检索结果-内蒙古大学图书馆

Development of a multispectral imagery device devoted to weed detection

JOURNAL OF ELECTRONIC IMAGING 2004年第3期13卷 547-552页

作者： Vioix, JB Douzals, JP ENESAD F-21800 Quetigny France LE21 F-71200 Le Creusot France

Multispectral imagery is a large domain with a number of practical applications: thermography and quality control in industry, food science, and agronomy. The main interest is to obtain spectral information of the objects for which a reflectance signal can be associated to physical, chemical, and/or biological properties. Agronomic applications of multispectral imagery generally involve the acquisition of several images in visible and near infrared wavelengths. We first present a different kind of multispectral devices used for agronomic applications and then introduce an original multispectral acquisition system based on a single CCD. First results in laboratory are detailed, presenting a detection method using a neural network and in-field acquisitions and their results are shown. To improve the quality of weed detection, the spatial distribution of crops is used by a second method. Finally, the first works on merging are outlined. (C) 2004 SPIE and IST.

关键词： Optical filters Multispectral imaging Charge-coupled devices Reflectivity neural networks Cameras Neurons Spatial resolution image processing Visible radiation

来源：评论

学校读者我要写书评

暂无评论

Pattern synchronization for associative memory in pulse coded neural networks

Pattern synchronization for associative memory in pulse code...

引用

47th Midwest Symposium on Circuits and Systems (MWSCAS 2004)

作者： Witkowski, U Rückert, U Univ Paderborn Heinz Nixdorf Inst D-33102 Paderborn Germany

ISBN: (纸本)078038346X

For image processing a lot of algorithms have been developed in the past that are well suited for specific tasks. These algorithms are often optimized for high performance computers with high power consumption, thus, it is not possible to use these algorithms for mobile applications. In this paper, a massive parallel vision system is partly discussed which is biologically inspired and requires less power. This system consists of several layers of pulsed neural networks, e.g. some layers form specific features detectors to decompose the input image in several features. The features are completed or bound by an associative memory that needs a synchronized input pulse pattern. In this paper, we focus on the synchronization stage of the system that is combined with the associative memory. The discussed synchronization unit detects correlated pulses in the network, collects them and activates a synchrones output pattern.

关键词： neural networks

来源：评论

学校读者我要写书评

暂无评论

Multi-layer cellular neural network and fuzzy C-mean classifiers comparison and performance analysis

Multi-layer cellular neural network and fuzzy C-mean classif...

引用

conference on applications of Digital image processing XXVii

作者： San-Martin, MT Hlebarov, V Sadki, M Brunel Univ Dept Elect & Comp Engn Uxbridge UB8 3PH Middx England

ISBN: (纸本)0819454966

neural networks and Fuzzy systems are considered two of the most important artificial intelligent algorithms which provide classification capabilities obtained through different learning schemas which capture knowledge and process it according to particular rule-based algorithms. These methods are especially suited to exploit the tolerance for uncertainty and vagueness in cognitive reasoning. By applying these methods with some relevant knowledge-based rules extracted using different data analysis tools, it is possible to obtain a robust classification performance for a wide range of applications. This paper will focus on non-destructive testing quality control systems, in particular, the study of metallic structures classification according to the corrosion time using a novel cellular neural network architecture, which will be explained in detail. Additionally, we will compare these results with the ones obtained using the Fuzzy C-means clustering algorithm and analyse both classifiers according to its classification capabilities.

关键词： cellular-neural network Fuzzy C-means texture features metallic structures corrosion

来源：评论

学校读者我要写书评

暂无评论

Automatic processing, analysis and recognition of images

Automatic processing, analysis and recognition of images

引用

conference on applications of Digital image processing XXVii

作者： Abrukov, VS Smirnov, VE Ivanov, DG Chuvash State Univ Physicotech Fac Cheboksary 428015 Russia

ISBN: (纸本)0819454966

New approaches and computer codes (A&CC) for automatic processing, analysis and recognition of images are offered. The A&CC are based on presentation of object image as a collection of pixels of various colours and consecutive automatic painting of distinguished itself parts of the image. The A&CC have technical objectives centred on such direction as: 1) image processing, 2) image feature extraction, 3) image analysis and some others in any consistency and combination. The A&CC allows to obtain various geometrical and statistical parameters of object image and it's parts. Additional possibilities of the A&CC usage deal with an usage of artificial neural networks technologies. We believe that A&CC can be used at creation of the systems of testing and control in a various field of industry and military applications (airborne imaging systems, tracking of moving objects), in medical diagnostics, at creation of new software for CCD, at industrial vision and creation of decision-making system, etc. The opportunities of the A&CC are tested at image analysis of model fires and plumes of the sprayed fluid, ensembles of particles, at a decoding of interferometric images, for digitization of paper diagrams of electrical signals, for recognition of the text, for elimination of a noise of the images, for filtration of the image, for analysis of the astronomical images and air photography, at detection of objects.

关键词： image processing analysis recognition automation particles ensemble spray

来源：评论

学校读者我要写书评

暂无评论

Automatic analysis of images

Automatic analysis of images

引用

conference on Sensors and Camera Systems for Scientific, Industrial, and Digital Photography applications V

作者： Abrukov, VS Chuvash State Univ Phys Tech Fac Cheboksary Russia

ISBN: (纸本)0819452041

A new approaches and computer codes (A&CC) for automatic analysis of images are offered. The A&CC are based on presentation of object image as a collection of pixels of various colours and consecutive painting of distinguished itself parts of the image in unusual manner. The A&CC have technical objectives centred on such direction as: 1) image processing (filtration, elimination of noise, segmentation), 2) image feature extraction, 3) image analysis, 4) recognition of image and object and some others. Additional possibilities of the A&CC dealing with usage of artificial neural networks technologies. The A&CC allows to obtain various geometrical and statistical parameters of object image and object. Among them: coordinates and maximum values of cross sizes of every individual part of object image, its square and perimeter, histogram of individual parts with respect to size as well as with respect to type, to form, etc. The opportunities of the A&CC are tested at image analysis of model fires and plumes of the sprayed fluid, ensembles of particles, at a decoding of interferometric images, for elimination of a noise of the images, for filtration of the image, at detection of objects.

关键词： image processing analysis recognition automation particles ensemble spray

来源：评论

学校读者我要写书评

暂无评论

Optimal design of neural networks for land-cover classification from multispectral imagery

Optimal design of neural networks for land-cover classificat...

引用

conference on image and Signal processing for Remote Sensing IX

作者： Silván-Cárdenas, JL Ctr Invest Geog & Geomat Ing Jorge L Tamayo Mexico City 01900 DF Mexico

ISBN: (纸本)0819451215

It has long been shown the effectiveness of artificial neural networks to solve highly non-linear problems such as land-cover classification based on multispectral imagery. However, due to the large amount of data that is processed within this kind of applications, it is desirable to design networks with the lowest number of neurons that are capable to separate all of the given classes. At present, there are several methods intended to determine this optimal network. Most of them involve adjoining or pruning hidden neurons followed by further training in iterative fashion, which is generally a very slow process. As an alternative, the approach described in this paper is based on the computation of centroids of relevant clusters for each class samples through the well known clustering method ISODATA. A proper tessellation of the ISODATA centroids allows first the determination of the minimum number of neurons in the first hidden layer that are required to effectively separate all of the classes;and secondly, to compute weight and bias parameters for such neurons. Then, the minimum network required to perform the logic function that combines the halfspaces generated by the first layer into classdiscriminant surfaces is determined via a logic function reduction method. This approach is much faster than that of current methods because it allows to determine the optimum network size and compute weight and bias parameters without further iterative adjustments. The procedure was tested with landsat 7 Enhanced Thematic Mapper Plus (ETM+) data. Results indicated that (1) the network exhibits good generalization behavior and (2) classification accuracies do not depend on the class boundary complexity but only on the class overlapping extent.

关键词： land-cover classification clustering method neural networks Voronoi tessellation Delaunay graph binary function reduction

来源：评论

学校读者我要写书评

暂无评论

Sub-pixel jitter video restoration on board of micro-UAV

Sub-pixel jitter video restoration on board of micro-UAV

引用

conference on Independent Component Analyses, Wavelets, Unsupervised Smart Sensors and neural networks ii

作者： Szu, H Buss, J Garcia, J Breaux, N Kopriva, I Karangelen, N Hsu, M Lee, T Willey, J Shield, G Brown, S Robbins, R Hobday, J ONR Arlington VA USA

ISBN: (纸本)0819453625

We review various image processing algorithms for micro-UAV EO/IR sub-pixel jitter restoration. Since the micro-UAV, Silver Fox, cannot afford isolation coupling mounting from the turbulent aerodynamics of the airframe, we explore smart real-time software to mitigate the sub-pixel jitter effect. We define jitter to be sub-pixel or small-amplitude vibrations up to one pixel, as opposed to motion blur over several pixels for which there already exists real time correction algorithms used on other platforms. We divide the set of jitter correction algorithms into several categories: They are real time, pseudo-real time, or non-real-time, but they are all standalone, i.e. without relying on a library storage or flight data basis on-board the UAV. The top of the list is demonstrated and reported here using real-world data and a truly unsupervised, real-time algorithm.

关键词： micro-UAV jitter restoration sub-pixel unsupervised learning band-limited stationary Wiener filter auto regression artificial neural networks

来源：评论

学校读者我要写书评

暂无评论

Content-based image retrieval by matching hierarchical attributed region adjacency graphs

Content-based image retrieval by matching hierarchical attri...

引用

Medical Imaging 2004 conference

作者： Fischer, B Thies, C Güld, MO Lehmann, TM Rhein Westfal TH Aachen Dept Med Informat RWTH D-52057 Aachen Germany

ISBN: (纸本)0819452831

Content-based image retrieval requires a formal description of visual information. In medical applications, all relevant biological objects have to be represented by this description. Although color as the primary feature has proven successful in publicly available retrieval systems of general purpose, this description is not applicable to most medical images. Additionally, it has been shown that global features characterizing the whole image do not lead to acceptable results in the medical context or that they are only suitable for specific applications. For a general purpose content-based comparison of medical images, local, i.e. regional features that are collected on multiple scales must be used. A hierarchical attributed region adjacency graph (HARAG) provides such a representation and transfers image comparison to graph matching. However, building a HARAG from an image requires a restriction in size to be computationally feasible while at the same time all visually plausible information must be preserved. For this purpose, mechanisms for the reduction of the graph size are presented. Even with a reduced graph, the problem of graph matching remains NP-complete. In this paper, the Similarity Flooding approach and Hopfield-style neural networks are adapted from the graph matching community to the needs of HARAG comparison. Based on synthetic image material build from simple geometric objects, all visually similar regions were matched accordingly showing the framework's general applicability to content-based image retrieval of medical images.

关键词： picture archiving and communication systems (PACS) content-based image retrieval (CBIR) graph thinning graph matching artificial intelligence neural networks computer-aided diagnosis shape analysis multiscale image representation

来源：评论

学校读者我要写书评

暂无评论

Classification system for GPR parameters

Classification system for GPR parameters

引用

10th International conference on Ground Penetrating Radar (GPR 2004)

作者： Yelf, R Al-Nuaimy, W Georadar Res Pty Ltd Coffs Harbour NSW 2450 Australia

ISBN: (纸本)9090179593

This paper addresses a problem commonly encountered in the processing and interpretation of GPR data for civil engineering and geotechnical applications. These projects typically involve large data sets composed of multivariate parameters, which need to be interpreted and coded in such a manner as to provide practical solutions to the site engineer. In this paper we propose a system for approaching this problem that has been field tested on many projects. This system uses two numerical descriptors for classifying complex geotechnical parameters derived from GPR field measurements. The first parameter, called GPR Class, is used to code the relative difficulty of excavation, or danger from instability. The second parameter, the GPR Rock Type Descriptor, is used to code the local soil or rock type and to describe the attributes of the material, such as its weathering condition or degree of cementation. The system is a highly efficient for coding large transects of GPR data. The coding system is also suitable for training artificial neural networks. neural networks are being used with increasing frequency for high dimensional problems of regression or classification. These networks, combined with second-order statistical image descriptors, can then be combined to visualise the data in 3 dimensions in a format readily comprehensible to persons without specialist GPR technical knowledge.

关键词： ground penetrating radar (GPR) GPR class GPR rock type descriptor geotechnical investigations rock quality roof stability Fibre Optic Cable neural networks

来源：评论

学校读者我要写书评

暂无评论

Efficient wavelet Architectures using field-programmable logic and residue number system arithmetic

Efficient wavelet Architectures using field-programmable log...

引用

conference on Independent Component Analyses, Wavelets, Unsupervised Smart Sensors and neural networks ii

作者： Ramírez, J Meyer-Baese, U García, A Dept Electron & Tecnol Computadores E-18071 Granada Spain

ISBN: (纸本)0819453625

Wavelet transforms are becoming increasingly important as an image processing technology. Their efficient implementation using commercially available VLSI technology is a subject of continuous study and development. This paper presents the implementation using modern Altera APEX20K field-programmable logic (FPL) devices of reduced complexity and high performance wavelet architectures by means of the residue number system (RNS). The improvement is achieved by reducing arithmetic operations to modulo operations executed in parallel over small wordy length channels. The systems are based on index arithmetic over Galois fields and the key for attaining low-complexity and high-throughput is an adequate selection of a small word-width modulus set. These systems are programmable in the sense that their coefficients can be reprogrammed in order to make them more suitable for most of the applications. FPL-efficient converters are also developed and the overhead of the input and output conversion is assessed. The design of a reduced complexity epsilon-CRT converter makes the conversion overhead of this kind of systems be not important for their practical implementation. The proposed structures are compared to traditional systems using 2's complement arithmetic. With this and other innovations, the proposed architectures are about 65% faster than the 2's complement designs and require fewer logic elements in most cases.

关键词： digital signal processing programmable wavelet FIR filters index arithmetic residue number system quadratic residue number system field-programmable logic devices

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：