with previous methods, and our results confirmed the validity of assessing camouflage effectiveness based on perceived color difference and gradient magnitude.

Approach for cleaning uncertain data based on information entropy theory

2013 ◽  
Vol 33 (9) ◽  
pp. 2490-2492
Author(s):  
Yuanxiang QIN ◽  
Liang DUAN ◽  
Kun YUE
Keyword(s):  
Information Entropy ◽  
Uncertain Data ◽  
Entropy Theory

scholarly journals Research on Pattern Recognition Method of Blockage Signal in Pipeline Based on LMD Information Entropy and ELM

2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Jingzong Yang ◽  
Xiaodong Wang ◽  
Zao Feng ◽  
Guoyong Huang
Keyword(s):  
Pattern Recognition ◽  
Impulse Response ◽  
Information Entropy ◽  
Operating Conditions ◽  
Support Vector ◽  
Entropy Theory ◽  
Pattern Recognition Method ◽  
Response Signal ◽  
Recognition Method ◽  
Learning Machine

Aiming at the nonstationary and nonlinear characteristics of acoustic impulse response signal in pipeline blockage and the difficulty in identifying the different degrees of blockage, this paper proposed a pattern recognition method based on local mean decomposition (LMD), information entropy theory, and extreme learning machine (ELM). Firstly, the impulse response signals of pipeline extracted in different operating conditions were decomposed with LMD method into a series of product functions (PFs). Secondly, based on the information entropy theory, the appropriate energy entropy, singular spectrum entropy, power spectrum entropy, and Hilbert spectrum entropy were extracted as the input feature vectors. Finally, ELM was introduced for classification of pipeline blockage. Through the analysis of acoustic impulse response signal collected under the condition of health and different degrees of blockages in pipeline, the results show that the proposed method can well characterize the state information. Also, it has a great advantage in terms of accuracy and it is time consuming when compared with the support vector machine (SVM) and BP (backpropagation) model.

Attribute Recognition Model Based on Entropy Weight and Its Application to Evaluation of Groundwater Quality

2010 ◽  
Vol 29-32 ◽  
pp. 2698-2702
Author(s):  
Xian Qi Zhang ◽  
Wen Hong Feng ◽  
Nan Nan Li
Keyword(s):  
Water Quality ◽  
Groundwater Quality ◽  
Information Entropy ◽  
Simple Calculation ◽  
Weight Coefficient ◽  
Entropy Theory ◽  
Entropy Weight ◽  
Recognition Model ◽  
Model Based ◽  
Attribute Recognition

It is necessary to take into account synthetically attribute of every index because of independence and incompatibility resulted from single index evaluating outcomes. Through the information entropy theory and attribute recognition model being combined together, attribute recognition model based on entropy weight is constructed and applied to evaluating groundwater quality by a new method, weight coefficient by the law of entropy value is exercised so that it is more objective. The outcome from concrete application indicates that it is suitable to evaluate water quality with reasonable conclusion and simple calculation.

Policy Analysis

2015 ◽  
pp. 132-146
Keyword(s):  
Policy Analysis ◽  
Real World ◽  
Policy Options ◽  
Environmental Scan ◽  
Analysis Process ◽  
Policy Question

In this chapter, students are presented with the fundamentals of policy analysis. Upon reading this chapter, students will understand the purpose of policy analysis, and how one goes about completing a policy analysis. Terms such as action forcing event, policy question, environmental scan, policy options, and options assessment are discussed in depth. Real world examples are used to further underscore each step in the policy analysis process.

TEXT LOCALIZATION IN IMAGES USING REVERSE THRESHOLDS ALGORITHM

2015 ◽  
Vol 75 (2) ◽  
Author(s):  
Lih-Fong Wong ◽  
Mohd Yazid Idris ◽  
Abdul Hanan Abdullah
Keyword(s):  
Similarity Index ◽  
Background Color ◽  
Text Localization ◽  
Color Similarity ◽  
Text Features ◽  
Rough Calculation ◽  
Novel Algorithm

High color similarity between text pixels and background pixels is the major problem that causes failure during text localization. In this paper, a novel algorithm, Reverse Thresholds (RT) algorithm is proposed to localize text from the images with various text-background color similarities. First, a rough calculation is proposed to determine the similarity index for every text region. Then, by applying reverse operation, the best thresholds for each text region are calculated by its similarity index. To remove other uncertainties, self-generated images with the same text features but different similarity index are used as experiment dataset. Experiment result shows that RT algorithm has higher localizing strength which is able to localize text in a wider range of similarity index.

scholarly journals A Copula Entropy Approach to Dependence Measurement for Multiple Degradation Processes

Entropy ◽  
2019 ◽  
Vol 21 (8) ◽  
pp. 724 ◽  
Author(s):  
Fuqiang Sun ◽  
Wendi Zhang ◽  
Ning Wang ◽  
Wei Zhang
Keyword(s):  
Information Entropy ◽  
Complex Structure ◽  
Copula Function ◽  
Dependence Structure ◽  
Entropy Theory ◽  
Multiple Features ◽  
Reliability Modeling ◽  
Degradation Processes ◽  
Degradation Analysis ◽  
Complex Dependence

Degradation analysis has been widely used in reliability modeling problems of complex systems. A system with complex structure and various functions may have multiple degradation features, and any of them may be a cause of product failure. Typically, these features are not independent of each other, and the dependence of multiple degradation processes in a system cannot be ignored. Therefore, the premise of multivariate degradation modeling is to capture and measure the dependence among multiple features. To address this problem, this paper adopts copula entropy, which is a combination of the copula function and information entropy theory, to measure the dependence among different degradation processes. The copula function was employed to identify the complex dependence structure of performance features, and information entropy theory was used to quantify the degree of dependence. An engineering case was utilized to illustrate the effectiveness of the proposed method. The results show that this method is valid for the dependence measurement of multiple degradation processes.

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