Four parameters, φ (electronegativity), nws1/3 (valence electron density in Wagner-Seitz cell),R (Pauling's metallic radius) and Z (number of valence electrons in atom), and the patternrecognition methods were u...
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Four parameters, φ (electronegativity), nws1/3 (valence electron density in Wagner-Seitz cell),R (Pauling's metallic radius) and Z (number of valence electrons in atom), and the patternrecognition methods were used to investigate the regularities of formation of ternary intermetallic compounds between three transition elements. The obtained mathematical model expressed by some inequalities can be used as a criterion of ternary compound formation in "unknown" phase diagrams of alloy systems.
Recently, many image encryption algorithms based on chaos have been proposed. Most of the previous algorithms encrypt components R, G, and B of color images independently and neglect the high correlation between them....
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Recently, many image encryption algorithms based on chaos have been proposed. Most of the previous algorithms encrypt components R, G, and B of color images independently and neglect the high correlation between them. In the paper, a novel color image encryption algorithm is introduced. The 24 bit planes of components R, G, and B of the color plain image are obtained and recombined into 4 compound bit planes, and this can make the three components affect each other. A four-dimensional(4D) memristive hyperchaotic system generates the pseudorandom key streams and its initial values come from the SHA 256 hash value of the color plain image. The compound bit planes and key streams are confused according to the principles of genetic recombination, then confusion and diffusion as a union are applied to the bit planes,and the color cipher image is obtained. Experimental results and security analyses demonstrate that the proposed algorithm is secure and effective so that it may be adopted for secure communication.
A robust face pose estimation approach is proposed by using face shape statistical model approach and pose parameters are represented by trigonometric functions. The face shape statistical model is firstly built by an...
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A robust face pose estimation approach is proposed by using face shape statistical model approach and pose parameters are represented by trigonometric functions. The face shape statistical model is firstly built by analyzing the face shapes from different people under varying poses. The shape alignment is vital in the process of building the statistical model. Then, six trigonometric functions are employed to represent the face pose parameters. Lastly, the mapping function is constructed between face image and face pose by linearly relating different parameters. The proposed approach is able to estimate different face poses using a few face training samples. Experimental results are provided to demonstrate its efficiency and accuracy.
A novel latent semantic indexing （LSI） approach for content-based image retrieval is presented in this paper. Firstly, an extension of non-negative matrix factorization （NMF） to supervised initialization is discus...
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A novel latent semantic indexing （LSI） approach for content-based image retrieval is presented in this paper. Firstly, an extension of non-negative matrix factorization （NMF） to supervised initialization is discussed. Then, supervised NMF is used in LSI to find the relationships between low-level features and high-level semantics. The retrieved results are compared with other approaches and a good performance is obtained.
Smooth interpolants defined over tetrahedra are currently being developed for they have many applications in geography, solid modeling, finite element analysis, etc. In this paper, we will characterize a certain class...
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Smooth interpolants defined over tetrahedra are currently being developed for they have many applications in geography, solid modeling, finite element analysis, etc. In this paper, we will characterize a certain class of C-1 discrete tetrahedral interpolants with only C-1 data required. As special cases of the class characterized, we give two C-1 discrete tetrahedral interpolants which have concise expressions.
A color-based visual technique is described based on the mean shift image segmentation method providing relevant information for robust localization of the visible road area in Urban Intelligent Transportation System ...
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A color-based visual technique is described based on the mean shift image segmentation method providing relevant information for robust localization of the visible road area in Urban Intelligent Transportation System (U-ITS). The traffic image sequences are firstly trained to extract the background and then segmented into separated parts by the mean shift method as initialization, regions with the number of pixels not less than a threshold and with more uniform surfaces with the 'same' color compared to their environment are filtered as recognized road area. The algorithm given in this paper can present road area recognition with arbitrary shapes, which is fit for unstructured road applications in urban cities very well.
Elliptical splats are used to represent and render the isosurface of volume data. The method consists of two steps. The first step is to extract points on the isosurface by looking up the case table. In the second ste...
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Elliptical splats are used to represent and render the isosurface of volume data. The method consists of two steps. The first step is to extract points on the isosurface by looking up the case table. In the second step, properties of splats are computed based on local geometry. Rendering is achieved using surface splatting algorithm. The obtained results show that the extraction time of isosurfaces can be reduced by a factor of three. So our approach is more appropriate for interactive visualization of large medical data than the classical marching cubes (MC) technique.
Pupil localization is a very important preprocessing step in many reel applications. Accurate and robust pupil localization in non-ideal eye images is a challenging task. A detailed method of pupil localization in non...
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Pupil localization is a very important preprocessing step in many reel applications. Accurate and robust pupil localization in non-ideal eye images is a challenging task. A detailed method of pupil localization in non-ideal eye images is proposed. This method is implemented in three main phases： first, segment the rough pupil region based on Gaussian Mixture Model： then modify the rough segmentation result using morphological method to minimize the influence of some disturbing factors; last estimate the pupil parameters based on minimizing the least square error. The proposed method is first tested on CASIA iris image dataset, and then on our self-captured iris dataset which contains a wider variety of iris images. Experiments show that the proposed method can perform well for nonideal eye images of various qualities.
In this paper,we consider unusual event detection problem in a novel viewpoint and provide an algorithm to solve the *** actions or events in the scene is usual or not will eventually be reflected on the changes of so...
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In this paper,we consider unusual event detection problem in a novel viewpoint and provide an algorithm to solve the *** actions or events in the scene is usual or not will eventually be reflected on the changes of some basic *** summarize these basic event features and propose special representation for each of *** we can model these features in a uniform mode using adaptive Gaussian mixture *** and unsupervised unusual event detection algorithm can be designed to fit various situations based on this *** superiority of our model is that it can detect unusual event automatically without to know the determinate model of unusual *** conclusion,we provide two applications to verify the effectiveness of our model.
A semiautomatic segmentation method based on active contour is proposed for computed tomography (CT) image series. First, to get initial contour, one image slice was segmented exactly by C-V method based on Mumford-Sh...
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A semiautomatic segmentation method based on active contour is proposed for computed tomography (CT) image series. First, to get initial contour, one image slice was segmented exactly by C-V method based on Mumford-Shah model. Next, the computer will segment the nearby slice automatically using the snake model one by one. During segmenting of image slices, former slice boundary, as next slice initial contour, may cross over next slice real boundary and never return to right position. To avoid contour skipping over, the distance variance between two slices is evaluated by an threshold, which decides whether to initiate again. Moreover, a new improved marching cubes (MC) algorithm based on 2D images series segmentation boundary is given for 3D image reconstruction. Compared with the standard method, the proposed algorithm reduces detecting time and needs less storing memory. The effectiveness and capabilities of the algorithm were illustrated by experimental results.
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