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检索条件"任意字段=Conference on Image Processing and Pattern Recognition in Remote Sensing"

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Evaluation of holographic subsurface radar for NDE of space shuttle thermal protection tiles

Evaluation of holographic subsurface radar for NDE of space ...

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conference on Sensors and Systems for Space Applications

作者： Lu, Thomas Snapp, Cooper Chao, Tien-Hsin Thakoor, Anilkumar Bechtel, Tim Ivashov, Sergey Vasiliev, Igor NASA Jet Prop Lab Bioinspired Syst & Technol Grp Pasadena CA 91109 USA NASA Johnson Space Ctr Thermal Design Branch ES3 Houston TX USA Univ Penn Enviroscan Inc Philadelphia PA 19104 USA Bauman Moscow State Tech Univ Remote Sensing Lab Moscow Russia

ISBN: (纸本)9780819466778

Experiments have been carried out to evaluate holographic subsurface radar (RASCAN) for non-destructive evaluation (NDE) of subnominal bond conditions between the Space Shuttle Thermal Protection System tiles and the aluminum substrate. Initial results have shown detection of small voids and spots of moisture between Space Shuttle thermal protection tiles and underlying aluminum substrate. The characteristic feature of this device is the ability to obtain one-sided radar soundings/images with high sensitivity (detecting of wire of 20 micron and less in diameter), and high resolution (2 cm lateral resolution) in the frequency band of 3.6-4.0 GHz. JPL's advanced high-speed image processing and pattern recognition algorithms can be used to process the data generated by the holographic radar and automatically detect and measure the defects. Combining JPL's technologies with the briefcase size, portable RASCAN system will produce a simple and fully automated scanner capable of inspecting dielectric heat shielding materials or other spacecraft structures for cracks, voids, inclusions, delamination, debonding, etc.. We believe this technology holds promise to significantly enhance the safety of the Space Shuttle and the future CEV and other space exploration missions.

关键词： holographic radar non-destructive testing space shuttle thermal protection tile bonding

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A Knowledge Based Classification for Urban Mapping Using High Resolution remote sensing Data

A Knowledge Based Classification for Urban Mapping Using Hig...

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Proceedings of the Digital image Computing: Technqiues and Applications (DICTA)

作者： Xiao Yi Xiuping Jia David Tien School of Information Technology Charles Sturt University Bathurst NSW Australia School of Information Technology and Electrical Engineering University of New South Wales Campbell ACT Australia

ISBN: (纸本)9781424431618;9780769530673

This paper addresses the weakness of pixel based or cell-based classification algorithms for urban mapping. They cannot provide a handy object level classification results as often preferred in urban planning and assessment applications. A knowledge based approach is proposed which is integrated with the spectral classification methods and image processing tools. Experiments using a high resolution image were conducted. The results show the proposed method can improve the performances obtained by using the conventional maximum likelihood or ECHO algorithms. Key words: Knowledge based, Object attributes, classification.

关键词： remote sensing image resolution Australia Classification algorithms Urban planning Information technology Geographic Information Systems Spatial resolution Urban areas Layout

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A Knowledge-Based Target recognition Method For remote sensing image

A Knowledge-Based Target Recognition Method For Remote Sensi...

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IEEE International conference on Integration Technology (ICIT)

作者： Zhenli Ma Huibin Wang Xinyao Lao Min Tang Fengchen Huang College of Computer and Information Engineering Hohai University HHU Nanjing Jiangsu China

This paper proposed a knowledge-based target bridge detection method from remote sensing images. Firstly, the prior knowledge about bridge can supervise the low and middle image processing and analysis to detect the edges of bridges and riversides. Secondly, knowledge about the different characters of the bridge edges and riverside edges was used to wipe off the riverside edges and remain the lines of bridges, so that the purpose of recognition on bridge can be achieved. The method was tested on spot remote sensing images and the result shows it can detect the bridges exactly from images.

关键词： Target recognition remote sensing Bridges image edge detection image analysis image segmentation Radar detection Rivers Educational institutions Knowledge engineering

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An adaptive nonparametric discriminant analysis method and its application to face recognition

An adaptive nonparametric discriminant analysis method and i...

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8th Asian conference on Computer Vision, ACCV 2007

作者： Huang, Liang Yong, Ma. Ijiri, Yoshihisa Lao, Shihong Kawade, Masato Zhao, Yuming Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai 200240 China Sensing and Control Technology Lab. Omron Corporation Kyoto 619-0283 Japan

ISBN: (纸本)9783540763895

Linear Discriminant Analysis (LDA) is frequently used for dimension reduction and has been successfully utilized in many applications, especially face recognition. In classical LDA, however, the definition of the between-class scatter matrix can cause large overlaps between neighboring classes, because LDA assumes that all classes obey a Gaussian distribution with the same covariance. We therefore, propose an adaptive nonparametric discriminant analysis (ANDA) algorithm that maximizes the distance between neighboring samples belonging to different classes, thus improving the discriminating power of the samples near the classification borders. To evaluate its performance thoroughly, we have compared our ANDA algorithm with traditional PCA+LDA, Orthogonal LDA (OLDA) and nonparametric discriminant analysis (NDA) on the FERET and ORL face databases. Experimental results show that the proposed algorithm outperforms the others. © Springer-Verlag Berlin Heidelberg 2007.

关键词： Face recognition

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Extraction of residential information from high-spatial resolution image integrated with upscaling methods and object multi-features - art. no. 678605

Extraction of residential information from high-spatial reso...

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5th International Symposium on Multispectral image processing and pattern recognition

作者： Dong, Lixin Wu, Bingfang Chinese Acad Sci Inst Remote Sensing Applicat Beijing 100101 Peoples R China

ISBN: (纸本)9780819469502

Monitoring residential areas at a regional scale, and even at a global scale, has become an increasingly important topic. However, extraction of residential information was still a difficulty and challenging task, such as multiple usable data selection and automatic or semi-automatic techniques. In metropolitan area, such as Beijing, urban sprawl has brought enormous pressure on rural and natural environments. Given a case study, a new strategy of extracting of residential information integrating the upscaling methods and object multi-features was introduced in high resolution SPOT fused image. Multi-resolution dataset were built using upscaling methods, and optimal resolution image was selected by semi-variance analysis approach. Relevant optimal spatial resolution images were adopted for different type of residential area (city, town and rural residence). Secondly, object multi-features, including spectral information, generic shape features, class related features, and new computed features, were introduced. An efficient decision tree and Class Semantic Representation were set up based on object multi-features. And different classes of residential area were extracted from multi-resolution image. Afterwards, further discussion and comparison about improving the efficiency and accuracy of classification with the proposed approach were presented. The results showed that the optimal resolution image selected by upscaling and semi-variance method successfully decreased the heterogeneous, smoothed the noise influence, decreased computational, storage burdens and improved classification efficiency in high spatial resolution image. The Class Semantic Representation and decision tree based on object multi-features improved the overall accuracy and diminished the 'salt and pepper effect'. The new image analysis approach offered a satisfactory solution for extracting residential information quickly and efficiently.

关键词： upscaling methods object multi-features semi-variance analysis multi-resolution residential area

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Perceptual Grouping for Building recognition in High-resolution SAR images using the GESTALT-System

Perceptual Grouping for Building Recognition in High-resolut...

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Urban remote sensing Joint Event

作者： Eckart Michaelsen Leo Doktorski Uwe Soergel Uwe Stilla FGAN-FOM Research Institute of Optronics and Pattern Recognition Ettlingen Germany Institute of Photogrammetry and GeoInformation University of Hanover Germany Institute of Photogrammetry and Remote Sensing Technical University Munich Germany

GESTALT is a production system interpreter designed for advanced automatic recognition from difficult pictorial data. Building recognition from leading edge high resolution SAR-data is a good example for such a challenge. This contribution explains the system itself and its application to this particular issue. Perceptual grouping paradigms are coded in the productions in order to discriminate man-made ordered structure from arbitrary clutter. In particular symmetry and repetitive similar structure render promising prospects for this application.

关键词： image recognition Production systems Buildings remote sensing Humans Machine vision Statistics Pins Rendering (computer graphics) image processing

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International conference on Robotic Welding, Intelligence and Automation, RWIA 2006

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International conference on Robotic Welding, Intelligence and Automation, RWIA 2006

ISBN: (纸本)3540733736

The proceedings contain 64 papers. The special focus in this conference is on Robotic Welding, Intelligence and Automation. The topics include: Behavior-based intelligent robotic technologies in industrial applications;detecting system modeling and hand-eye calibration for a robot to detect the ablation of hydro-turbine blades;dynamic model and control for an omnidirectional mobile manipulator;soft touch control strategy of remote teaching based on force sensing;a novel pose estimation system for indoor mobile robots based on two optical sensors;haptic teleoperation of robotic manipulator;practical stabilization of nonholonomic mobile robots moving on uneven surface;an efficient method for collision detection and distance queries in a robotic bridge maintenance system;laser vision system based on synchronized scanning method;a wide angle-of-view thermal imaging system utilizing the rotation of optical path;on the key technologies of intelligentized welding robot;numerical study of tube cathode arc with anode melting;planning the torch orientation of planar lap joint in robotic welding;automatic path planning for welding robot based on reconstructed surface model;study on the control strategy of commutation process in variable polarity plasma arc welding;recognition of macroscopic seam for complex robotic welding environment;research on performance of welding fuzzy petri net model;integrated weld quality control system based on laser strobe vision;visual sensing and image processing in aluminum alloy welding;efficient weld seam detection for robotic welding from a single image.

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Developing an Automated System, Based on Remtoly-Sensed Data, for Recognizing the Effect of Climate on the Morphology of Urban Open Spaces

Developing an Automated System, Based on Remtoly-Sensed Data...

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Urban remote sensing Joint Event

作者： Aviva Peeters Yair Etzion Desert Architecture and Urban Planning Unit Department of Man in the Desert Jacob Blaustein Institutes for Desert Research Ben-Gurion University of the Negev Israel

Urban form reflects cultural, socio-economical and environmental parameters and constraints. An important environmental generator of urban form is climate. The majority of existing research that deals with the influence of climate on the development of urban form tends to present vernacular (traditional) urban form as a successful combination of architecture, urban design and climate. This assumption is supported by the claim that vernacular settlements adapted to the harsh climatic conditions through a process of trial and error. Selected cases of vernacular settlements are often presented to support this claim. This paper introduces the first part of an ongoing research which develops a model that investigates this claim through a quantitative based analysis. An automated system is under development, which will assist in studying the effect of prevailing climatic conditions on the development of urban form, particularly the development of vernacular urban form in hot-arid regions. This system combines: a) automated recognition of urban open spaces and b) automated recognition of morphological patterns and their analysis based on local climatic conditions. The system is based on remotely-sensed images with very-high spatial resolution and integrates image processing tools with Geographic Information Systems (GIS) spatial analysis.

关键词： Morphology pattern recognition Geographic Information Systems Cultural differences pattern analysis remote sensing Spatial resolution image processing image analysis Information analysis

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A Hierarchical Finite-State Model for Texture Segmentation

A Hierarchical Finite-State Model for Texture Segmentation

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International conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Giuseppe Scarpa Michal Haindl Josiane Zerubia DIET University Federico II Italy INRIA/I3S ARIANA Research Group France Pattern Recognition Dep. Academy of Sciences Prague Czech Republic

A novel model for unsupervised segmentation of texture images is presented. The image to be segmented is first discretized and then a hierarchical finite-state region-based model is automatically coupled with the data by means of a sequential optimization scheme, namely the texture fragmentation and reconstruction (TFR) algorithm. Both intra- and inter-texture interactions are modeled, by means of an underlying hierarchical finite-state model, and eventually the segmentation task is addressed in a completely unsupervised manner. The output is then a nested segmentation, so that the user may decide the scale at which the segmentation has to be provided. TFR is composed of two steps: the former focuses on the estimation of the states at the finest level of the hierarchy, and is associated with an image fragmentation, or over-segmentation; the latter deals with the reconstruction of the hierarchy representing the textural interaction at different scales.

关键词： image segmentation image reconstruction Clustering algorithms State estimation pattern recognition Biomedical imaging remote sensing Source coding System testing Benchmark testing

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Support Vector Machine for Classification of Hyperspectral remote sensing imagery

Support Vector Machine for Classification of Hyperspectral R...

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International conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Chen-guang Dai Xiao-bo Huang Guang-jun Dong Zhengzhou Institute of Surveying and Mapping Zhengzhou China

As one of the popular and advanced statistical learning algorithms, support vector machine (SVM) has been the new hot study area of pattern recognition and machine learning in recent years. SVM has such advantages as suitableness to high dimensional data, requirement of few samples and robustness to uncertainty, so it can be used to hyperspectral remote sensing image classification effectively. Based on the theory of SVM, a new approach for information classification on hyperspectral sensor has been developed by the experimental case of spatial information classification in central area of Shanghai city with PHI image. The algorithm is synthetically compared with the traditional classification methods. The experiment results confirm the effectiveness of the proposed method, which results in higher classification accuracy than the traditional methods.

关键词： Support vector machines Support vector machine classification Hyperspectral sensors Hyperspectral imaging remote sensing Statistical learning Machine learning algorithms pattern recognition Machine learning Robustness

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