Safe traveling of the blind and vision-disabled people is a trouble in their daily lives. Pedestrian crossing area is an important traffic sign which should be recognized in the image-based blind aid devices. This pap...
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Safe traveling of the blind and vision-disabled people is a trouble in their daily lives. Pedestrian crossing area is an important traffic sign which should be recognized in the image-based blind aid devices. This paper proposes a method for extracting pedestrian crossing based on imageprocessing, which contains bipolarity testing, morphological operations, edge detection and radon transform techniques. By introducing a parameter "bipolarity" which represents the gray level contrast in an image, areas with strong contrast were selected. Morphology processing approaches were used to analysis and process noises in bipolarity image. According to the corresponding relationships between an image and its radon transform result, pedestrian crossing features, such as number and edge of pedestrian crossing stripes were extracted in transform domain. This algorithm was proved to be effective with 96.2% accuracy under the test of 54 real crossing images.
This paper presents a novel image fusion algorithm using an improved nonlinear wavelet-decomposition-scheme. The scheme is obtained by introducing redundancy in the max-lifting scheme. Experimental results based on re...
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This paper presents a novel image fusion algorithm using an improved nonlinear wavelet-decomposition-scheme. The scheme is obtained by introducing redundancy in the max-lifting scheme. Experimental results based on real-world images show that the proposed algorithm produces good results in medical image fusion and visual-infrared image fusion; moreover, it is computationally efficient as a shift-invariant scheme.
Two-dimensional gel electrophoresis (2DGE) images are extremely useful support for proteins analysis in the field of proteomics. The registration of 2DGE images is an important element for protein identification in bi...
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ISBN:
(纸本)9781424441327
Two-dimensional gel electrophoresis (2DGE) images are extremely useful support for proteins analysis in the field of proteomics. The registration of 2DGE images is an important element for protein identification in biological research while it is a complex and difficult problem. This paper proposes a new non-linear registration approach for 2DGE images, which is based on the exploitation of both spot distance measure and spot intensity. The method consists of three steps: multi-resolution affine registration, spot pairing, and thin-plate spline interpolation. The results on both simulated and real gel images show that the proposed method significantly improves registration accuracy in comparison with traditional registration techniques and has promising use in practical gel image analysis systems in proteomics.
To segment CT (computed tomography) images of liver cancer effectively, a new method based on Snake model was proposed. image segmentation based on threshold was combined with image segmentation based on Snake model, ...
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To segment CT (computed tomography) images of liver cancer effectively, a new method based on Snake model was proposed. image segmentation based on threshold was combined with image segmentation based on Snake model, and a contour correction process was added. This method obtains a better result on liver cancer CT images segmentation, overcomes the defect that traditional Snake model can not segment the images with serious depressions. The results of the experiment demonstrate that this algorithm is an effective method for segmenting the liver cancer image.
A new Combinatorial Ricci curvature and Laplacian operators for grayscale images are introduced and tested on 2D synthetic, natural and medical images. The effectiveness of the notions introduced herein, as compared w...
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A new Combinatorial Ricci curvature and Laplacian operators for grayscale images are introduced and tested on 2D synthetic, natural and medical images. The effectiveness of the notions introduced herein, as compared with more classical methods, is shown by a variety of experimental results. Analogue formulae for voxels are also obtained. This novel approach is based upon more general concepts developed by R. Forman. Further applications, in particular a fitting Ricci flow, are discussed.
To improve insufficiently available satellite and solve the anomaly geometry, normal GPS system and its mentioned drawbacks are simulated. Based on the analysis of anomaly examples, singular value decomposition (SVD) ...
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To improve insufficiently available satellite and solve the anomaly geometry, normal GPS system and its mentioned drawbacks are simulated. Based on the analysis of anomaly examples, singular value decomposition (SVD) is applied to settle the anomaly and its effect on precision is investigated. Then pseudolites with proper geometry are laid to increase the number of measurements and advance the geometry to compare with the only GPS normal and anomaly system. The results show that added pseudolites not only solve the problem of no or not good navigation and position solution without enough available measurements, but resolve the lower precision and clock bias because of the anomaly geometry to obtain the required dilution of precision and right clock value.
In this paper, we present an overview and experimental comparison of a large number of image descriptors for content-based retrieval of X-ray images. The paper concludes with recommendations which descriptors are most...
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In this paper, we present an overview and experimental comparison of a large number of image descriptors for content-based retrieval of X-ray images. The paper concludes with recommendations which descriptors are most suitable for content-based retrieval of X-ray images. The local features invariant to scale, translation and rotation give best results. The features were integrated in content-based retrieval system for X-ray images. The system supports querying by image to find visually similar images to presented query. To employ multiple visual features to characterize image content we developed simple feature aggregation scheme.
An improved level set framework for fast segmentation based on single parameter is presented. The traditional level set methods for image segmentation need inevitably too many parameters adjustment and they have usual...
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An improved level set framework for fast segmentation based on single parameter is presented. The traditional level set methods for image segmentation need inevitably too many parameters adjustment and they have usually lower computationally implementation. To solve this problem, the proposed method improves the C-V PDE model by adding a penalized energy term and replacing the dirac function with the norm of level set function gradient. Besides, only the parameter of the length term is reserved in the model and an evolution criterion is introduced for the value rules of this single parameter. The experimental results of synthesized and biomedicalimages show that the new method is faster and more robust. Moreover, the new method has more extensive adaptability on account of the zero level set function being set anyplace freely and the single parameter adjustment convenience.
Objective to develop a signalprocessing system based on FPGA used in digital ophthalmology ultrasongraphy to process echo signals. Methods main signalprocessing technique used in the system includes interpolation, d...
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Objective to develop a signalprocessing system based on FPGA used in digital ophthalmology ultrasongraphy to process echo signals. Methods main signalprocessing technique used in the system includes interpolation, dynamic filter, TGC, envelop demodulation and logarithmic amplifier. In FPGA, a schematic file acts as the top module, and hardware describe language VHDL act as bottom modules. Results By building a physical simulation model, the validity of each phases in signalprocessing of the system has been validated. By detecting normal human eyes and orbits, the echo signals gained are all right. Conclusion The system has good ability to process high frequency ultrasonic echo signals of ophthalmology in real time. It has reached design demands, and shows a good application prospect.
The coil sensitivity distribution is one of the most essential elements of any parallel imaging methods, which provides the spatial information for unfolding the aliased images due to under sampling. In general, there...
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The coil sensitivity distribution is one of the most essential elements of any parallel imaging methods, which provides the spatial information for unfolding the aliased images due to under sampling. In general, there are two basic calibration methods to obtain the coil information: pre-scan and autocalibration. In this paper, the standard and advanced calibrating methods for coil sensitivity estimation are firstly reviewed. Secondly, in vivo applications of the up-to date methods are accomplished. Finally, the problems of these calibration methods are post. At last, the paper has outlined the practical considerations of the calibration techniques.
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