Corner point is one of the most important feature points in computer vision and pattern recognition. In this paper we introduce a new boundary-based corner detection method using wavelet transform for its ability for ...
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ISBN:
(纸本)081944278X
Corner point is one of the most important feature points in computer vision and pattern recognition. In this paper we introduce a new boundary-based corner detection method using wavelet transform for its ability for detecting sharp variations. Our idea is derived from Jiann-Shu Lee et al.'s algorithm, but, unlike them, we represent the orientation profile in an almost "continuous" way. Theoretical analysis and experimental results show that our method is effective in detecting corners.
LS MPP is a massively parallel processor It has fine-grained parallelism with up to 4096 processing elements arranged in a SIMD architecture The processing elements are arranged in 64 X 64 two-dimensional mesh-connect...
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ISBN:
(纸本)0819442836
LS MPP is a massively parallel processor It has fine-grained parallelism with up to 4096 processing elements arranged in a SIMD architecture The processing elements are arranged in 64 X 64 two-dimensional mesh-connected array for low-level imageprocessing In this paper, the system architecture the components of processing element array controller memory organization of LS MPP processor are described. In the final we have discussed the performance of LS MPP.
A new binary image lossless compressing method is proposed, which regards a binary image as being constructed of a limited number of fractal elements that have undergone a series of operations such as contraction/dila...
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ISBN:
(纸本)0819442798
A new binary image lossless compressing method is proposed, which regards a binary image as being constructed of a limited number of fractal elements that have undergone a series of operations such as contraction/dilation, embedding and jointing. Therefore, coding compression for an image is mainly a process of acquiring its specific fractal structure. This algorithm defines 16 basic elements of size 2x2, which can be dilated to power of 2 or put together side by side when of the same type to make up a self-similar element set in different *** element set constitutes the codebook of fractal-like-coding. Prior to coding, it is necessary to carry out decorrelation operation of an image and then perform sliding matching on the image with the elements to find the best matching element that meets appropriate matching merit. Record the error subimage that may have formed owing to incomplete matching. Then carry out dynamic segment designates coding for the error image featuring a sparse matrix form. Finally perform arithmetic coding for the code characters sequence obtained. It has been demonstrated by testing images of different complexities that the new method is very efficient to encode binary images.
The magnetic properties of Mn-Zn ferrite such as initial permeability, saturation magnetization, Curie temperature, resistivity and power loss are affected greatly by the Fe2+ content in the raw materials. The experim...
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The magnetic properties of Mn-Zn ferrite such as initial permeability, saturation magnetization, Curie temperature, resistivity and power loss are affected greatly by the Fe2+ content in the raw materials. The experimental results show that low resistivity (rho) and high eddy current loss (P-e) are induced by the superfluous Fe2+ content in the raw materials;the scant Fe2+ content in the raw materials will increase hysteresis loss (P-h) and decrease Curie temperature (T-c), saturation magnetization (M-s) and initial permeability (mu (i)). (C) 2001 Elsevier Science B.V. All rights reserved.
This paper presents a novel compression encoding/decoding method based on lift scheme for I-VOP. In traditional coding I-VOP algorithm, the textures and shapes are separately coded. and the macro-block DCT coding meth...
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ISBN:
(纸本)0819442798
This paper presents a novel compression encoding/decoding method based on lift scheme for I-VOP. In traditional coding I-VOP algorithm, the textures and shapes are separately coded. and the macro-block DCT coding method is adopted in the coding texture and 16 x 16 BAB (Binary Alpha Block) coding method is employed in shape coding. The texture and shape coding method is not of embed feature. The algorithm based on lift scheme for I-VOP, the texture and shape at same time is coded and the bit streaming is of embed feature.
Augmented reality is the merging of synthetic sensory information into a user's perception of a real environment. As one of the most important tasks in augmented scene modeling, terrain simplification research has...
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Augmented reality is the merging of synthetic sensory information into a user's perception of a real environment. As one of the most important tasks in augmented scene modeling, terrain simplification research has gained more and more attention. In this paper, we mainly focus on point selection problem in terrain simplification using triangulated irregular network. Based on the analysis and comparison of traditional importance measures for each input point, we put forward a new importance measure based on local entropy. The results demonstrate that the local entropy criterion has a better performance than any traditional methods. In addition, it can effectively conquer the 'short-sight' problem associated with the traditional methods.
This paper presents an unsupervised range image segmentation based on Kohonen neural network. At first, the derivative and partial derivative of each point are calculated and the normal in each points is gotten. With ...
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This paper presents an unsupervised range image segmentation based on Kohonen neural network. At first, the derivative and partial derivative of each point are calculated and the normal in each points is gotten. With the character vectors including normal and range value, self-organization map is introduced to cluster. The normal analysis is used to eliminate over-segmentation and the last result is gotten. This method avoid selecting original seeds and uses fewer samples, moreover computes rapidly. The experiment shows the better performance.
This paper discusses the research in small target detection in infrared images with heavy clutter background. For most infrared images, ship objects are rather dim in the relative dark sea surface background. The exis...
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This paper discusses the research in small target detection in infrared images with heavy clutter background. For most infrared images, ship objects are rather dim in the relative dark sea surface background. The existence of scan line disturbance and noise also increases the difficulty in proper detection. Dim objects must be distinguished from a dark background. On the other hand, the small targets must also be distinguished from clutters. Through analysis of the targets and background, we build characteristic models of small ship objects, noise and sea backgrounds respectively, and indicate their differences in spatial and frequency domains among them. Based on the principles of signal processing, pattern recognition and artificial intelligence, we propose a combined algorithm for detecting sea surface small targets. In this algorithm, components of background and noise are first suppressed by a multilevel filter designed accordingly, meanwhile enhancing the target ones of interest. The pixels of the candidate targets are then discriminated by minimum risk Bayes test. Finally, according to a priori knowledge about the targets such as the ranges of their sizes, the targets of interest can be detected. In particular, the related probability distributions used by statistic decision are obtained by offline learning of typical training samples. Experiments show that the algorithm is excellent for such kinds of target detection and is robust to noise.
Motivated by the need of the numerous real-world applications, 3D object recognition has become an active research field. The representation describes the sensed data and the object models, and it is a key issue in th...
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Motivated by the need of the numerous real-world applications, 3D object recognition has become an active research field. The representation describes the sensed data and the object models, and it is a key issue in the recognition process, which decides the match strategy and the effectiveness and robustness of the recognition system. In this paper, we propose an improved 3D object representation first, which computes the local signatures of a given basis polygon on the surface mesh, and converts the signatures to a 2D array called the distance-angle (DA) images by weighted bilinear interpolation. This representation is adaptive to free-form objects and resistant to occlusion and clutter. Compared with the original representation, it has a more distinct meaning, easier operation, and adaptation to different resolutions and irregular triangle meshes. Secondly, based on the improved representation, a novel 3D recognition algorithm is presented, which has multiresolution mesh based, coarse-to-fine recognition. By matching the DA image of a polygon in the scene surface mesh with the DA images of models at low resolution, a model candidate set is obtained. The set is filtered in the neighborhood of the matched polygons in a high-resolution mesh and verified by the model candidate sets of other polygons. Experiments show that this algorithm needs less computation and is very accurate and robust.
Because of wide variation in gray levels and particle dimensions and the presence of many small gravel objects in the background, as well as corrupting the image by noise, it is difficult o segment gravel objects. In ...
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Because of wide variation in gray levels and particle dimensions and the presence of many small gravel objects in the background, as well as corrupting the image by noise, it is difficult o segment gravel objects. In this paper, we develop a partial entropy method and succeed to realize gravel objects segmentation. We give entropy principles and fur calculation methods. Moreover, we use minimum entropy error automaticly to select a threshold to segment image. We introduce the filter method using mathematical morphology. The segment experiments are performed by using different window dimensions for a group of gravel image and demonstrates that this method has high segmentation rate and low noise sensitivity.
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