Based on the fusion of color and gradient features, this paper implements a novel approach to real-time background subtraction. Firstly, an energy function is defined based on the fusion of color and gradient features...
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Based on the fusion of color and gradient features, this paper implements a novel approach to real-time background subtraction. Firstly, an energy function is defined based on the fusion of color and gradient features. Secondly, the graph cuts based algorithm is employed to minimize energy function and segment the foreground. Finally, average optical flow is used to make inference about the validity of foreground regions, background models are then updated. The experimental results of different real scenes show that the proposed approach can produce real-time detection and promising results.
The current color transfer methods always use statistics as transfer function and can not deal with images with lower similarity. In this paper, a section by section color transfer method is presented, in which all th...
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The current color transfer methods always use statistics as transfer function and can not deal with images with lower similarity. In this paper, a section by section color transfer method is presented, in which all the source images and reference images are segmented into a series of homogeneous regions, in which variations between classes are big and variations within classes are small, and then the color between the corresponding regions are transferred. The experiments show that the algorithm is efficient, the results are satisfactory, and it can be applied to complicated images with lower similarity.
This paper proposes an edge detection scheme based on Fresnel diffraction mode. Since Fresnel diffraction is mathematically complex, it is simplified into a linear convolution filter. Experiments on images are compare...
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This paper proposes an edge detection scheme based on Fresnel diffraction mode. Since Fresnel diffraction is mathematically complex, it is simplified into a linear convolution filter. Experiments on images are compared with the Laplacian of Gaussian, Sobel and Canny edge detection algorithms. The experimental results indicate that the new detector's result is comparable to Canny detector and agree more with human's recognition. And it also can get an even better edge map on some regions which contain abundant local details or some tiny changes.
The analytical study of a large scale nonlinear neural network is an uneasy *** try to analyze the function of neural systems by probing into the fuzzy logical framework of the neural ceUs'dynamical *** papers inv...
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ISBN:
(纸本)0780394224
The analytical study of a large scale nonlinear neural network is an uneasy *** try to analyze the function of neural systems by probing into the fuzzy logical framework of the neural ceUs'dynamical *** papers investigate the relation between fuzzy logic and neural *** most investigations focus on finding new function of neural system by combining fuzzy logical and neural system. In this paper,a novel approach is used to understand the nonlinear dynamic characteristics of neural system by analyzing the fuzzy logic framework of neural *** is the only way to understand the behavior of a large scale nonlinear neural *** abstracting the fuzzy logical framework of a neural cell,our analysis enables the delicate design of network *** an example,a difficulty task to build a recurrent network model of primary visual cortex by common dynamical analysis can be easily completed by this kind approach.
NKI contains a multi-domain oriented and large scale knowledge base. Text corpus is an important knowledge source of it. This paper presents an ontology-driven and integrated multi-agent architecture (MAKAT) for achie...
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Based on Jordan curve theorem, a universal classification method based on hyper surface is recently put forward. The experiments show that the new method can efficiently and accurately classify large data size up to 1...
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As a suitable tool for analyzing concept interconnection formally, the theory of Formal Concept Analysis (FCA) is applied. FCA deals with formal mathematical tools and techniques to develop and analyze relationship be...
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As a suitable tool for analyzing concept interconnection formally, the theory of Formal Concept Analysis (FCA) is applied. FCA deals with formal mathematical tools and techniques to develop and analyze relationship between concepts and to develop concept structures, and concepts are important building blocks in the concept-interconnection. This paper mainly discusses how FCA can be used to support concept-interconnection analysis from an application point of view. In order to introduce our idea, two kinds of concept-interconnection and interconnection measure in detail are discussed. One is based on Concept-Backbone and the other is based on the attributes. It is seen that FCA can support the building of concept-interconnection as a learning technique, but the established concept-interconnection also can be analyzed by using techniques of FCA.
Two algorithms for the phase retrieval of hard X-ray in-line phase contrast imaging are presented. One is referred to as Iterative Angular Spectrum Algorithm (IASA) and the other is a hybrid algorithm that combines IA...
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Two algorithms for the phase retrieval of hard X-ray in-line phase contrast imaging are presented. One is referred to as Iterative Angular Spectrum Algorithm (IASA) and the other is a hybrid algorithm that combines IASA with TIE (transport of intensity equation). The calculations of the algorithms are based on free space propagation of the angular spectrum. The new approaches are demonstrated with numerical simulations. Comparisons with other phase retrieval algorithms are also performed. It is shown that the phase retrieval method combining the IASA and TIE is a promising technique for the application of hard X-ray phase contrast imaging.
Gait is an identifying biometric feature. In recent years, Video-based gait recognition is becoming a new challenging problem in the field of computer vision. In this paper, wavelet reflective symmetry moments (WRSMs)...
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Gait is an identifying biometric feature. In recent years, Video-based gait recognition is becoming a new challenging problem in the field of computer vision. In this paper, wavelet reflective symmetry moments (WRSMs) have been proposed to describe and recognize gait automatically. WRSMs represent the appearance of people with merits of moments and wavelet analysis and reflect people's symmetrical walking habit. Moments have translation, scale and rotation invariant characteristics;while wavelet analysis is able to extract the multi-resolution features subtly and deal with noise. So combination of wavelet moments and reflective symmetry not only has characteristics of moments and wavelet analysis, but also is in accordance with one of the relative results in psychological researches which state that gait is a type of symmetrical model. Experiments based on USF's database have shown that the application of wavelet reflective symmetry moments in gait recognition leads to relatively high distinguishability of gait with effective noise handling.
The naïve Bayesian classifier (NBC) is a simple yet very efficient classification technique in machine learning. But the unpractical condition independence assumption of NBC greatly degrades its performance. Ther...
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