The reference-point played important roles in most algorithms of fingerprint recognition. It is widely used in fingerprint classification, and fingerprint matching. There are many methods proposed for reference point ...
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In this paper two fuzzy clustering algorithms, namely fuzzy C-means (FCM) and Gustafson Kessel clustering (GKC), have been used for detecting changes in multitemporal remote sensing images. Change detection maps are o...
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In this paper two fuzzy clustering algorithms, namely fuzzy C-means (FCM) and Gustafson Kessel clustering (GKC), have been used for detecting changes in multitemporal remote sensing images. Change detection maps are obtained by separating the pixel-patterns of the difference image into two groups. To show the effectiveness of the proposed technique, experiments are conducted on three multispectral and multitemporal images. Results are compared with those of existing Markov random field (MRF) & neural network based algorithms and found to be superior. The proposed technique is less time-consuming and unlike MRF do not need any a priori knowledge of distribution of changed and unchanged pixels (as required by MRF).
With extracted local features of a given image, computing its global feature under perceptual framework has shown promising performance in object recognition. However, under some tough applications with large intra-cl...
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In this paper, Bayesian decision theory is discussed. Bayesian decision related to the basic elements and the principles as well as the Bayes optimal decision criteria is introduced briefly. Its characteristics, advan...
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In this paper, Bayesian decision theory is discussed. Bayesian decision related to the basic elements and the principles as well as the Bayes optimal decision criteria is introduced briefly. Its characteristics, advantages and disavantages as well as the applicable targets are analysed in this paper, in the end, the new application situation is introduced.
We consider the problem of determining an unknown source, which depends only on the spatial variable, in a diffusion equation. This is an ill-posed problem. For a reconstruction of the solution from indirect data, the...
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We consider the problem of determining an unknown source, which depends only on the spatial variable, in a diffusion equation. This is an ill-posed problem. For a reconstruction of the solution from indirect data, the dual least squares method generated by the family of Shannon wavelet subspaces is applied. Moreover, a certain simple nonlinear modification of the method based on local refinements of the wavelet expansion of the noisy data is investigated.
This paper proposed a method of quaternion K-L transform and biomimetic patternrecognition (BPR) for color face recognition. The BPR aimed at optimal covering in the feature space R n using some complex geometric bo...
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ISBN:
(纸本)9781424447374;9781424447541
This paper proposed a method of quaternion K-L transform and biomimetic patternrecognition (BPR) for color face recognition. The BPR aimed at optimal covering in the feature space R n using some complex geometric bodies for cover samples distribution in R n approximately in order to ¿recognize¿. We used quaternion K-L transform to extract the Eigen-faces of training samples and algebraic feature components of each sample for training by BPR. The method was applied to the face database ¿faces94¿ in Essex University, and the experiments results indicated that the correct recognition rate reached to 96.67%, and proved its efficiency and feasibility for color face recognition, and also showed it was better than the performance of SVM.
This contribution introduces a software framework enabling researchers to develop real-time patternrecognition and sensor fusion applications in an abstraction level above that of common programming languages in orde...
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This contribution introduces a software framework enabling researchers to develop real-time patternrecognition and sensor fusion applications in an abstraction level above that of common programming languages in order to reduce and minimize programming errors and technical obstacles. Furthermore, a proof of concept using two separate instances of the process engine on different computers with audiovisual data processing is described. The scenario shows the capability of the engine to process data in realtime and synchronously on multiple machines, which are necessary features in large scale projects.
It has been shown that the flow and shear characteristics of granular particles such as soils are significantly dependent on the shape of the particles. This is important from a practical viewpoint because a fundament...
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ISBN:
(纸本)9781424433520
It has been shown that the flow and shear characteristics of granular particles such as soils are significantly dependent on the shape of the particles. This is important from a practical viewpoint because a fundamental understanding of granular behavior will lead to an improved understanding of soil stability and influence the design of structural foundations. Furthermore, the calculation of soil stability and consequently structural stability is particularly useful during earthquake events. In previous work, we have demonstrated the applicability of X-ray and optical' tomography measurements for characterizing 3-D shapes of natural sands and manufactured granular particles. In this paper, we extend the work to measure the arrangement and orientation of an assemblage of such particles. A combination of X-ray CT for measuring the coordinates of the individual particles, and basic image processing techniques for computing the local variations in packing density are employed to generate density maps. Such maps can be used to gain a more fundamental understanding of the shear characteristics of granular particles. In this paper, we demonstrate the success of our technique by exercising the method on two sets of granular particles - glass beads (used as a control) and Michigan Dune sand.
The application of adaptive neuro fuzzy inference system (ANFIS) to the partial discharge (PD) patternrecognition is presented in this paper. Four types of defect models are made according to the main reason of insul...
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ISBN:
(纸本)9781424447374;9781424447541
The application of adaptive neuro fuzzy inference system (ANFIS) to the partial discharge (PD) patternrecognition is presented in this paper. Four types of defect models are made according to the main reason of insulation failures in real power system. Experiments are carried out to acquire the sample data, from which eight statistical features are extracted to construct the ANFIS. Different characteristics of the proposed defect models are compared based on the extracted features. Then the ANFIS is trained by characteristic features. Testing samples are utilized to validate the performance of the recognition system. The result shows that ANFIS reaches a successful recognition rate in the application of PD pattern classification.
In this paper a practical, automated contour segmentation technique for digital radiography image is described. Digital radiography is an imaging mode based on the penetrability of x-ray. Unlike reflection imaging mod...
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