Qiang Wang, Chen Meng and Cheng Wang
This study aims to reveal the essential characteristics of nonstationary signals and explore the high-concentration representation in the joint time–frequency (TF) plane.
Abstract
Purpose
This study aims to reveal the essential characteristics of nonstationary signals and explore the high-concentration representation in the joint time–frequency (TF) plane.
Design/methodology/approach
In this paper, the authors consider the effective TF analysis for nonstationary signals consisting of multiple components.
Findings
To make it, the authors propose the combined multi-window Gabor transform (CMGT) under the scheme of multi-window Gabor transform by introducing the combination operator. The authors establish the completeness utilizing the discrete piecewise Zak transform and provide the perfect-reconstruction conditions with respect to combined TF coefficients. The high-concentration is achieved by optimization. The authors establish the optimization function with considerations of TF concentration and computational complexity. Based on Bergman formulation, the iteration process is further analyzed to obtain the optimal solution.
Originality/value
With numerical experiments, it is verified that the proposed CMGT performs better in TF analysis for multi-component nonstationary signals.
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Published posthumously, presented in 1965 at the Wiener Memorial Meeting. Concerned with Norbert Wiener who, while rendering great services to engineering, always remained a pure…
Abstract
Published posthumously, presented in 1965 at the Wiener Memorial Meeting. Concerned with Norbert Wiener who, while rendering great services to engineering, always remained a pure mathematician. Considers that the principal achievement of Wiener is that he establishes the link between statistical phenomena and the arts of communication and control. Provides examples of Wiener’s method of treating random phenomena and considers it to be very characteristic of his approach to physical problems. Outlines much of Wiener’s works relating to communication and discusses what he believes to be even more important, his contribution to the art of communication. Looks at the relationship of Wiener’s work to Shannon’s, as it was then understood, and to their position in the whole vast field of information theory.
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Philosophers and political theorists have presented us with a dazzling variety of views on freedom but, after more than two thousand years of discussion, general agreement as to…
Abstract
Philosophers and political theorists have presented us with a dazzling variety of views on freedom but, after more than two thousand years of discussion, general agreement as to the correct meaning of the concept appears to be as far off as ever. What Abraham Lincoln said almost a century ago is still true: the world has never had a good definition of the word liberty.
Hao Wu, Xiangrong Xu, Jinbao Chu, Li Duan and Paul Siebert
The traditional methods have difficulty to inspection various types of copper strips defects as inclusions, pits and delamination defects under uneven illumination. Therefore…
Abstract
Purpose
The traditional methods have difficulty to inspection various types of copper strips defects as inclusions, pits and delamination defects under uneven illumination. Therefore, this paper aims to propose an optimal real Gabor filter model for inspection; however, improper selection of Gabor parameters will cause the boundary between the defect and the background image to be not very clear. This will make the defect and the background cannot be completely separated.
Design/methodology/approach
The authors proposed an optimal Real Gabor filter model for inspection of copper surface defects under uneven illumination. This proposed method only requires a single filter by calculating the specific convolution energy of the Gabor filter with the image. The Real Gabor filter’s parameter is optimized by particle swarm optimization (PSO), which objective fitness function is maximization of the Gabor filter’s energy average divided by the energy standard deviation, the objective makes a distinction between the defect and normal area.
Findings
The authors have verified the effect with different iterations of parameter optimization using PSO, the effects with different control constant of energy and neighborhood window size of real Gabor filter, the experimental results on a number of metal surface have shown the proposed method achieved a well performance in defect recognition of metal surface.
Originality/value
The authors propose a defect detection method based on particle swarm optimization for single Gabor filter parameters optimization. This proposed method only requires a single filter and finds the best parameters of the Gabor filter. By calculating the specific convolution energy of the Gabor filter and the image, to obtain the best Gabor filter parameters and to highlight the defects, the particle swarm optimization algorithm’s fitness objective function is maximize the Gabor filter's average energy divided by the energy standard deviation.
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Xiuping Liu, Zhijie Wen, Zhixun Su and Shaogeng Yi
Automatic slub detection is vital in the classification and identification of fabric images. This paper seeks to present a rapid and accurate approach for automatic detection of…
Abstract
Purpose
Automatic slub detection is vital in the classification and identification of fabric images. This paper seeks to present a rapid and accurate approach for automatic detection of slub in fabric images using Gabor filters.
Design/methodology/approach
Slub can be regarded as defects along weft or warp. Gabor filters as bandpass filters consider the directional characteristics of slub and its frequency spectrum after Fourier transform. Choosing appropriate parameters for Gabor filters, slub can be detected accurately.
Findings
The proposed method achieves automatic detection of slub. The experimental results suggest that the authors approach is effective.
Originality/value
This paper considers appropriate parameters to design a Gabor filter for automatic detection of slub. And it is helpful to classify and identify fabric images.
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Wenda Wei, Chengxia Liu and Jianing Wang
Nowadays, most methods of illusion garment evaluation are based on the subjective evaluation of experienced practitioners, which consumes time and the results are too subjective…
Abstract
Purpose
Nowadays, most methods of illusion garment evaluation are based on the subjective evaluation of experienced practitioners, which consumes time and the results are too subjective to be accurate enough. It is necessary to explore a method that can quantify professional experience into objective indicators to evaluate the sensory comfort of the optical illusion skirt quickly and accurately. The purpose of this paper is to propose a method to objectively evaluate the sensory comfort of optical illusion skirt patterns by combining texture feature extraction and prediction model construction.
Design/methodology/approach
Firstly, 10 optical illusion sample skirts are produced, and 10 experimental images are collected for each sample skirt. Then a Likert five-level evaluation scale is designed to obtain the sensory comfort level of each skirt through the questionnaire survey. Synchronously, the coarseness, contrast, directionality, line-likeness, regularity and roughness of the sample image are calculated based on Tamura texture feature algorithm, and the mean, contrast and entropy are extracted of the image transformed by Gabor wavelet. Both are set as objective parameters. Two final indicators T1 and T2 are refined from the objective parameters previously obtained to construct the predictive model of the subjective comfort of the visual illusion skirt. The linear regression model and the MLP neural network model are constructed.
Findings
Results show that the accuracy of the linear regression model is 92%, and prediction accuracy of the MLP neural network model is 97.9%. It is feasible to use Tamura texture features, Gabor wavelet transform and MLP neural network methods to objectively predict the sensory comfort of visual illusion skirt images.
Originality/value
Compared with the existing uncertain and non-reproducible subjective evaluation of optical illusion clothing based on experienced experts. The main advantage of the authors' method is that this method can objectively obtain evaluation parameters, quickly and accurately obtain evaluation grades without repeated evaluation by experienced experts. It is a method of objectively quantifying the experience of experts.
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Chunlei Li, Chaodie Liu, Zhoufeng Liu, Ruimin Yang and Yun Huang
The purpose of this paper is to focus on the design of automated fabric defect detection based on cascaded low-rank decomposition and to maintain high quality control in textile…
Abstract
Purpose
The purpose of this paper is to focus on the design of automated fabric defect detection based on cascaded low-rank decomposition and to maintain high quality control in textile manufacturing.
Design/methodology/approach
This paper proposed a fabric defect detection algorithm based on cascaded low-rank decomposition. First, the constructed Gabor feature matrix is divided into a low-rank matrix and sparse matrix using low-rank decomposition technique, and the sparse matrix is used as priori matrix where higher values indicate a higher probability of abnormality. Second, we conducted the second low-rank decomposition for the constructed texton feature matrix under the guidance of the priori matrix. Finally, an improved adaptive threshold segmentation algorithm was adopted to segment the saliency map generated by the final sparse matrix to locate the defect regions.
Findings
The proposed method was evaluated on the public fabric image databases. By comparing with the ground-truth, the average detection rate of 98.26% was obtained and is superior to the state-of-the-art.
Originality/value
The cascaded low-rank decomposition was first proposed and applied into the fabric defect detection. The quantitative value shows the effectiveness of the detection method. Hence, the proposed method can be used for accurate defect detection and automated analysis system.
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F.H. She, F. Xia, W.S. Zhang and L.X. Kong
There is a huge demand for objective on-farm techniques, which would enable identification of the ‘outliers’ of sheep for the purpose of breeding selection, reducing the fineness…
Abstract
There is a huge demand for objective on-farm techniques, which would enable identification of the ‘outliers’ of sheep for the purpose of breeding selection, reducing the fineness (or diameter) of woolgrowers’ flocks with greater confidence, and maintaining the uniform quality throughout the wool clips. In this study, the concept of texture analysis based on Gabor filtering is employed and textural features are extracted from the images of wool staples with different fineness. It is justified by the experiments that those textural features are rotation invariant and also sensitive to the fineness of wool staples and efficient in discrimination of wool staples with different fineness. Since it requires minimum manual operations, this approach has a great potential to be applied on farm or in shearing shed.
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N.V. Brindha and V.S. Meenakshi
Any node in a mobile ad hoc network (MANET) can act as a host or router at any time and so, the nodes in the MANET are vulnerable to many types of attacks. Sybil attack is one of…
Abstract
Purpose
Any node in a mobile ad hoc network (MANET) can act as a host or router at any time and so, the nodes in the MANET are vulnerable to many types of attacks. Sybil attack is one of the harmful attacks in the MANET, which produces fake identities similar to legitimate nodes in the network. It is a serious threat to the MANET when a malicious node uses the fake identities to enter the network illegally.
Design/methodology/approach
A MANET is an independent collection of mobile nodes that form a temporary or arbitrary network without any fixed infrastructure. The nodes in the MANET lack centralized administration to manage the network and change their links to other devices frequently.
Findings
So for securing a MANET, an approach based on biometric authentication can be used. The multimodal biometric technology has been providing some more potential solutions for the user to be able to devise an authentication in MANETs of high security.
Research limitations/implications
The Sybil detection approach, which is based on the received signal strength indicator (RSSI) variations, permits the node to be able to verify the authenticity of communicating nodes in accordance with their localizations.
Practical implications
As the MANET node suffers from a low level of memory and power of computation, there is a novel technique of feature extraction that is proposed for the multimodal biometrics that makes use of palm prints that are based on a charge-coupled device and fingerprints, along with the features that are fused.
Social implications
This paper proposes an RSSI-based multimodal biometric solution to detect Sybil attack in MANETs.
Originality/value
The results of the experiment have indicated that this method has achieved a performance which is better compared to that of the other methods.
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Fowei Wang, Bo Shen, Shaoyuan Sun and Zidong Wang
The purpose of this paper is to improve the accuracy of the facial expression recognition by using genetic algorithm (GA) with an appropriate fitness evaluation function and…
Abstract
Purpose
The purpose of this paper is to improve the accuracy of the facial expression recognition by using genetic algorithm (GA) with an appropriate fitness evaluation function and Pareto optimization model with two new objective functions.
Design/methodology/approach
To achieve facial expression recognition with high accuracy, the Haar-like features representation approach and the bilateral filter are first used to preprocess the facial image. Second, the uniform local Gabor binary patterns are used to extract the facial feature so as to reduce the feature dimension. Third, an improved GA and Pareto optimization approach are used to select the optimal significant features. Fourth, the random forest classifier is chosen to achieve the feature classification. Subsequently, some comparative experiments are implemented. Finally, the conclusion is drawn and some future research topics are pointed out.
Findings
The experiment results show that the proposed facial expression recognition algorithm outperforms ones in the existing literature in terms of both the actuary and computational time.
Originality/value
The GA and Pareto optimization algorithm are combined to select the optimal significant feature. To improve the accuracy of the facial expression recognition, the GA is improved by adjusting an appropriate fitness evaluation function, and a new Pareto optimization model is proposed that contains two objective functions indicating the achievements in minimizing within-class variations and in maximizing between-class variations.