Human's real life is within a colorful world. Compared to the gray images, color images contain more information and have better visual effects. In today's digital imageprocessing, image segmentation is an im...
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Human's real life is within a colorful world. Compared to the gray images, color images contain more information and have better visual effects. In today's digital imageprocessing, image segmentation is an important section for computers to "understand" images and edge detection is always one of the most important methods in the field of image segmentation. Edges in color images are considered as local discontinuities both in color and spatial domains. Despite the intensive study based on integration of single-channel edge detection results, and on vector space analysis, edge detection in color images remains as a challenging issue.
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.
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.
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.
A novel approach based on independent component analysis (ICA) for speckle filtering and target extraction of synthetic aperture radar (SAR) images is proposed using adaptive space separation with weighted information...
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A novel approach based on independent component analysis (ICA) for speckle filtering and target extraction of synthetic aperture radar (SAR) images is proposed using adaptive space separation with weighted information entropy (WIE) incorporated. First the basis and the independent components are respectively obtained by ICA technique, and WIE of the image is computed; then based on the threshold computed from function T-WIE (threshold versus weighted-information-entropy), independent components are adaptively separated and the bases are classified accordingly. Thus, the image space is separated into two subspaces: "clean" and "noise". Then, a proposed nonlinear operator ABO is applied on each component of the 'clean' subspace for further optimization. Finally, recovery image is obtained reconstructing this subspace and target is easily extracted with binarisation. Note that here T-WIE is an interpolated function based on several representative target SAR images using proposed space separation algorithm.
When applying formal majority voter in TMR (triple modular redundancy) fault tolerance system with two error injections, there is a problem that formal majority voter has a low rate of output. To solve this problem, w...
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When applying formal majority voter in TMR (triple modular redundancy) fault tolerance system with two error injections, there is a problem that formal majority voter has a low rate of output. To solve this problem, we propose a modified majority voting model with special rules. In the situation of error injection, test result shows that compared with formal majority voter, modified majority voter has a higher rate of correct decision and a lower ratio of benign signals.
Automatic recognition of artists is very important in acoustic music indexing, browsing, and contentbased acoustic music retrieving, but synchronously it is still a challenging errand to extract the most representativ...
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Automatic recognition of artists is very important in acoustic music indexing, browsing, and contentbased acoustic music retrieving, but synchronously it is still a challenging errand to extract the most representative and salient attributes to depict diversiform artists. In this paper, we developed a novel system to complete the reorganization of artist automatically. The proposed system can efficiently identify the artist's voice of a raw song by analyzing substantive features extracted from both pure music and singing song mixed with accompanying music. The experiments on different genres of songs illustrate that the proposed system is possible.
The sensitivity of diffuse optical tomography （DOT） imaging exponentially decreases with the increase of photon penetration depth, which leads to a poor depth resolution for DOT. In this letter, an exponential adjus...
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The sensitivity of diffuse optical tomography （DOT） imaging exponentially decreases with the increase of photon penetration depth, which leads to a poor depth resolution for DOT. In this letter, an exponential adjustment method （EAM） based on maximum singular value of layered sensitivity is proposed. Optimal depth resolution can be achieved by compensating the reduced sensitivity in the deep medium. Simulations are performed using a semi-infinite model and the simulation results show that the EAM method can substantially improve the depth resolution of deeply embedded objects in the medium. Consequently, the image quality and the reconstruction accuracy for these objects have been largely improved.
In this article, we present an approach for the automated extraction of quantitative information about trichome patterning on leaves of Arabidopsis thaliana. Time series of growing rosette leaves (4D confocal datasets...
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ISBN:
(纸本)9781424439317
In this article, we present an approach for the automated extraction of quantitative information about trichome patterning on leaves of Arabidopsis thaliana. Time series of growing rosette leaves (4D confocal datasets, 3D + time) are used for this work. At first, significant anatomical structures, i.e. leaf surface and midplane are extracted robustly. Using the extracted anatomical structures, a biological reference coordinate system is registered to the leaves. The performed registration allows to determine intra- as well as inter-series spatiotemporal correspondences. Trichomes are localized by first detecting candidates using Hough transform. Then, local 3D invariants are extracted and the candidates are validated using a Support Vector Machine (SVM).
A closed form solution to the problem of segmenting multiple 3D motion models was proposed from straight-line optical flow. It introduced the multibody line optical flow constraint (MLOFC), a polynomial equation relat...
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A closed form solution to the problem of segmenting multiple 3D motion models was proposed from straight-line optical flow. It introduced the multibody line optical flow constraint (MLOFC), a polynomial equation relating motion models and line parameters. The motion models can be obtained analytically as the derivative of the MLOFC at the corresponding line measurement, without knowing the motion model associated with that line. Experiments on real and synthetic sequences were also presented.
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