检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

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

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

164 篇 会议
1 篇 期刊文献

馆藏范围

165 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

155 篇 理学
- 143 篇 物理学
- 28 篇 数学
- 6 篇 统计学（可授理学、...
- 2 篇 生物学
- 1 篇 化学
- 1 篇 大气科学
- 1 篇 海洋科学
154 篇 工学
- 98 篇 测绘科学与技术
- 33 篇 计算机科学与技术...
- 29 篇 软件工程
- 25 篇 信息与通信工程
- 23 篇 光学工程
- 14 篇 电气工程
- 6 篇 控制科学与工程
- 5 篇 电子科学与技术（可...
- 4 篇 机械工程
- 3 篇 仪器科学与技术
- 2 篇 化学工程与技术
- 2 篇 生物工程
- 1 篇 动力工程及工程热...
- 1 篇 交通运输工程
- 1 篇 航空宇航科学与技...
- 1 篇 农业工程
- 1 篇 生物医学工程（可授...
118 篇 医学
- 118 篇 临床医学
3 篇 管理学
- 3 篇 图书情报与档案管...
1 篇 农学
- 1 篇 作物学

主题

23 篇 image segmentati...
9 篇 target tracking
6 篇 image processing
6 篇 target detection
5 篇 image fusion
5 篇 image matching
4 篇 wavelet
4 篇 image denoising
4 篇 image analysis
4 篇 image recognitio...
4 篇 image registrati...
3 篇 level set
3 篇 edge detection
3 篇 feature extracti...
3 篇 isar imaging
2 篇 image enhancemen...
2 篇 wavelet transfor...
2 篇 fuzzy logic
2 篇 template
2 篇 image acquisitio...

机构

6 篇 xidian univ inst...
4 篇 huazhong univ sc...
4 篇 wuhan univ sch r...
3 篇 school of automa...
3 篇 graduate school ...
3 篇 natl univ def te...
3 篇 chinese acad sci...
2 篇 wuhan univ sch r...
2 篇 tsinghua univ de...
2 篇 chinese acad sci...
2 篇 beihang univ sch...
2 篇 huazhong univ sc...
2 篇 chinese acad sci...
2 篇 xidian univ inst...
2 篇 shenyang institu...
2 篇 univ sci & techn...
2 篇 wuhan inst techn...
2 篇 wuhan univ natl ...
2 篇 state key labora...
2 篇 chinese acad sci...

作者

10 篇 jiao licheng
8 篇 zhang tianxu
4 篇 liu yang
4 篇 shi zelin
4 篇 tian biao
3 篇 chen zengping
3 篇 wang shuang
3 篇 yan luxin
3 篇 tian jinwen
3 篇 li gang
3 篇 peng fuyuan
2 篇 liu zhifang
2 篇 zhou xiaodong
2 篇 cai chao
2 篇 hong hanyu
2 篇 hu maolin
2 篇 ding mingyue
2 篇 li yun
2 篇 wang cheng
2 篇 li haigang

语言

164 篇 英文
1 篇 中文

检索条件"任意字段=MIPPR 2007: Automatic Target Recognition and Image Analysis;and Multispectral Image Acquisition"

共 165 条记录，以下是121-130 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Research on classification of high-resolution remote sensing image

Research on classification of high-resolution remote sensing...

引用

mippr 2007: automatic target recognition and image analysis;and multispectral image acquisition

作者： Zhang, Xiwang Wu, Bingfang Li, Qiangzi Institute of Remote Sensing Applications Chinese Academy of Sciences Beijing 100101 China

ISBN: (纸本)9780819469502

High-resolution remote sensing image is usually considered that its pixel size is less than 10 meters. Traditional classification methods based on pixels are not fit for the classification of this kind of image because this kind of image has higher spatial resolution and more local heterogeneity compared to the low-resolution remote sensing image data. Object-oriented image classification method provides a good technique to solve this problem. This method segments image to create homogeneous regions or image objects through region merging or boundary detection algorithms. Objects possess more features such as geometric and structure characteristics besides spectral characteristics than pixels. So it is important to select appropriate characterstics in classification. Class-Related features, landscape pattern metrics, geometric attributes of objects, spatial information are very useful characteristics. The paper will pay more attention to the selection and integrative utilization of these features and spectral characteristics, and give several examples to show their performance. (1) If We want to extract a kind of feature which has similar spectral characteristic as the other feature but has a certain positional relationship with a specific feature, at this time, Class-Related features will be very efficacious. (2) Both river and pounds have also similar spectral characteristic, but has different geometric characteristic in the landscape pattern metrics. Synthetically use of the landscape pattern metrics and spectral characteristic will wok well. (3) In the same segmentation scale, the objects from the region with more homogeneity will be bigger than other objects from the region with more heterogeneity. So, the area and spectral characteristic can be used in classification. The results show a better accuracy. The selection and integrative utilization of features of objects were very important in achieving these high accuracies.

关键词： image segmentation

来源：评论

学校读者我要写书评

暂无评论

High-accurate line feature extraction algorithm based on line diffusion function model

High-accurate line feature extraction algorithm based on lin...

引用

5th International Symposium on multispectral image Processing and Pattern recognition

作者： Zheng, Shunyi Li, Cailin Su, Guozhong Zhang, Jianqing Wuhan Univ Sch Romote Sensing & Informat Engn Wuhan 430079 Peoples R China Chinese Acad Sci Acad Opto Elect Beijing 100080 Peoples R China

ISBN: (纸本)9780819469502

A high-accurate line feature extraction algorithm based on line diffusion function model has been proposed in this paper, using local gray value variations to precisely identify edge locations. This paper firstly analyzed the primary principle of line diffusion function model, then showed that how to use the information of image window to determine the exact position of line features in images. During the process, the mathematical model is provided and high-accurate line feature extraction algorithm has been developed. Finally, this algorithm has been used to extract line features from aerial images of urban area and experimental results are presented to demonstrate the efficiency and accuracy of the proposed algorithm.

关键词： line feature extraction line diffusion function model high-accurate algorithm least square image patch bilinear interpolation

来源：评论

学校读者我要写书评

暂无评论

Improved thresholding method based on Tsallis-Havrda-Charvat entropy

Improved thresholding method based on Tsallis-Havrda-Charvat...

引用

5th International Symposium on multispectral image Processing and Pattern recognition

作者： Chen, Jingjing Wu, Jin Chen, Min Wang, Ruixin Wuhan Univ Sci & Technol Coll Informat Sci & Engn Wuhan 430081 Peoples R China

ISBN: (纸本)9780819469502

This paper presents a thresholding method for image segmentation by using an improved thresholding output function on a two-dimensional (2-D) histogram based on Tsallis-Havrda-Charvat entropy principle. The Tsallis-Havrda-Charvat entropy is obtained from two-dimensional histogram which has determined by using the gray value of the pixels and the local average gray value of the pixels. Based on Tsallis-Havrda-Charvat entropy, we obtain the optimal threshold pair by maximizing the criterion function. The threshold pair groups the projection drawing of the 2-D histogram into four quadrants. Then we draw a line passing the optimal point. According to the line, we use the improved thresholding output function to separate the four quadrants into two parts, above the line and below the line. Therefore, the pixels are also grouped into two groups, targets and background. Experiment results show that the proposed method is robust to noise.

关键词： image segmentation thresholding two-dimensional histogram Tsallis-Havrda-Charvat entropy robust

来源：评论

学校读者我要写书评

暂无评论

New method for text detection and segmentation from complex images

New method for text detection and segmentation from complex ...

引用

5th International Symposium on multispectral image Processing and Pattern recognition

作者： Liu, Fang Peng, Xiang Wang, Tianjiang Huazhong Univ Sci & Technol Sch Comp Sci & Technol Intelligent & Distributed Comp Lab Wuhan 430074 Peoples R China

ISBN: (纸本)9780819469502

Textual information contained in images is a valuable source of high-level semantics for image indexing and retrieval. This paper proposes a new method to detect and segment text from complex images. First, a density-based clustering method is employed to discover the candidate text regions. The clustering method is from data mining area. It computes the density distribution of overall image and makes spatial connective pixels with similar color/grayscale into one region. The clustered regions are deemed as candidate text regions. Then simple heuristics are applied to delete those obvious non-text regions from the candidate. But there still exits a few non-text regions in the candidate. Therefore a texture-based method is used to select text regions from the filtered candidate text regions. Considering the time complexity of density computation in clustering step, an approximate algorithm is designed to improve the efficiency. Experimental result shows the method is robust to variations in text font, orientation, language, and size.

关键词： text detection imaging indexing Gaussian density distribution texture analysis

来源：评论

学校读者我要写书评

暂无评论

Novel motion object extraction algorithm

Novel motion object extraction algorithm

引用

5th International Symposium on multispectral image Processing and Pattern recognition

作者： Xiao, Yi-Jun Wang, Bang-Pin Lu, Xiao-Chun Jiang, Xin-Rong Sichuan Univ Graph & Image Res Lab Sch Comp Sci Chengdu Peoples R China

ISBN: (纸本)9780819469502

In intelligent transport system, it is very important to precisely segment motion object from complex scene. Background difference and frame difference are two classic motion object extraction algorithms. If there are shadows associated to moving objects, both of the methods cannot extract moving object precisely. With this problem, this paper proposes a motion object extraction algorithm based on active contour model (ACMMOE). The following steps are performed in ACMMOE: firstly, moving areas involving shadows are segmented with classical background difference algorithm. Secondly, perform shadow detection and coarsely removal, then using grid method to extract initial contours. Finally, use active contour model approach to the contour of the real object by iteratively tuning the parameter of the model. The proposed algorithm adopts greedy algorithm to speed up the solution to active contour model. Experiments show the algorithm can remove the shadow and keep the integrity of moving object.

关键词： active contour model shadow detection dilate erode

来源：评论

学校读者我要写书评

暂无评论

Coherent ISAR imaging based on phase matching processing of complex range profile for procession space target 11

Coherent ISAR imaging based on phase matching processing of ...

引用

11th International Symposium on multispectral image Processing and Pattern recognition (mippr) - multispectral image acquisition, Processing, and analysis (mippr)

作者： Kang, Hongyan Tian, Biao Liu, Yongxiang Natl Univ Def Technol Tech Serv Ctr Vocat Educ Changsha Peoples R China Natl Univ Def Technol Coll Elect Sci & Technol Changsha Peoples R China

ISBN: (纸本)9781510636347

In order to improve the inverse synthetic aperture radar (ISAR) imaging quality of precession space target, an algorithm based on phase matching processing (PMP) of complex range profile envelope (CRPE) is proposed in this paper. By phase matching processing, only the echo components located at the scattering points corresponding to the main body of the warhead can be coherently accumulated. The echoes of other scattering centers without any coherence will cancel each other when they are transformed. Hence, the focusing of scatters centers of the warhead main body is improved and the interference caused by non-spin symmetric components is well suppressed. Simulation results confirmed the effectiveness of the method.

关键词： inverse synthetic aperture radar precession space target phase matching processing complex range profile envelope

来源：评论

学校读者我要写书评

暂无评论

Local level set segmentation method combined with narrow band

Local level set segmentation method combined with narrow ban...

引用

5th International Symposium on multispectral image Processing and Pattern recognition

作者： Li, Yushi Zhou, Jun Li, Junlong Liu, Chunsheng Northwest Polytech Univ Sch Astronaut Beijing Peoples R China China Aerosp Sci & Ind Corp Beijing Peoples R China

ISBN: (纸本)9780819469502

The paper deduces a general form of energy function from the level set method based on Mumford-Shah model. It introduces the gradient of image features into the energy function, which could make the segmentation more precise and the algorithm converge faster. In order to detect local object in the image with clutter background, a local level set segmentation method using the proposed energy function is presented in this paper. The method combined with narrow band could obtain local optimal segmentation, which just needs prior location of the object. To tackle the problem that the calculation cost of level set is so expensive, the paper proposes an efficient algorithm for narrow band which implements very fast. The algorithm starts with a simple initial curve, and then it only updates the level set function in the narrow band. The local level set method is applied successfully to image segmentation with cluttered background, multi-object detection and moving object detection. The results of the experiments are presented in the end of paper.

关键词： level set narrow band image segmentation contour extraction

来源：评论

学校读者我要写书评

暂无评论

Stochastic approach based salient moving object detection using kernel density estimation

Stochastic approach based salient moving object detection us...

引用

5th International Symposium on multispectral image Processing and Pattern recognition

作者： Tang, Peng Liu, Zhifang Gao, Lin Sheng, Peng Sichuan Univ Inst Image & Graph Dept Comp Sci Chengdu 610065 Peoples R China

ISBN: (纸本)9780819469502

Background modeling techniques are important for object detection and tracking in video surveillances. Traditional background subtraction approaches are suffered from problems, such as persistent dynamic backgrounds, quick illumination changes, occlusions, noise etc. In this paper, we address the problem of detection and localization of moving objects in a video stream without apperception of background statistics. Three major contributions are presented. First, introducing the sequential Monte Carlo sampling techniques greatly reduce the computation complexity while compromise the expected accuracy. Second, the robust salient motion is considered when resampling the feature points by removing those who do not move in a relative constant velocity and emphasis those in consistent motion. Finally, the proposed joint feature model enforced spatial consistency. Promising results demonstrate the potentials of the proposed algorithm.

关键词： video surveillance moving object detection kernel density estimation Monte Carlo simulation

来源：评论

学校读者我要写书评

暂无评论

Single level set based fast images segmentation model with multiple regions

Single level set based fast images segmentation model with m...

引用

5th International Symposium on multispectral image Processing and Pattern recognition

作者： Zhang, Honghui Tan, Yong Li, Shanshan Univ Sci & Technol China Dept Elect Engn & Informat Sci Hefei 230027 Peoples R China

ISBN: (纸本)9780819469502

In traditional image segmentation models based on single level set function, only two regions can be identified because different regions are identified by the signs of single level set function. Though several segmentation models with multiple regions have been proposed, but the largest number of regions that can be identified was limited by the number of embedded level set functions in them. Moreover, the more embedded level set functions, the higher the time cost, usually increasing linearly with the increase of embedded level set functions. In this paper, by introducing the segmentation-measure function, a new model for multi-regions image segmentation based on single level set function is proposed. At the same time, a new initialization function for the level set function is also proposed in order to reduce the time cost of the segmentation model. The experiment results show that the new image segmentation mode with multiple regions proposed in this paper performs well and dramatically reduces the time cost compared with the popular model for multiple regions proposed by Vese and Chan.

关键词： level set image segmentation curve evolution energy minimization

来源：评论

学校读者我要写书评

暂无评论

Novel color image segmentation using self-generating prototypes

Novel color image segmentation using self-generating prototy...

引用

5th International Symposium on multispectral image Processing and Pattern recognition

作者： Liu, Chunping Yuan, Xiaohua Wang, Zhaohui Cui, Zhiming Suzhou Univ Sch Comp Sci & Technol Suzhou 215006 Jiangsu Peoples R China Shanghai Fisheries Univ Coll Informat Shanghai 200090 Peoples R China

ISBN: (纸本)9780819469502

A new self-generating prototypes method based on SGNT is presented. This method uses reference patterns as initial prototype. This procedure can be implemented in a SGNT with specific architecture consisting of one root and the initial class number of reference patterns. The leaf in SGNT is defined with prototype vector, learning vector, center property vector and distant property vector. After training, prototype set are outputted. The main advantage of this method is that both the number of prototypes and their locations are learned from the training set without much human intervention. Experiments with synthesis and real color image the excellent performance of this classification scheme as compared to existing K-nearest neighbor (K-NN) and Learning vector quantization (LVQ) algorithm.

关键词： competitive learning color image segmentation K-nearest neighbor algorithm Learning vector quantization hierarchical clustering self-generating prototype

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共17页 << < 8 9 10 11 12 13 14 15 16 17 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

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：