A novel algorithm of global motion estimation is proposed. First, through Gabor wavelet transform (GWT), a kind of energy distribution of image is obtained and checkpoints are selected according to a probability decis...
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A novel algorithm of global motion estimation is proposed. First, through Gabor wavelet transform (GWT), a kind of energy distribution of image is obtained and checkpoints are selected according to a probability decision approach proposed. Then, the initialized motion vectors are obtained via a hierarchal block-matching based on these ***, by employing a 3-parameter motion model, precise parameters of global motion are found. From the experiment, the algorithm is reliable and robust.
＜正＞Researches indicate that the gray-scale images mapped from most nature objects accord to the fractal Brown stochastic field which foundation is self-similarity,an image is self-similarity means the image is made...
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ISBN:
(纸本)0780394224
＜正＞Researches indicate that the gray-scale images mapped from most nature objects accord to the fractal Brown stochastic field which foundation is self-similarity,an image is self-similarity means the image is made up of copies of itself in a reduced *** fractal dimension can quantificational depict the fractal character and the property of an image. Therefore,a new method based-on fractal dimension to fuse mid-wave infrared images and long-wave infrared images is presented in the ***,images are decomposed into different scale using wavelet ***,the fractal dimensions of sub-images of original images are computed,and then take them as weight to fuse sub-images at the same level according to different ***,reconstruct the fused images by wavelet inverse *** experimental results imply that the method can effectively preserve the information of source images with a high contrast and may be very practical.
Many applications using wireless sensor networks (WSNs) aim at providing friendly and intelligent services based on the recognition of human's *** the research result on wearable computing has been fruitful,our ex...
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Many applications using wireless sensor networks (WSNs) aim at providing friendly and intelligent services based on the recognition of human's *** the research result on wearable computing has been fruitful,our experience indicates that a user-free sensor deployment is more natural and acceptable to *** our system,activities were recognized through matching the movement patterns of the objects,which tri-axial accelerometers had been attached to. Several representative features,including accelerations and their fusion,were calculated and three classifiers were tested on these *** with Decision Tree(DT) C4.5 and Multiple-Layer Perception(MLP),Support Vector Machine (SVM) performs relatively well across different tests. Additionally,feature selection will be discussed for better system performance for WSNs.
Dental Panoramic X-ray images are images having complex content, because several layers of tissue, bone, fat, etc. are superimposed. Non-uniform illumination, stemming from the X-ray source, gives extra modulation to ...
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A novel diversity-sampling based nonparametric multi-modal background model is proposed. Using the samples having more popular and various intensity values in the training sequence, a nonparametric model is built for ...
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A novel diversity-sampling based nonparametric multi-modal background model is proposed. Using the samples having more popular and various intensity values in the training sequence, a nonparametric model is built for background subtraction. According to the related intensifies, different weights are given to the distinct samples in kernel density estimation. This avoids repeated computation using all samples, and makes computation more efficient in the evaluation phase. Experimental results show the validity of the diversity- sampling scheme and robustness of the proposed model in moving objects segmentation. The proposed algorithm can be used in outdoor surveillance systems.
Color quantization is wildly exploited for many applications especially in the fields of computer graphics and imageprocessing. After studying the approaches of color clustering, a new approach based on ant colony cl...
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ISBN:
(纸本)0769523153
Color quantization is wildly exploited for many applications especially in the fields of computer graphics and imageprocessing. After studying the approaches of color clustering, a new approach based on ant colony clustering algorithm applied in color image quantization is proposed in the paper. According to the picking up-dropping theory, a promoted ant algorithm is applied to group colors into certain clusters in RGB space. It finishes color quantization after colors mapping of every pixel. Our experiment shows that the algorithm proposed in this paper has rather good performance with an excellent robustness, a less time consumption, and a simple realization.
Feature selection is a process where a minimal feature subset is selected from an original feature set according to a certain measure. In this paper, feature relevancy is defined by an inconsistency rate. A bidirectio...
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Feature selection is a process where a minimal feature subset is selected from an original feature set according to a certain measure. In this paper, feature relevancy is defined by an inconsistency rate. A bidirectional automated branch and bound algorithm is presented. It is a new complete search algorithm for feature selection, which performs feature deletion and feature addition in parallel. Its bound is determined by inconsistency rate of the original feature set, hence termed as ‘automated’. Experimental study shows that it is fit for feature selection.
Archaeology is at a point where it can benefit greatly from the application of computer vision methods, and in turn provides a large number of new, challenging and interesting conceptual problems and data for computer...
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Archaeology is at a point where it can benefit greatly from the application of computer vision methods, and in turn provides a large number of new, challenging and interesting conceptual problems and data for computer science. This is true in particular in the study of ceramics - the most abundant and widespread of all archaeological finds. The traditional way of documenting archaeological sherds is to draw the profile line, which is the intersection of a sherd along the axis of symmetry. A profilograph is a mechanical device, which can directly acquire and transfer a profile line by pin-pointing the profile on a sherd to a computer. We developed a fully automated vision system, which is able to compute the profile line out of the acquired 3D model of the fragment. In this paper we want to give a thorough comparison between the traditional manual approach, the profilograph and our system and present an improvement of the robustness of our approach by finding circular rills on the fragments. Practical experiments have been undertaken at the excavation Tel Dor in Israel.
A novel two-stage level set evolution method for detecting man-made objects in aerial images is described. The method is based on a modified Mumford-Shah model and it uses a two-stage curve evolution strategy to get a...
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ISBN:
(纸本)0769523722
A novel two-stage level set evolution method for detecting man-made objects in aerial images is described. The method is based on a modified Mumford-Shah model and it uses a two-stage curve evolution strategy to get a preferable detection. It applies fractal error metric, developed by Cooper, et al. (1994) at the first curve evolution stage and adds additional constraint texture edge descriptor that is defined by using DCT (discrete cosine transform) coefficients on the image at the next stage. Man-made objects and natural areas are optimally differentiated by evolving the partial differential equation. The method artfully avoids selecting a threshold to separate the fractal error image, while an improper threshold often results in great segmentation errors. Experiments of the segmentation show that the proposed method is efficient.
An effective approach to the detection and tracking of small moving targets with low contrast is proposed. In our application, small moving targets are detected and tracked in a low quality video sequence captured fro...
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ISBN:
(纸本)0780390059
An effective approach to the detection and tracking of small moving targets with low contrast is proposed. In our application, small moving targets are detected and tracked in a low quality video sequence captured from an airborne platform. The detection and tracking system includes three modules. First, the global motion parameters are estimated using fast least trimmed squares (FAST-ITS) regression and hierarchical processing. Once the global motion is robustly estimated, relatively stationary background can be eliminated almost completely through image warping. Then a motion-based fast target detector selects candidate pixels of the moving targets with motions statistically different from that of the background, and a particle filtering tracker examines the temporal consistency of targets to identify them and update their states. Information in the system flows in a closed loop form, in which the tracker instructs the detector where to look for a target, and the detector returns what it has found. Experimental results prove that the proposed method can reliably and effectively detect and track the real small moving target in real-time even if there is strong clutter influence.
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