检索结果-内蒙古大学图书馆

2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

作者： SHENG ZHENG JIAN LIU WEN-ZHONG SHI GUANG-XI ZHU Electronic & Information Engineering Dept. Huazhong University of Science and Technology Wuhan 430 State Education Commission Key Laboratory for Image Processing and Intelligent Control Inst.for Pat Advanced Research Center for Spatial Information Technology Department of Land Surveying and Geo-In Chinese Key lab of optic & electronics Huazhong University of Science and Technology Wuhan 430074

In this paper, a unique road contour extraction approach from high resolution satellite image is proposed, in which the road contour was extracted in two steps. Firstly, support vector machines (SVM) was employed merely to classify the image into two groups of categories: a road group and a non-road group. The identified road group images are the discrete and irregularly distributed sampled points, and they are an uncompleted data set for the road. Secondly, the road contour was extracted from the road group images using the tensor voting framework, since the tensor voting technique is superior to the traditional methods in extracting the geometrical structure from the uncompleted data set. The experimental results on the high resolution satellite image demonstrate that the proposed approach worked well with images comprised by both rural and urban area features.

关键词： Tensor voting framework Road central line extraction High-resolution satellite image

来源：评论

学校读者我要写书评

暂无评论

Fast DCT-I, DCT-III, and DCT-IV via Moments

引用

Eurasip Journal on Applied Signal processing 2005年第12期2005卷 1902-1909页

作者： Liu, J.G. Liu, Y.Z. Wang, G.Y. Key Laboratory of Education Huazhong University of Science and Technology Ministry for Image Processing and Intelligence Control Wuhan 430074 China Department of Computer Science and Engineering China University of Geosciences Wuhan 430074 China Key Laboratory of State Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology China Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology China

This paper presents a novel approach to compute DCT-I, DCT-III, and DCT-IV. By using a modular mapping and truncating, DCTs are approximated by linear sums of discrete moments computed fast only through additions. This enables us to use computational techniques developed for computing moments to compute DCTs efficiently. We demonstrate this by applying our earlier systolic solution to this problem. The method can also be applied to multidimensional DCTs as well as their inverses. © 2005 Hindawi Publishing Corporation.

关键词： Method of moments

来源：评论

学校读者我要写书评

暂无评论

An algorithm for radar scene matching based on multi-area selection using fuzzy sets

An algorithm for radar scene matching based on multi-area se...

引用

MIPPR 2005: image Analysis Techniques

作者： Yang, Weidong Zuo, Zhengrong Zhang, Tianxu Mao, Haicen State Key Laboratory of Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

Radar scene matching technique has been widely found in many application fields such as remote sensing, navigation, terrain-map match, scenery variance analysis and so on. Radar image geometry is quite different from that of optical satellite imagery, whose imaging is a slanting imaging of electromagnetic microwave reflection. The different characters between radar image and optical satellite images are very distinct, such as the layover distortion of ground-truth and speckle noise, which degrades the image to such an extent that the features are very unclear and difficult to be extracted. So the factors such as the hypsography, ground truth, sensor altitude and imaging time should be taken into account for radar image and optical image matching. In this paper, we develop an image match algorithm based on reference map multi-area selection using fuzzy sets. image matching is generally a procedure that calculates the similarity measurement between sensed image and the corresponding intercepted image in reference map and it searches the maximum position in the correlation map. Our method adopts a converse matching strategy which selects multi-areas in optical reference map using fuzzy sets as model images, then match them on the sensed image respectively by normalized cross correlation matching algorithm and fuse the match results to get the optimum registered position. Multi-areas selection mainly considers two influence factors such as ground-truth texture features and the hypsography (DEM) of imaging region, which will suppress the influence of great variance imaging region. Experiment results show the method is effective in registering performance and reducing the calculation.

关键词： Remote sensing

来源：评论

学校读者我要写书评

暂无评论

A New Scrambling Method Based on Semi-frequency Domain and Chaotic System

A New Scrambling Method Based on Semi-frequency Domain and C...

引用

2005 International Conference on Neural Networks and Brain(ICNN&B’05)

作者： Tao Li Shaowu Zhou Zhaofu Zeng Qingli Ou School of Information and Electrical Engineering Hunan University of Science and Technology Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science & Technology

ISBN: (纸本)0780394224

A new digital image scrambling method based on DCT and chaos maps is presented in this *** the chaotic system in semi-frequency domain,all the pixels of the original image are rearranged and *** procedure of the algorithm is roughly divided into three steps:first,an original image is decomposed for its first variable by 1-D DCT, then modulated by chaos system,a primary scrambling result is achieved,at last,after by inverse 1-D DCT for the scrambling result,repeating the same procedure for the second variable,a final scrambling result is obtained for the original *** confirm the robustness of the novel method,some robustness testing experiments are carried out on the scrambling *** experimental results shows that the method succeeds in enduring several kinds of common image attacks,such as cropping,noise and rotation.

关键词： image security image scrambling chaotic sequences DCT(the discrete cosine transform)

来源：评论

学校读者我要写书评

暂无评论

Three-dimensional double directional filter for tracking and detecting moving dim weak target

Three-dimensional double directional filter for tracking and...

引用

MIPPR 2005: image Analysis Techniques

作者： Li, Meng Zhang, Tianxu Yang, Weidong Mao, Haiceng State Education Commission Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

The aim of the present work is to assess the performance of three-dimensional Double Directional Filtering (TDDDF) algorithm for detecting and tracking a weak moving dim target against a complex cluttered background in infrared image sequences. This paper proposes an novel TDDDF to improve the integrated signal-to-clutter ratio (ISCR) and enhance the three-dimensional directional filter's (TDDF) target energy accumulation ability further. Since the TDDDF do well to whitening noise (or quasi whitening noise) but not so sensitive to complex cloudscene background, prior to the filtering, a newly pre-whitening method termed Spatial-Temporal Adaptive Filtering algorithm is used here to suppress clutter background. Extensive experiment results demonstrate the proposed algorithm's ability in detecting weak dim point target against cloud-cluttered background. Finally, performance comparisons of the proposed algorithm and TDDF, on real IR image data, are presented in which the advantages of the proposed TDDDF filters are shown.

关键词： Tracking (position)

来源：评论

学校读者我要写书评

暂无评论

Runway detection of an unmanned landing aerial vehicle based on vision

Runway detection of an unmanned landing aerial vehicle based...

引用

MIPPR 2005: SAR and Multispectral image processing

作者： Wang, Hongqun Peng, Jiaxiong Li, Lingling Institute for Pattern Recognition and Artificial Intelligence State Education Commission Key Laboratory for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074

When an monocular vision-based unmanned aerial vehicle (UAV) based on vision is flown to the final approach fix to intercept the glide slope without the navigation of Global Positioning System (GPS), the position and orientation of the airport runway in image must be detected accurately so as to a host of suitable procedures have to be followed. The optimum length of the final approach is about five miles from the runway threshold. The front view of the runway, which is achieved at the moment, is very illegible. The approaching marking (cross bar) of the runway are showed as some white spots of high intensity and the complicated backgrounds of the airport are included in the images. In this case, spots with high intensity should be extracted and classified, some of these spots are just the images of the background noises and the pseudo-targets, which can't be separated with the spots of the runway as in the view there is no significant characteristic difference among them ostensibly. Fortunately, in the terrestrial coordinate space, most of the runway marks are located at the apexes of a rectangle, having some geometric relationships. The relationship among the projection coordinates of the runway spots in the images can be determined according to the perspective principle, the constraint condition of the rectangle as well as the front shot constraint condition of the target, by using this relationship, the runway approaching marks can be separated, the position and the direction of the runway in the images can be identified. In this paper, the clustering management is adopted so as to greatly reduce the computing time. The consequence of the experiments shows that by this algorithm, even from a place far away from the runway whose marks are unclear, we also can effectively detect the runway.

关键词： Unmanned vehicles

来源：评论

学校读者我要写书评

暂无评论

基于目标区域特性的海面小目标检测快速算法

引用

自动化学报 2005年第3期31卷 427-433页

作者：邹玉兰汪国有张磊 Institute for Pattern Recognition and Artificial Intelligence State Education Commission Key Laboratory for Image Processing and Intelligent Control Huazhong University of Science & Technology Wuhan 430074

A fast object detection method based on object region dissimilarity and 1-D AGADM(one dimensional average gray absolute difference maximum) between object and background isproposed for real-time defection of small offshore targets. Then computational complexity, antinoiseperformance, the signal-to-noise ratio (SNR) gain between original images and their results as afunction of SNR of original images and receiver operating characteristic (ROC) curve are analyzed andcompared with those existing methods of small target detection such as two dimensional average grayabsolute difference maximum (2-D AGADM), median contrast filter algorithm and multi-level filteralgorithm. Experimental results and theoretical analysis have shown that the proposed method hasfaster speed and more adaptability to small object shape and also yields improved SNR performance.

关键词：小目标检测快速算法区域特性海面

来源：评论

学校读者我要写书评

暂无评论

Background suppression based-on wavelet transformation to detect infrared target

Background suppression based-on wavelet transformation to de...

引用

International Conference on Machine Learning and Cybernetics, ICMLC 2005

作者： Sun, Y.U.-Qiu Tian, Jin-Wen Liu, Jian School of Information and Mathematics Yangtze University Jingzhou 434023 China State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China State Education Commission Key Laboratory for Image Processing and Intelligent Control Dept. of Electronic Information and Enginery Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)078039092X

Target detection and location in infrared clutter background is very important to infrared search and track system. Especially for small target detection in infrared image in background of sea and sky, there are no geometric and structure character to use. When targets such as ship and naval vessel sailing at long distance, they always appear around the sea-level line, and it is mixed with cloud and sea-wave clutter. It is difficult to segment and locate precisely. Background suppression based-on wavelet transformation is proposed in the paper. Wavelet decomposition makes it possible to analyze a signal both in time and frequency domains. In the paper infrared sea and key background images are processed. For their SNR is low and background is complex, using wavelet transformation decomposes an original image and extract approximate feature to reconstruct an image, which mainly includes background information. A new image will be obtained using background image subtracted from original image. There are mainly target and noise points left in the new image. By setting proper threshold, the target can be detected perfectly. At last, experiment results are given and show the method is practical. © 2005 IEEE.

关键词： Pattern recognition

来源：评论

学校读者我要写书评

暂无评论

A new method for ship classification and recognition

A new method for ship classification and recognition

引用

MIPPR 2005: image Analysis Techniques

作者： Zhao, Guangzhou Wang, Fei Zhang, Tianxu Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China State Key Laboratory for Image Processing and Intelligent Control Wuhan 430074 China

This paper proposes a fast and robust algorithm for classification and recognition of ships based on the Principal Component Analysis (PCA) method. The three-dimensional ship models are achieved by modeling software of MultiGen, and then they are projected by Vega simulating software for two-dimensional ship silhouettes. The PCA method as against the Back-Propagation (BP) neural network method for simulated ship recognition using training and testing experiments, we can see that there is a sharp contrast between them. Some recognition results from simulated data are presented, the correct recognition rate of PCA method improved rapidly for each of the five ship types than that of neural network method, the number of times a ship type is recognized as one of the other ships is reduced greatly.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

Contrast-modulated nonlinear diffusion for X-ray angiogram images

Contrast-modulated nonlinear diffusion for X-ray angiogram i...

引用

2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005

作者： Li, Baopu Sang, Nong Cao, Zhiguo Department of Electronic Engineering Chinese University of Hong Kong Shatin N.T. Hong Kong Key Laboratory Ministry of Education for Image Processing and Intelligent Control Wuhan China

ISBN: (纸本)0780387406

In this paper, we present a new method for X-ray angiogram images enhancement using a contrast-modulated nonlinear diffusion. The original nonlinear diffusion is gradient driven, which leads into much dependence on the accurate estimation of the edge. However, it is very difficult to get the accurate estimation of edges for X-ray angiogram images, which are characterized with complex background. So it is necessary to do some improvements to this model. By designing a new concept of contrast space according to the characteristics of these images, we change the original nonlinear diffusion into contrast-modulated nonlinear diffusion. Compared with the traditional method, this new approach is proved to have a better performance of enhancement. © 2005 IEEE.

关键词： Medical imaging

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：