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Research and Implement for Vehicle License Plate Recognition Based on improved BP Network

Research and Implement for Vehicle License Plate Recognition...

2010 International Conference on computer and Communication Technologies in Agriculture engineering(计算机与通信技术在农业工程国际会议 CCTAE 2010)

作者： Zhiwen WANG Shaozi LI Department of Computer and Engineering Guangxi University of Technology Liuzhou 545006 China Cognitive Science Department of Xiamen University Xiamen 361005 China

In this article, BP network learning algorithm is improved by using momentum and genetic algorithm after analyzing the defects of the BP network learning algorithm. So the convergence rate of BP network is speeded up greatly. The vehicle license plate character image is segmented and feature is extracted by edge detection using sobel operator. And then license plates of cars are automatically recognized by using improved BP neural network. This algorithm can improve the speed and accuracy for the automatic identification of the license plates of vehicle.

关键词： BP network momentum genetic algorithm license plate location license plate character segmentation license plate character recognition

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Message Broker Using Asynchronous Method Invocation in Web Service and Its Evaluation

Message Broker Using Asynchronous Method Invocation in Web S...

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IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW

作者： Fan Bai Wang Tao Interactive Systems and Interaction Design Department of Computer Science and Applied Cognitive Sciences Faculty of Engineering University of Duisburg-Essen Germany

Event driven architectures are widely used in numerous software applications, for instance in GUI focused software. Currently most event driven softwares are applied merely in local environment. If we need to use event driven architecture in a distributed environment, there are not too many candidates to choose from. Thus, although there are a number of techniques which support the event notification in distributed environments, such as Comet technique and ESB platform, we still require a light-weight and user-friendly system, free from platform and protocol, to support event notification in the Web environment. In this paper we implemented a middleware which supports event subscription and publication based on Web Service. Through the evaluations afterwards we finally found out the limitations of our current system and we offered our suggestions accordingly.

关键词： Web services Application software Protocols Web server Java computer architecture Graphical user interfaces Subscriptions Software testing Interactive systems

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Balance (bioengineering approaches for lifestyle activity and nutrition continuous engagement): Developing new technology for monitoring energy balance in real time

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Journal of Diabetes science and Technology 2010年第2期4卷 429-434页

作者： Hughes, Deonna C. Andrew, Adrienne Denning, Tamara Hurvitz, Philip Lester, Jonathan Beresford, Shirley Borriello, Gaetano Bruemmer, Barbara Moudon, Anne Vernez Duncan, Glen E. Nutritional Sciences Program Department of Epidemiology University of Washington Seattle WA 98195 Box 353410 United States Department of Computer Science and Engineering University of Washington Seattle WA United States College of Built Environments University of Washington Seattle WA United States Department of Electrical Engineering University of Washington Seattle WA United States

Methods that measure energy balance accurately in real time represent promising avenues to address the obesity epidemic. We developed an electronic food diary on a mobile phone that includes an energy balance visualization and computes and displays the difference between energy intake from food entries and energy expenditure from a multiple-sensor device that provides objective estimates of energy expenditure in real time. A geographic information system dataset containing locations associated with activity and eating episodes is integrated with an ArcPad mapping application on the phone to provide users with a visual display of food sources and locations associated with physical activity within their proximal environment. This innovative tool captures peoples' movement through space and time under free-living conditions and could potentially have many health-related applications in the future. © Diabetes Technology Society.

关键词： Activity Energy balance Food diary Real-time assessment Self-monitoring

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Computationally effective stereovision SLAM

Computationally effective stereovision SLAM

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IEEE International Conference on Imaging Systems and Techniques

作者： Nalpantidis, Lazaros Sirakoulis, Georgios Ch. Carbone, Andrea Gasteratos, Antonios Laboratory of Robotics and Automation Department of Production and Management Engineering Democritus University of Thrace University Campus Kimmeria GR-67100 Xanthi Greece Laboratory of Electronics Department of Electrical and Computer Engineering Democritus University of Thrace University Campus Kimmeria GR-67100 Xanthi Greece Autoagent Laboratory for Cognitive Robotics Department of Computer and Systems Science University of Rome La Sapienza Via Ariosto 25 00185 Rome Italy

ISBN: (纸本)9781424464944

In this paper a visual Simultaneous Localization and Mapping (SLAM) algorithm suitable for indoor area measurement applications is proposed. The algorithm is focused on computational effectiveness. The only sensor used is a stereo camera placed onboard a moving robot. The algorithm processes the acquired images calculating the depth of the scenery, detecting occupied areas and progressively building a map of the environment. The stereo vision-based SLAM algorithm embodies a custom-tailored stereo correspondence algorithm, the robust scale and rotation invariant feature detection and matching Speeded Up Robust Features (SURF) method, a computationally effective v-disparity image calculation scheme, a novel map-merging module, as well as a sophisticated Cellular Automata (CA)-based enhancement stage. The proposed algorithm is suitable for autonomously mapping and measuring indoor areas using robots. The algorithm is presented and experimental results for self-captured image sets are provided and analyzed. © 2010 IEEE.

关键词： Stereo vision

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The story of a single cell: Peeking into the semantics of spikes

The story of a single cell: Peeking into the semantics of sp...

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International Workshop on cognitive Information Processing (CIP)

作者： Roi Kliper Thomas Serre Daphna Weinshall Israel Nelkenz School of Computer Science and Engineering Brown University Department of Cognitive and Linguistic Sciences Hebrew University of Jerusalem Jerusalem Jerusalem IL

Traditionally, the modeling of sensory neurons has focused on the characterization and/or the learning of input-output relations. Motivated by the view that different neurons impose different partitions on the stimulus space, we propose instead to learn the structure of the stimulus space, as imposed by the cell, by learning a cell specific distance function or kernel. Metaphorically speaking, this direction attempts to bypass the syntactic question of “how the cell speaks”, by focusing instead on the semantic and fundamental question of “what the cell says”. Here we consider neural data from both the inferotemporal cortex (ITC) and the prefrontal cortex (PFC) of macaque monkeys. We learn a cell-specific distance function over the stimulus space as induced by the cell response; the goal is to learn a function such that the distance between stimuli is large when the responses they evoke are very different, and small when the responses they evoke are similar. Our main result shows that after training, when given new stimuli, our ability to predict their similarity to previously seen stimuli is significantly improved. We attempt to exploit this ability to predict the response of the cell to a novel stimuli using KNN over the learnt distances. Furthermore, using our learned kernel we obtain a partitioning of the stimulus space which is more similar to the partition induced by the cell responses as reveled by low dimension embedding, and thus, are able in some of the cases to peek at the semantic partition induced by the cell.

关键词： Neurons Correlation Training Visualization Brain models Predictive models

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Hardware particle swarm optimization based on the attractive-repulsive scheme for embedded applications

Hardware particle swarm optimization based on the attractive...

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2010 International Conference on Reconfigurable Computing and FPGAs, ReConFig 2010

作者： Muñoz, Daniel M. Llanos, Carlos H. Dos S. Coelho, Leandro Ayala-Rincón, Mauricio Department of Mechanical Engineering Automation and Control Group/GRACO University of Brasilia Brasilia DF Brazil Industrial and Systems Engineering Graduate Program LAS/PPGPES Pontifical Catholic University of Parana Curitiba Parana Brazil Department of Computer Science and Mathematics University of Brasilia Brasilia DF Brazil

ISBN: (纸本)9780769543147

Particle Swarm Optimization (PSO) algorithms have been proposed to solve engineering problems that require to find an optimal point of operation. However, the PSO algorithm suffers from premature convergence and high elapsed time when solving multimodal and large scale engineering problems. This problem becomes an evident drawback for embedded applications in which the microcontrollers often operates at low computational capacity. This paper proposes a hardware implementation of a parallel self-adaptive PSO algorithm based on an attractive-repulsive scheme and using the efficient floating-point arithmetic which performs computations with large dynamic range and high precision. The parallel capabilities of the PSO are exploited by implementing parallel particles directly in hardware in order to decrease the running time. In addition, the attractive-repulsive technique avoids the premature convergence problem by self-adapting the swarm behavior according to its diversity. Synthesis and simulation results for benchmark test problems were performed, demonstrating the correctness of the proposed architectures. Finally, an elapsed time comparison between the hardware and software implementations shows the suitableness of the proposed architecture for embedded applications. © 2010 IEEE.

关键词： Global optimization

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PTZ camera assisted face acquisition, tracking & recognition

PTZ camera assisted face acquisition, tracking & recognition

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IEEE International Conference on Biometrics: Theory, Applications, and Systems (BTAS)

作者： Hyun-Cheol Choi Unsang Park Anil K. Jain Department of Brain and Cognitive Engineering Korea University Seoul South Korea Department of Computer Science and Engineering Michigan State University East Lansing MI USA

Face recognition systems typically have a rather short operating distance with standoff (distance between the camera and the subject) limited to 1~2 meters. When these systems are used to capture face images at a larger distance (5~10 m), the resulting images contain only a small number of pixels on the face region, resulting in a degradation in face recognition performance. To address this problem, we propose a camera system consisting of one PTZ camera and two static cameras to acquire high resolution face images up to a distance of 10 meters. We propose a novel camera calibration method based on the coaxial configuration between the static and PTZ cameras. We also use a linear prediction model and camera control to mitigate delays in image processing and mechanical camera motion. The proposed system has a larger standoff in face image acquisition and effectiveness in face recognition test. Experimental results on video data collected at a distance ranging from 5 to 10 meters of 20 different subjects as probe and 10,020 subjects as gallery shows 96.4% rank-1 identification accuracy of the proposed method compared to 0.1% rank-1 accuracy of the conventional camera system using a state-of-the-art matcher.

关键词： Cameras Face Face recognition Image resolution Calibration Accuracy

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Online visual vocabulary pruning using pairwise constraints

Online visual vocabulary pruning using pairwise constraints

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Conference on computer Vision and Pattern Recognition (CVPR)

作者： Pavan K. Mallapragada Rong Jin Anil K. Jain Department Computer Science and Engineering Michigan State University East Lansing MI USA Department Brain and Cognitive Engineering Korea University Seoul South Korea

Given a pair of images represented using bag-of-visual-words and a label corresponding to whether the images are “related”(must-link constraint) or “unrelated” (cannot-link constraint), we address the problem of selecting a subset of visual words that are salient in explaining the relation between the image pair. In particular, a subset of features is selected such that the distance computed using these features satisfies the given pairwise constraints. An efficient online feature selection algorithm is presented based on the dual-gradient descent approach. Side information in the form of pair-wise constraints is incorporated into the feature selection stage, providing the user with flexibility to use an unsupervised or semi-supervised algorithm at a later stage. Correlated subsets of visual words, usually resulting from hierarchical quantization process (called groups), are exploited to select a significantly smaller vocabulary. A group-LASSO regularizer is used to drive as many feature weights to zero as possible. We evaluate the quality of the pruned vocabulary by clustering the data using the resulting feature subset. Experiments on PASCAL VOC 2007 dataset using 5000 visual keywords, resulted in around 80% reduction in the number of keywords, with little or no loss in performance.

关键词： Vocabulary Clustering algorithms computer science Quantization Performance loss Prototypes Large-scale systems Image retrieval Scalability Partitioning algorithms

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PILL-ID: Matching and Retrieval of Drug Pill Imprint Images

PILL-ID: Matching and Retrieval of Drug Pill Imprint Images

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International Conference on Pattern Recognition

作者： Young-Beom Lee Unsang Park Anil K. Jain Department of Brain and Cognitive Engineering Korea University Seoul South Korea Department of Computer Science & Engineering Michigan State University East Lansing MI USA

ISBN: (纸本)9781424475421

Automatic illicit drug pill matching and retrieval is becoming an important problem due to an increase in the number of tablet type illicit drugs being circulated in our society. We propose an automatic method to match drug pill images based on the imprints appearing on the tablet. This will help identify the source and manufacturer of the illicit drugs. The feature vector extracted from tablet images is based on edge localization and invariant moments. Instead of storing a single template for each pill type, we generate multiple templates during the edge detection process. This circumvents the difficulties during matching due to variations in illumination and viewpoint. Experimental results using a set of real drug pill images (822 illicit drug pill images and 1,294 legal drug pill images) showed 76.74% (93.02%) rank one (rank-20) matching accuracy.

关键词： Drugs Image edge detection Feature extraction Shape Databases Law

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Research for Automatic Recognition for Vehicle Based on improved BP Network

Research for Automatic Recognition for Vehicle Based on impr...

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2010 International Conference on computer and Communication Technologies in Agriculture engineering(计算机与通信技术在农业工程国际会议 CCTAE 2010)

作者： Zhiwen WANG Shaozi LI Department of Computer and Engineering Guangxi University of Technology Liuzhou 545006 China Cognit Cognitive Science Department of Xiamen University Xiamen 361005 China

In this article, BP network learning algorithm is improved by using momentum and genetic algorithm after analyzing the defects of the BP network learning algorithm. Wavelet multi-scale edge detection is used to segment the vehicle image and extract the feature of the image. And then the features of moment invariants and improved BP neural network models are used to automatically recognize and classify the vehicle image. This algorithm can improve the speed and accuracy for the automatic identification and classification of the vehicle.

关键词： BP network momentum Genetic algorithm invariant Quadrature automatic recognition for vehicle

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