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检索条件"任意字段=5th International Symposium on Multispectral Image Processing and Pattern Recognition"

共 1596 条记录，以下是1501-1510 订阅

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A hypergraph-based image database clustering framework

A hypergraph-based image database clustering framework

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international symposium on I/V Communications and Mobile Network (ISVC)

作者： Aurélien Ducournau Soufiane Rital Alain Bretto ENISE-DIPI EA 3719 Saint Etienne France LTCI CNRS TSI Telecom ParisTech Paris France Centre National de la Recherche Scientifique Paris ÃŽle-de-France FR

this paper describes a new approach to image database clustering. the method requires no a priori information. It works free of context and previous knowledge: in a first stage, the image features are formed automatically, and modeled by a p-Nearest Neighbor Hypergraph (p-NNH) representation. then images are clustered to form categories using a multilevel p-NNH partitioning approach. the partitioning approach operates on Coarsening-Paritioning-UnCoarsening scheme (CPUC). Categories are visualized by displaying the most typical image(s) of the categories as thumbnails. the main benefit of the approach is that it deals with a large volume image database and with a representation structure (hypergraph) that is close to the human visual grouping system. To judge results, an evaluation scheme which is adequate for the task of categorization is proposed.

关键词： image databases Partitioning algorithms Clustering algorithms image color analysis Heuristic algorithms pattern recognition Visualization

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Non-contact Support Based on image processing for 3D Printing

Non-contact Support Based on Image Processing for 3D Printin...

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Robotics & Intelligent Manufacturing Technology (ISRIMT), international symposium on

作者： Yizhe Yang Yatao Liu Bingshan Liu Wei Wang Gong Wang Chinese Academy of Sciences Technology and Engineering Center for Space Utilization Beijing China

Additive manufacturing (AM) technology has received widespread attention due to its advantages in layer-by-layer printing, among which stereolithography is applied to the printing of precision ceramic products. Due to the non-Newtonian fluid properties of ceramic slurry, non-contact support can help ensure manufacturability and reduce accuracy loss. But currently, the efficiency of existing detection and generation algorithms is relatively low. this article proposes a fast recognition and generation method for non-contact support based on slicing through image processing methods such as Boolean and morphological operations, which avoids time-consuming pixel traversal. the comparison with previous work results verifies the effectiveness of this algorithm. the checkerboard-like support has been eliminated and the speed has increased significantly.

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Multi-bits Fingerprinting for image Captured by Digital Camera

Multi-bits Fingerprinting for Image Captured by Digital Came...

引用

international Conference on Information, Communications and Signal processing

作者： Won-gyum Kim Seon Hwa Lee Yong-seok Seo Youngho Suh Digital Contents Research Division Electronics and Telecommnications Research Institute Daejeon South Korea

this paper presents a new image fingerprinting scheme which embeds multi-bits fingerprinting code and is robust to the capturing attack by a digital camera. When capturing an image by a digital camera, various kinds of distortions such as noise, geometrical distortion and lens distortion are applied simultaneously. In this paper, we propose several steps to extract fingerprints from the distorted image. To embed fingerprinting code into an image designing of multi-bits embedding is required. We embed 64 bits information as a fingerprint into a 512times512 color image. In order to restore a captured image from geometrical distortions a noise reduction filter is performed and a rectilinear tiling pattern is used as a template. Actually a multi-bits fingerprinting code is embedded repeatedly like a tiling pattern into the spatial domain of the image. We show that the extracting is successful from the image captured by a digital camera through the experiment

关键词： Fingerprint recognition Digital cameras Lenses Data mining Watermarking Color Cities and towns Noise robustness image restoration Noise reduction

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Florence faces: A dataset supporting 2D/3D face recognition

Florence faces: A dataset supporting 2D/3D face recognition

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international symposium on Communications Control and Signal processing (ISCCSP)

作者： Andrew D. Bagdanov Alberto Del Bimbo Iacopo Masi MICC-Media Integration and Communication Center University of Florence Italy

this article describes a new dataset under construction at the Media Integration and Communication Center and the University of Florence. the dataset consists of high-resolution 3D scans of human faces from each subject, along with several video sequences of varying resolution and zoom level. Each subject is recorded in a controlled setting in HD video, then in a less-constrained (but still indoor) setting using a standard, PTZ surveillance camera, and finally in an unconstrained, outdoor environment with challenging conditions. In each sequence the subject is recorded at three levels of zoom. this dataset is being constructed specifically to support research on techniques that bridge the gap between 2D, appearance-based recognition techniques, and fully 3D approaches. It is designed to simulate, in a controlled fashion, realistic surveillance conditions and to probe the efficacy of exploiting 3D models in real scenarios.

关键词： three dimensional displays Solid modeling Face recognition Databases Cameras Lighting image resolution

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In-sensor low-complexity audio pattern recognition for pervasive networking

In-sensor low-complexity audio pattern recognition for perva...

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international symposium on Wireless Pervasive Computing (ISWPC)

作者： Marco Martalò Gianluigi Ferrari Claudio Malavenda WASN Laboratory Department Inform. Eng University of Parma Italy Elsag Datamat SpA Rome Italy

ISBN: (纸本)9781424468553;9781424468584

In the last years, wireless sensor networking has become a key technology for making pervasive communications a reality. To this end, wireless sensor nodes need to consume as less energy as possible and, thus, the complexity of any onboard signal processing operation needs to be kept as low as possible. In this paper, we present a low-complexity detection approach for the recognition of different audio signal patterns, expedient, for example, for intrusion control in critical areas. To this end, the proposed detection algorithm evolves through two main processing phases: (a) coarse and (b) fine. the evolution between these two phases is described through a finite state machine (FSM) model. In fact, fine processing (in the frequency domain) is carried out only when an “atypical” audio signal is detected. On the other hand, coarse processing (in the time domain), performed a larger number of times, has a much lower complexity. Our results show that our processing technique allows to detect efficiently the presence of signals of interest (identified by properly selected spectral signatures) and to reliably distinguish different audio signal patterns, e.g., between speech and non-speech signals. While we first present simulation-based performance results of the proposed detection algorithm, we then validate our approach with realistic experimental results based on audio signals acquired with a commercial microphone.

关键词： pattern recognition Signal processing Wireless sensor networks Detection algorithms Signal processing algorithms Automata Frequency domain analysis Signal detection Speech processing Microphones

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Handwritten Bengali Numeral recognition using HOG Based Feature Extraction Algorithm

Handwritten Bengali Numeral Recognition using HOG Based Feat...

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international Conference on Signal processing and Integrated Networks (SPIN)

作者： Amitava Choudhury Hukam Singh Rana Tanmay Bhowmik Indian Insritute of Engineering Science and Technology Shibpur SoCS UPES Dehradun School of Computer Science UPES Dehradun India

Hand written character recognition is widely used in modern research. Recognize the characters from an image has always been active research area in the computer vision community. Apart from English, there are several regional languages available worldwide. In India there are 22 official languages, and Bengali is one of them. Bengali script has its own writing pattern. Like any other language number system, Bengali numeral system has ten different digits to indicate 0-9. It has its own alphabets and numerals. In this paper, Histogram of oriented gradient (HOG) and color histogram for selection of features algorithm is proposed. HOG are used as the feature set to represent each digit sample at the feature space and Support Vector Machine (SVM) used to produce the output from input image. Proposed algorithm is efficient and gives an accuracy of 98.05 on CMATERDB3.1.1 dataset. this type of numeric image recognition can be use in the post offices to acknowledge the pin code written in Bengali.

关键词： Feature extraction Handwriting recognition Histograms Character recognition Signal processing algorithms Support vector machines image color analysis

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An effective method for people detection in grayscale image sequences

An effective method for people detection in grayscale image ...

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IEEE international Conference on Intelligent Computer Communication and processing (ICCP)

作者： Mircea Popa Gheorghe Lazea Andras Majdik Levente Tamas Istvan Szoke Department of Automatics Technical University Cluj-Napoca Romania

this paper presents a method for detecting people from images taken with a camera mounted on a robot. the purpose of the detection is avoiding people collision while robot is moving within an unknown environment. It combines two algorithms for this purpose. First, the appearance of people is learned using a set of Haar-like features and the Adaboost algorithm. this information is embedded by building a classifier to differentiate people appearances by other structures. When an image is analyzed for detecting people, regions which contain vertical structures are determined using image gradients. those regions which have a specific aspect-ratio are selected and the classifier is applied on them. the classifier marks the regions which contain people-like structures. Because this method is desired to be integrated in an autonomous robot navigation system for a dynamic environment, particular attention is paid to increase the speed of the detection as much as possible.

关键词： Gray-scale image sequences Object detection Object recognition Active contours pattern recognition Robotics and automation image analysis Navigation image edge detection

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Advances in Neural Networks – ISNN 2013 1

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： Chengan Guo Zeng-Guang Hou Zhigang Zeng

ISBN: (数字)9783642390685

ISBN: (纸本)9783642390678

the two-volume set LNCS 7951 and 7952 constitutes the refereed proceedings of the 10th international symposium on Neural Networks, ISNN 2013, held in Dalian, China, in July 2013. the 157 revised full papers presented were carefully reviewed and selected from numerous submissions. the papers are organized in following topics: computational neuroscience, cognitive science, neural network models, learning algorithms, stability and convergence analysis, kernel methods, large margin methods and SVM, optimization algorithms, varational methods, control, robotics, bioinformatics and biomedical engineering, brain-like systems and brain-computer interfaces, data mining and knowledge discovery and other applications of neural networks.

关键词： Computation by Abstract Devices Artificial Intelligence pattern recognition image processing and Computer Vision Mathematical Modeling and Industrial Mathematics Algorithm Analysis and Problem Complexity

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Neural networks and emerging technologies

Neural networks and emerging technologies

引用

IEEE international Conference on Fuzzy Systems (FUZZ-IEEE)

作者： G. Erten M.L. Padgett F.M. Salam IC Tech Inc. USA Aubum University USA Michigan State University USA

Neural networks and related soft computing algorithms and architectures represent the next step in the evolution of information processing. Two categories of approaches define the domains of implementation: the concept of conventional processing to emulate neural algorithms, and the creation of networks of experimental computer chips, called silicon neurons. the role of neural networks in redefining and expanding computing, intelligent processing, and multimedia integration are explored by this panel. the goal of the forum is to present an overview or a snapshot of examples of the status and role of neural networks and related fields.

关键词： Neural networks Biological neural networks Computer networks Signal processing algorithms Intelligent networks Neurons Inspection Computer aided manufacturing image recognition pattern recognition

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Classifying Agricultural Terrain for Machinery Traversability Purposes

Classifying Agricultural Terrain for Machinery Traversabilit...

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5th IFAC Conference on Sensing, Control and Automation Technologies for Agriculture (AGRICONTROL)

作者： Yandun, Francisco J. Gregorio, Eduard Zuniga, Marcos Escola, Alexandre Rosell-Polo, Joan R. Auat Cheein, Fernando A. Univ Tecn Federico Santa Maria Elect Engn Dept Valparaiso Chile Univ Lleida Agrotecn Ctr Dept Agr & Forrest Engn Res Grp AgroIct & Precis Agr Lieida Spain

the detection of the type of soil surface where a robotic vehicle is navigating on is an important issue for performing several agricultural tasks. Satisfactory results in activities such as seeding, plowing, fertilizing, among others depend on a correct identification of the vehicle environment, specially its contact interface with the ground. In the this work, the implementation of a supervised image texture classifier to recognize five different classes of typical agricultural soil surfaces is presented and analysed. the sensing device is the Microsoft Kinect for Windows V2, which allows to acquire RGB, IR and depth data. Only IR and depth data were used for the processing, since color information becomes unreliable under different illumination conditions. Two data acquisition modes allowed to validate and to apply the system in real operation conditions. the accuracy of the classifier was assessed under different configuration parameters, obtaining up to 93 percent of success rate, in ideal conditions. Real field conditions were simulated by placing the sensor over a moving wagon, obtaining up to 86 percent of success rate, showing in this way the usability of a low cost sensor such as the Kinect V2 for agricultural robotics. (C) 2016, IFAC (international Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Agricultural robotics terrain classification terramechanics modelling pattern recognition

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