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

54 篇 会议
9 篇 期刊文献

馆藏范围

63 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

42 篇 工学
- 25 篇 计算机科学与技术...
- 21 篇 软件工程
- 9 篇 信息与通信工程
- 8 篇 机械工程
- 8 篇 生物医学工程（可授...
- 7 篇 电气工程
- 7 篇 生物工程
- 6 篇 光学工程
- 5 篇 控制科学与工程
- 4 篇 电子科学与技术（可...
- 2 篇 仪器科学与技术
- 2 篇 化学工程与技术
- 1 篇 力学（可授工学、理...
- 1 篇 建筑学
- 1 篇 交通运输工程
- 1 篇 核科学与技术
20 篇 理学
- 8 篇 数学
- 8 篇 物理学
- 7 篇 生物学
- 2 篇 化学
- 2 篇 统计学（可授理学、...
- 1 篇 系统科学
11 篇 管理学
- 6 篇 管理科学与工程(可...
- 6 篇 图书情报与档案管...
4 篇 医学
- 3 篇 基础医学(可授医学...
- 3 篇 临床医学
- 3 篇 药学(可授医学、理...
- 1 篇 公共卫生与预防医...
2 篇 农学
- 2 篇 作物学
1 篇 法学
- 1 篇 社会学

主题

8 篇 pattern recognit...
8 篇 computer vision
7 篇 image segmentati...
6 篇 image processing
5 篇 computer graphic...
5 篇 feature extracti...
5 篇 shape
4 篇 support vector m...
4 篇 image edge detec...
4 篇 lighting
4 篇 biomedical imagi...
4 篇 image recognitio...
3 篇 image
3 篇 mobile robots
3 篇 algorithm design...
3 篇 histograms
2 篇 image enhancemen...
2 篇 object detection
2 篇 pixel
2 篇 image texture an...

机构

13 篇 institute of ima...
6 篇 college of math ...
6 篇 institute for co...
5 篇 pattern recognit...
4 篇 pattern recognit...
4 篇 institute for co...
4 篇 institute of ima...
2 篇 pattern recognit...
2 篇 centre for image...
2 篇 institute of ima...
2 篇 computer vision ...
2 篇 department of in...
2 篇 college of mecha...
2 篇 institute of aut...
2 篇 computer vision ...
2 篇 school of inform...
1 篇 computer science...
1 篇 and the ieee com...
1 篇 key laboratory o...
1 篇 pattern recognit...

作者

7 篇 bischof horst
6 篇 h. bischof
6 篇 luya wang
6 篇 weixing wang
4 篇 g. langs
4 篇 langs georg
3 篇 li xi
3 篇 liu xiangbin
3 篇 xi li
3 篇 jiang shao-hua
3 篇 xiangbin liu
2 篇 m. reiter
2 篇 chanda sukalpa
2 篇 jogan matjaž
2 篇 timofte radu
2 篇 yang hui-jun
2 篇 abhinav dhall
2 篇 wildenauer horst
2 篇 doermann david
2 篇 he dong-jian

语言

62 篇 英文
1 篇 其他

检索条件"机构=Institute of Image Recognition and Computer Vision"

共 63 条记录，以下是21-30 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：

Iterative data adaptive anisotropic image filtering

Iterative data adaptive anisotropic image filtering

引用

2012 International Conference on Machine Learning and Cybernetics, ICMLC 2012

作者： Yang, Chang-Cai Zheng, Xin-Yi Tian, Jin-Wen Shang, Ke Tian, Xin Hao, Wei Institute for Pattern Recognition and Artificial Intelligence Science and Technology on Multi-Spectral Information Processing Laboratory Huazhong University of Science and Technology Wuhan 430074 China Electrical Engineering and Renewable Energy School China Three Gorges University Yichang 443002 China Institute of Intelligent Vision and Image Information College of Computer and Information Technology China Three Gorges University Yichang 443002 China

ISBN: (纸本)9781467314855

This paper presents a novel data-adaptive anisotropic filtering technique built on top of an iterative scheme. This new technique can preserve the original significant structures while suppressing noises to the largest extent. To achieve this goal, dominant orientation information of all gradients is used to control the local kernel adaptively. This results in elongated and elliptical contours spread along the directions of the local edge structure. With these locally adapted kernels, the smoothing is mostly effective along the edges, rather than across them. Therefore details in the original input can be preserved. The performance of the proposed data-adaptive anisotropic filter together with its iterative scheme are compared with the conventional Gaussian filter, anisotropic diffusion filter, the structure-adaptive anisotropic filter, and the iterative kernel regression scheme. The experimental results on both simulated Gaussian and Poission noisy images indicate that the proposed method performs the best, and the iterative scheme can significantly improve the performance of the noise suppressing while delivering high computation efficiency. © 2012 IEEE.

关键词： Iterative methods

来源：评论

学校读者我要写书评

暂无评论

A point feature-based cylindrical image mosaic method

A point feature-based cylindrical image mosaic method

引用

2nd International Conference on Multimedia Technology, ICMT 2011

作者： Li, Xi Gong, Ping College of Math and Computer Science Hunan Normal University Changsha China Institute of Image Recognition and Computer Vision Hunan Normal University Changsha China

ISBN: (纸本)9781612847740

A cylindrical image mosaic method based on Harris corner feature is proposed in the paper. Firstly, the sequence of photographs taken around 360 degree is projected to cylinder coordinate system, and then the Harris corners are detected by an improved Harris corner detecting algorithm. After the NCC (Normalized Cross Correlation) corner matching algorithm performed a rough match, an improved RANSAC (Random Sample Consensus) algorithm is applied twice to remove the mismatched points as far as possible to improve the correct matching ratio. Finally, the image mosaic and fusion are accomplished according to the registration result. Experiments demonstrate that the proposed algorithm has achieved a well result. © 2011 IEEE.

关键词： image enhancement

来源：评论

学校读者我要写书评

暂无评论

A separating algorithm for particle image

A separating algorithm for particle image

引用

2nd International Conference on Multimedia Technology, ICMT 2011

作者： Liu, Xiangbin Li, Xi Institute of Image Recognition and Computer Vision Hunan Normal University Central South University Changsha China College of Math and Computer Science Hunan Normal University Changsha China

ISBN: (纸本)9781612847740

In the particle images, objects tend to touch, overlap with each other to form clusters. How to separate these clusters into single objects is a vital problem for the counting, feature extraction and analysis in the following process. Separating them by boundary tracking do not need an acute angle and/or the strong density contrast at the points where the objects touched, so it can get a better separating result. But sometimes when the principal axis direction of the cluster is neither horizontal nor vertical, it does not work. For this, a new separating algorithm is presented in the paper. At first, the algorithm calculates the principal axis direction of the cluster, if it is nearly horizontal or vertical then goes on, otherwise it rotates the cluster to make its principal axis direction be horizontal. And then the algorithm performs separating by boundary tracking. Experiments show that the algorithm has achieved a well separating result. © 2011 IEEE.

关键词： Clustering algorithms

来源：评论

学校读者我要写书评

暂无评论

A point feature-based cylindrical image mosaic method

A point feature-based cylindrical image mosaic method

引用

International Conference on Multimedia Technology

作者： Xi Li Ping Gong College of Math and Computer Science Hunan Normal University Changsha China Institute of Image Recognition & Computer Vision Hunan Normal University Changsha China

ISBN: (纸本)9781612847719

关键词： image registration Feature extraction Transforms image edge detection Correlation Nickel Least squares methods

来源：评论

学校读者我要写书评

暂无评论

A separating algorithm for particle image

A separating algorithm for particle image

引用

International Conference on Multimedia Technology

作者： Xiangbin Liu Xi Li Institute of Image Recognition & Computer Vision Hunan Normal University Changsha China School of Information Science and Engineering Central South University Changsha China College of Math and Computer Science Hunan Normal University Changsha China

ISBN: (纸本)9781612847719

关键词： Clustering algorithms Algorithm design and analysis image segmentation Heuristic algorithms Feature extraction Transforms Arrays

来源：评论

学校读者我要写书评

暂无评论

A skeleton extracting algorithm for dorsal hand vein pattern

A skeleton extracting algorithm for dorsal hand vein pattern

引用

2010 International Conference on computer Application and System Modeling, ICCASM 2010

作者： Yang, Lin Liu, Xiangbin Liu, Zhicheng Institute of Image Recognition and Computer Vision Hunan Normal University Changsha China

ISBN: (纸本)9781424472369

Extracting vein skeleton with little distortion from the vein image is very important for improving the identification rate. In the paper, an algorithm for segmenting the dorsal hand vein image and extracting the vein skeleton is presented. Firstly, after gray and size normalizing, Gaussian lowpass filter and median filter are used to eliminate the speck noise and the horizontal strip scanning noise respectively. Then, an improved NiBlack algorithm segments the vein pattern and an area thresholding algorithm removes the noise blocks from the vein pattern. Subsequently, opening, closing and median filter are used to smooth the vein boundary. After that, the vein pattern is thinned by Kejun Wang's improved conditional thinning. Lastly, a pruning algorithm is presented to trim the spurs and the vein pattern is skeletonized. Experiment shows the algorithm acquires more real skeleton. © 2010 IEEE.

关键词： Median filters

来源：评论

学校读者我要写书评

暂无评论

A dorsal hand vein pattern recognition algorithm

A dorsal hand vein pattern recognition algorithm

引用

2010 3rd International Congress on image and Signal Processing, CISP 2010

作者： Li, Xi Liu, Xiangbin Liu, Zhicheng College of Math and Computer Science Hunan Normal University Changsha China Institute of Image Recognition and Computer Vision Hunan Normal University School of Information Science and Engineering Changsha China Institute of Image Recognition and Computer Vision Hunan Normal University Changsha China

ISBN: (纸本)9781424465149

An algorithm for dorsal hand vein pattern recognition is presented in the paper. To improve the recognition ratio, the vein skeleton extracting with little distortion is very important. Firstly, the algorithm acquires a clean, one-pixel-width skeleton with little distortion after a series of processes: size and gray normalizing, Gaussian lowpass and median filtering, NiBlack local dynamic thresholding segmenting, area thresholding, morphological opening and closing, median filtering, conditional thinning, spurs pruning. Then, the seven corrected moment invariants of the vein skeleton are extracted as the feature vector. At last, the feature vector is input into SVM for training and recognition. Experiment shows the algorithm achieves a higher recognition ratio of 95.5%. ©2010 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Mathematical modeling for corner saliency

Mathematical modeling for corner saliency

引用

International Conference on Software Technology and Engineering

作者： Jiang, Shao-Hua Xu, Xue-Jun Zhu, Hong-Bo Chen, Xue-Song Digital Engineering and Simulation Research Center Huazhong University of Science and Technology Wuhan 430074 China Institute of Image Recognition and Computer Vision Hunan Normal University Changsha 410081 China

ISBN: (纸本)9781424486656

This paper proposed the definition of corner saliency firstly, which is an intrinsic characteristic of a corner and denote the contributiveness of a corner on the result of image processing. Then, we discussed the relation among the corner saliency, the out-in degree, the angle sequence and the ratio of line-length sequence in detail, and formulate a mathematic model to calculate the corner saliency. Finally, we introduced an experiment to illustrate the calculation of corner saliency. It shows that the proposed model is effective and has practical application value also. © 2010 IEEE.

关键词： image processing

来源：评论

学校读者我要写书评

暂无评论

A Skeleton Extracting Algorithm for Dorsal Hand Vein Pattern

A Skeleton Extracting Algorithm for Dorsal Hand Vein Pattern

引用

The 2010 International Conference on computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

作者： Lin Yang Xiangbin Liu Zhicheng Liu Institute of Image Recognition & Computer Vision Hunan Normal University Changsha China

ISBN: (纸本)9781424472352

Extracting vein skeleton with little distortion from the vein image is very important for improving the identification rate. In the paper, an algorithm for segmenting the dorsal hand vein image and extracting the vein skeleton is presented. Firstly, after gray and size normalizing, Gaussian low pass filter and median filter are used to eliminate the speck noise and the horizontal strip scanning noise respectively. Then, an improved NiBlack algorithm segments the vein pattern and an area thresholding algorithm removes the noise blocks from the vein pattern. Subsequently, opening, closing and median filter are used to smooth the vein boundary. After that, the vein pattern is thinned by Kejun Wang's improved conditional thinning. Lastly, a pruning algorithm is presented to trim the spurs and the vein pattern is skeletonized. Experiment shows the algorithm acquires more real skeleton.

关键词： vein pattern recognition segmentation smoothing skeletonizing

来源：评论

学校读者我要写书评

暂无评论

A dorsal hand vein pattern recognition algorithm

A dorsal hand vein pattern recognition algorithm

引用

Congress on image and Signal Processing, CISP

作者： Xi Li Xiangbin Liu Zhicheng Liu College of Math and Computer Science Hunan Normal University Changsha China Institute of Image Recognition & Computer Vision Hunan Normal University China School of Information Science and Engineering Central South University Changsha China Institute of Image Recognition & Computer Vision Hunan Normal University Changsha China

关键词： Veins Feature extraction Skeleton Pattern recognition Pixel image segmentation Support vector machines

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7页 << < 1 2 3 4 5 6 7 > >>

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：