检索结果-内蒙古大学图书馆

3rd international symposium on multispectral image processing and pattern recognition

作者： Wang, JJ Liu, WY Cai, HY Ming, L Li, R Tianjin Univ Coll Precise Instrument & Opt Elect Engn Tianjin 300072 Peoples R China

ISBN: (纸本)0819451819

With the development of modem science and technology, MEMS becomes an important branch. The micro operating system becomes an interested spot. During the micromanipulation process, observing the micro components by optical microscope is a crucial technology. Limited by the optical parameters, focus of the optical microscope is small. For example, focus of 10(x) object lens is about 10 micron. The observation of some bigger micro objects, which size is tens or hundreds times of 10 micron, are certainly impossible by one time imaging. Some researchers had tried to extend the focus by improving the structure of microscopy, but the results are not satisfying. The optical microscope has CCD sensor as detector. Moving the object carrier, series adjusted focus images can be given. As the distance between CCD sensor and object lens is fixed, these images are with the same amplification ratio. We can use computer to analysis these images for extending the focus. Through series images to extend focus, core of this method is analyzing and processing these series images, and at last composing one image, which is clear at each vertical depth. On this image, the position of each micro object can be measured easily. Sub-pixel processing technique makes the measure precision achieve micron degree. The distance, which is recorded while adjusting the object carrier, can help to locate the vertical position of micro object, experiments show that the locating precision could up to micron degree also. Using this method avoids changing optical system hardware, and is easy achieved. Clear image can be got in the adjustable range of object carrier. The range of focus is extended. The precision can be up to micron degree on 3D direction. So the method is useful on observing and measuring of micro object, has theoretical and practical value.

关键词： extending focus optical microscopy image processing MEMS

来源：评论

学校读者我要写书评

暂无评论

The classification of MODIS images based on band combination

The classification of MODIS images based on band combination

引用

third international symposium on multispectral image processing and pattern recognition

作者： Li, Yan Zhai, Ruifang Wang, Ying School of Geodesy and Geomatics Wuhan University 129 Luoyu Road Wuhan 430079 China Sch. of Remote Sensing/Info. Eng. Wuhan University 129 Luoyu Road Wuhan 430079 China

This paper discusses the existing three optimal band combination rules of hyperspectral remote sensing images. They are joint entropy, optimal index factor and Sheffield index respectively. Three bands of MODIS images data are combined arbitrarily according to the three rules, so the best three bands combination images of the three rules are acquired. On the basis of this, the three images are all classified in term of maximum likelihood classifier. Also, the influence of each band combination to the classification performance is discussed. The experiment result proves that the best classification performance of the MODIS images based on the three bands combination is the combination image based on optimal index factor.

关键词： image analysis

来源：评论

学校读者我要写书评

暂无评论

A family of triangular grids in digital geometry

A family of triangular grids in digital geometry

引用

international symposium on image and Signal processing and Analysis

作者： B. Nagy University of Debrecen Hungary

In this paper we show a new geometric interpretation of the hexagonal and triangular grids. They can be considered as the sets of points of one (see (I. Her, 1995)), respectively two plane(s) in Z/sup 3/. By this approach we can build up a whole family of triangular grids (the so called n-planes triangular grids). The hexagonal and triangular grids are the first two members of this family, moreover, they are duals of each other. We investigate the three-planes grid, the third member of the family, and its dual in detail. We show that for n /spl ges/ 4 on, the n-planes triangular grids are non-planar.

关键词： Geometry Digital images pattern recognition Signal processing image analysis Signal analysis

来源：评论

学校读者我要写书评

暂无评论

PURSUIT: an automatic classification tool for remote sensing data

PURSUIT: an automatic classification tool for remote sensing...

引用

IEEE international symposium on Geoscience and Remote Sensing (IGARSS)

作者： T.M. Bachmann M.H. Bettenhausen Remote Sensing Division Code 7212 Naval Research Laboratory Inc. Washington D.C. DC USA IMSI Inc. Arlington VA USA

PURSUIT (Projection Understanding and recognition from a SUite of intelligent Tools) has been under development at the Naval Research Laboratory for a number of years. It is a versatile software tool designed to address the problem of automatic feature extraction and classification from remote sensing data. Although the tool can be applied to a variety of applications outside of the field of remote sensing, it is particularly useful for automated remote sensing imagery analysis. To date, the package has been applied to imagery from a variety of different sensor types including: multispectral, hyperspectral, synthetic aperture radar (SAR), and multi-sensor data. Because of its modular design, PURSUIT is re-configurable and the suite of algorithms that comprise it can be flexibly combined to address new applications as they arise. As such, new algorithms can be easily added. Algorithms included in the present corpus consist of a variety of in-house algorithms, as well as standard algorithms derived from many areas of the statistical pattern recognition literature, including adaptive vector quantization, unsupervised and supervised feature extraction and classification, and neural networks. Each module contains a number of different preprocessing and post-processing options, and the input data may be spectral, spatial, or spatial-spectral. The modular design of the package allows data from multiple sources to be combined in the same overall automatic classification model.

关键词： Remote sensing Feature extraction Packaging Hyperspectral sensors Laboratories Software tools Software design Application software image analysis image sensors

来源：评论

学校读者我要写书评

暂无评论

multispectral image processing: The nature factor

引用

international JOURNAL OF pattern recognition AND ARTIFICIAL INTELLIGENCE 2000年第7期14卷 895-906页

作者： Watkins, WR USA Res Lab AMSRL SL EA White Sands Missile Rang NM 88002 USA

The images processed by our brain represent our window into the world. For some animals this window is derived from a single eye, for others, including humans, two eyes provide stereo imagery, for others like the black widow spider several eyes are used (8 eyes), and some insects like the common housefly utilize thousands of eyes (ommatidia). Still other animals like the bat and dolphin have eyes for regular vision, but employ acoustic sonar vision for seeing when their regular eyes do not work such as in pitch black caves or turbid water. Of course, other animals have adapted to dark environments by bringing along their own lighting such as the firefly and several creatures from the depths of the ocean floor. Animal vision is truly varied and has developed over millennia in many remarkable ways. We have learned a lot about vision processes by studying these animal systems and can still learn even more.

关键词： image processing human vision depth perception wide baseline stereo target acquisition navigation optical turbulence

来源：评论

学校读者我要写书评

暂无评论

On geometric and orthogonal moments

引用

international JOURNAL OF pattern recognition AND ARTIFICIAL INTELLIGENCE 2000年第7期14卷 875-894页

作者： Shen, J Shen, W Shen, DF Univ Bordeaux 3 Inst EGID Image Lab F-33607 Pessac France Zhongshan Univ Dept Elect Guangzhou 510275 Peoples R China Ecole Natl Super Telecommun Bretagne Paris France

Moments are widely used in pattern recognition, image processing, computer vision and multiresolution analysis. To clarify and to guide the use of different types of moments, we present in this paper a study on the different moments and compare their behavior. After an introduction to geometric, Legendre, Hermite and Gaussian-Hermite moments and their calculation, we analyze at first their behavior in spatial domain. Our analysis shows orthogonal moment base functions of different orders having different number of zero-crossings and very different shapes, therefore they can better separate image features based on different modes, which is very interesting for pattern analysis and shape classification. Moreover, Gaussian-Hermite moment base functions are much more smoothed, they are thus less sensitive to noise and avoid the artifacts introduced by window function discontinuity. We then analyze the spectral behavior of moments in frequency domain. Theoretical and numerical analyses show that orthogonal Legendre and Gaussian-Hermite moments of different orders separate different frequency bands more effectively It is also shown that Gaussian-Hermite moments present an approach to construct orthogonal features from the results of wavelet analysis. The orthogonality equivalence theorem is also presented. Our analysis is confirmed by numerical results, which are then reported.

关键词： image characterization classification moments orthogonal moments behavior analysis frequency analysis orthogonality equivalence

来源：评论

学校读者我要写书评

暂无评论

Extraction of bibliography information based on image of book cover

引用

international JOURNAL OF pattern recognition AND ARTIFICIAL INTELLIGENCE 2000年第7期14卷 963-978页

作者： Yang, H Kashimura, M Onda, N Ozawa, S Keio Univ Dept Elect Engn Yokohama Kanagawa 2238522 Japan

This paper describes a new system for extracting and classifying bibliography regions from the color image of a book cover. The system consists of three major components: preprocessing, color space segmentation and text region extraction and classification. Preprocessing extracts the edge lines of the book and geometrically corrects and segments the input image, into the parts of front cover, spine and back cover. The same as all color image processing researches, the segmentation of color space is an essential and important step here. Instead of RGB color space, HSI color space is used in this system. The color space is segmented into achromatic and chromatic regions first;and both the achromatic and chromatic regions are segmented further to complete the color space segmentation. Then text region extraction and classification follow. After detecting fundamental features (stroke width and local label width) text regions are determined. By comparing the text regions on front cover with those on spine, all extracted text regions are classified into suitable bibliography categories: author, title, publisher and other information, without applying OCR.

关键词： color space segmentation HSI color space achromatic region chromatic region text region

来源：评论

学校读者我要写书评

暂无评论

3D articulated object understanding, learning, and recognition from 2D images

引用

international JOURNAL OF pattern recognition AND ARTIFICIAL INTELLIGENCE 2000年第7期14卷 863-873页

作者： Wang, PSP Northeastern Univ Boston MA 02115 USA

This paper is aimed at 3D object understanding from 2D images, including articulated objects in active vision environment, using interactive, and internet virtual reality techniques. Generally speaking, an articulated object can be divided into two portions: main rigid portion and articulated portion. It is more complicated that "rigid" object in that the relative positions, shapes or angles between the main portion and the articulated portion have essentially infinite variations, in addition to the infinite variations of each individual rigid portions due to orientations, rotations and topological transformations. A new method generalized from linear combination is employed to investigate such problems. It uses very few learning samples, and can describe, understand, and recognize 3D articulated objects while the objects status is being changed in an active vision environment.

关键词： articulated object recognition feature extraction learning active vision linear combination pattern representation thinning

来源：评论

学校读者我要写书评

暂无评论

Detection of sea surface small targets in infrared images based on multilevel filter and minimum risk Bayes test

引用

international JOURNAL OF pattern recognition AND ARTIFICIAL INTELLIGENCE 2000年第7期14卷 907-918页

作者： Moon, YS Zhang, TX Zuo, ZR Zuo, Z Huazhong Univ Sci & Technol Inst Pattern Recognit & Artificial Intelligence State Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China Chinese Univ Hong Kong Dept Comp Sci & Engn Hong Kong Hong Kong Peoples R China

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.

关键词： target detection infrared imaging multilevel filter minimum risk Bayes test pattern recognition modeling and learning

来源：评论

学校读者我要写书评

暂无评论

Multi-sensor 3D image fusion and interactive search

Multi-sensor 3D image fusion and interactive search

引用

international Conference on Information Fusion

作者： W.D. Ross A.M. Waxman W.W. Streilein M. Aguiiar J. Verly F. Liu M.I. Braun P. Harmon S. Rak Lincoln Laboratory Massachusetts Institute of Technology Lexington MA USA Massachusetts Institute of Technology Cambridge MA US Lincoln Lab. MIT Lexington MA USA

Describes a system under development for the 3D fusion of multi-sensor surface surveillance imagery, including electro-optical (EO), IR, SAR, multispectral and hyperspectral sources. Our approach is founded on biologically-inspired image processing algorithms. We have developed an image processing architecture enabling the unified interactive visualization of fused multi-sensor site data which utilizes a color image fusion algorithm based on retinal and cortical processing of color. We have also developed interactive Web-based tools for training neural network search agents that are capable of automatically scanning site data for the fused multi-sensor signatures of targets and/or surface features of interest. Each search agent is an interactively trained instance of a neural network model of cortical pattern recognition called a fuzzy ARTMAP. The utilization of 3D site models is central to our approach because it enables the accurate multi-platform image registration that is necessary for color image fusion and the designation, learning and searching for multi-sensor fused pixel signatures. Interactive stereo 3D viewing and fly-through tools enable efficient and intuitive site exploration and analysis. Web-based remote visualization and search agent training and utilization tools facilitate rapid, distributed and collaborative site exploitation and dissemination of results.

关键词： image fusion Color image processing Neural networks Surveillance Hyperspectral imaging Data visualization Retina pattern recognition Fuzzy neural networks

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：