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检索条件"主题词=Detection and tracking algorithms"

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FAST WATERSHED algorithms - ANALYSIS AND EXTENSIONS

FAST WATERSHED ALGORITHMS - ANALYSIS AND EXTENSIONS

引用

Conference on Nonlinear Image Processing V

作者： DOBRIN, BP VIERO, T GABBOUJ, M TAMPERE UNIV TECHNOL SIGNAL PROC LABSF-33101 TAMPERE 10FINLAND

ISBN: (纸本)0819414751

Watershed transformation is used in morphological image segmentation. This transformation could be considered as a topographic region growing method. Recently, fast watershed algorithms have been proposed for general purpose computers. They are based on immersion simulations of the image surface, which is considered as a topographic relief. In such a model, the greylevel values of pixels stand for altitude values on the relief. In this paper, the operation of the present fast watershed algorithms is analyzed and a new extension is proposed. Drawbacks of the present algorithms are pointed out, studied, and illustrated with test images. These problems lead, in several cases, to a loss of information about image details and structures or even to unprocessed areas in the image. The new watershed algorithm overcomes these deficiencies and preserves more information about image details. The new algorithm is based on a split-and-merge scheme. It constantly monitors the presence of isolated areas during the immersion simulation, considering them as new catchment basins. Application of the split-and-merge watershed algorithm to marker-based image segmentation is discussed.

关键词： Image processing algorithms and systems Image segmentation Image processing Nonlinear image processing detection and tracking algorithms Floods Particles Raster graphics Computing systems Lead

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HIGH-PERFORMANCE REAL-TIME CLASSIFICATION PROCESSOR USING CONVENTIONAL AND NEURAL PROCESSING TECHNIQUES

HIGH-PERFORMANCE REAL-TIME CLASSIFICATION PROCESSOR USING CO...

引用

4th International Conference on Automatic Object Recognition

作者： SHEARS, R GEC MARCONI AVION LTD DIV SENSORSFUTURE SYST K205BASILDON SS14 3ELESSEXENGLAND

ISBN: (纸本)0819415383

Future systems must intelligently preprocess an increasingly large volume of sensor data in real time within the constraints of an airborne environment. A compact, flightworthy, real time sensor processor has been developed which can host both conventional and neural processing algorithms. This will support a wide range of applications including high performance target classification from high resolution infrared imagery. The architecture features software reconfigurability to support different processing tasks and modular upgrade potential. Accurate classification of ship imagery has been demonstrated, using real airborne trials data produced under a range of operating conditions. The system is currently continuing to undergo airborne trials.

关键词： Software development detection and tracking algorithms Video Digital signal processing Image classification Neural networks Video processing Algorithm development Sensors Computer architecture

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Wavelet packet based algorithm for identification of quasi-periodic signals

Wavelet packet based algorithm for identification of quasi-p...

引用

Conference on Wavelets - Applications in Signal and Image Processing IX

作者： Averbuch, AZ Kozlov, I Zheludev, VA Tel Aviv Univ Sch Comp Sci IL-69978 Tel Aviv Israel

ISBN: (纸本)0819441929

We present a generic approach that identifies and differentiates among signals for wide range of problems. Originally our algorithm was developed to detect the presence of a specific vehicle belonging to a certain class via the analysis of the acoustic signals emitted while it is moving. A crucial factor in having a successful detection (no false alarm) is to construct signatures built from characteristic features that enable to discriminate between the class of interest and the residual information such as background. We construct the signatures of certain classes by the distribution of the energies among blocks which consist of wavelet packet coefficients. We developed an efficient procedure for adaptive selection of the characteristic blocks. We modified the CART algorithm in order to utilize it to be a decision unit in our scheme. However, this technology, which has many algorithmic variations, can be used to solve a wide range of classification and detection problems which are based on acoustic processing and, more generally, for classification and detection of signals which have near-periodic structure. We present results of successful application of the properly modified algorithm to detection of early symptoms of arterial hypertension in children via real-time analysis of pulse signals.

关键词： Wavelets Signal detection Algorithm development Signal processing Acoustics Diagnostics Arteries Biomedical optics detection and tracking algorithms Fourier transforms

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Research on servo control system based on RBF-PID algorithm 9

Research on servo control system based on RBF-PID algorithm

引用

9th International Symposium on Sensors, Mechatronics, and Automation System, ISSMAS 2023

作者： Ren, Mingze Shi, Fuzhen Zhu, Zhifeng Zhengzhou Institute of Mechanical and Electrical Engineering Henan Province Zhengzhou450015 China

ISBN: (纸本)9781510672802

The servo of intelligent ammunition usually used brushless DC motor as the power source, and its control system was nonlinear, time-varying parameter and multi-variable coupling complex system. The traditional PID control algorithm had gradually failed to meet the high performance control requirements of the servo control system. In this paper, RBFPID algorithm combining RBF network and PID control was designed for the speed loop controller of the steering servo. The simulation results showed that the RBF-PID control algorithm achieved better control effect than the traditional PID control algorithm in dynamic response ability, steady-state accuracy of the system, follow-ability and robustness of the control system, etc. © 2024 SPIE.

关键词： Control systems Servomechanisms Device simulation detection and tracking algorithms Bismuth Modeling Computer simulations Resistance Transmission electron microscopy Radium

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Document image binarization based on texture analysis

Document image binarization based on texture analysis

引用

Document Recognition

作者： Liu, Ying Srihari, Sargur N. SUNY/Buffalo (United States)

ISBN: (纸本)081941476X

A new thresholding algorithm is presented to address strong noise, complex patterns, poor contrast, and variable modalities in gray-scale histograms. It is based on document image texture analysis. The algorithm consists of three steps. First candidate thresholds are produced from the gray scale histogram analysis. Then, texture features associated with each candidate threshold are computed from the corresponding run-length histogram. Finally, the optimal threshold is selected according to the goodness evaluation so that the most desirable document texture features are produced. Only one pass through an image is required for optimal threshold selection. The test set consisted of 9000 machine printed address blocks from an unconstrained U.S. mail stream. Over 99.6% of the images were visually well-binarized. In an objective test, a system run with 594 mail address blocks, which contains many difficult images, shows that an 8.1% higher character recognition rate was achieved, compared to that by a previous algorithm due to Otsu.

关键词： detection and tracking algorithms Image analysis Image segmentation Image processing Document image analysis Feature extraction Surface plasmons Visualization Image quality Optical character recognition

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Development and validation of the AFIT scene and sensor emulator for testing (ASSET) 28

Development and validation of the AFIT scene and sensor emul...

引用

28th Conference on Infrared Imaging Systems: Design, Analysis, Modeling, and Testing

作者： Young, Shannon R. Steward, Bryan J. Gross, Kevin C. Department of Engineering Physics Air Force Institute of Technology WPAFB OH United States

ISBN: (纸本)9781510608573

ASSET is a physics-based model used to generate synthetic data sets of wide field of view (WFOV) electro-optical and infrared (EO/IR) sensors with realistic radiometric properties, noise characteristics, and sensor artifacts. It was developed to meet the need for applications where precise knowledge of the underlying truth is required but is impractical to obtain for real sensors. For example, due to accelerating advances in imaging technology, the volume of data available from WFOV EO/IR sensors has drastically increased over the past several decades, and as a result, there is a need for fast, robust, automatic detection and tracking algorithms. Evaluation of these algorithms is difficult for objects that traverse a wide area (100-10,000 km) because obtaining accurate truth for the full object trajectory often requires costly instrumentation. Additionally, tracking and detection algorithms perform differently depending on factors such as the object kinematics, environment, and sensor configuration. A variety of truth data sets spanning these parameters are needed for thorough testing, which is often cost prohibitive. The use of synthetic data sets for algorithm development allows for full control of scene parameters with full knowledge of truth. However, in order for analysis using synthetic data to be meaningful, the data must be truly representative of real sensor collections. ASSET aims to provide a means of generating such representative data sets for WFOV sensors operating in the visible through thermal infrared. The work reported here describes the ASSET model, as well as provides validation results from comparisons to laboratory imagers and satellite data (e.g. Landsat-8). © 2017 COPYRIGHT SPIE.

关键词： Sensors Earth observing sensors Landsat Cameras Image sensors Algorithm development Data modeling Clouds Image resolution Visible radiation Automatic tracking detection and tracking algorithms Imaging technologies Infrared imaging Infrared radiation

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Recognition strategy for pantograph-arc based on ZOA-RBFNN

Recognition strategy for pantograph-arc based on ZOA-RBFNN

引用

2024 International Workshop on Automation, Control, and Communication Engineering, IWACCE 2024

作者： Kou, Haowen Ma, Yufang Jin, Fengyi Faulty of Electrical and Control Engineering Liaoning Technical University Liaoning Province Huludao125105 China

ISBN: (数字)9781510685420

ISBN: (纸本)9781510685413

The pantograph-catenary system, as a vital link in the energy supply chain of electrified railways, has a direct impact on the overall reliability of the railway system. The occurrence of pantograph arc not only affects the quality of power collection by locomotives but also poses significant safety concerns. Therefore, the quest for accurate and efficient methods to identify pantograph arcs is of paramount practical importance. This paper proposes a pantograph arc recognition strategy based on Zebra Optimization Algorithm (ZOA) optimized Radial Basis Function Neural Network (RBFNN). Four groups of current collection experiments were conducted under different operating conditions using a self-developed Pantograph arc experimental simulator;And based on the consideration of zero-rest phenomenon during arc occurrence, the collected current data was selected from the data of the middle half cycle of the power frequency for feature calculation. Principal Component Analysis (PCA) was used to screen the features with higher contribution rate as the recognition basis;Furthermore, the ZOA was used to optimize the RBFNN for training and learning the features of the four groups of experimental, the average test level of the model is 98.5%, and the overall level is above 98%.The testing results of the model verified the generalization feasibility of this strategy;Finally, the superiority of this strategy was demonstrated through comparison with optimization and testing results of other types of algorithms. © 2024 SPIE. All rights reserved.

关键词： Education and training Mathematical optimization Data modeling Principal component analysis detection and tracking algorithms Particle swarm optimization Electromagnetism Neural networks Carbon Performance modeling

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Handwritten text line detection based on vision transformer 7

Handwritten text line detection based on vision transformer

引用

7th International Conference on Advanced Electronic Materials, Computers, and Software Engineering, AEMCSE 2024

作者： Zhong, Kaihe School of Computing and Information Engineering Tianjin Normal University Tianjin300387 China

ISBN: (纸本)9781510681866

There are various challenges in text detection of handwritten document images, such as dense text, complex layout, and noise interference. In order to better detect handwritten text lines in document, this paper combines ViT with PAN++ network models, utilizes ViT's powerful image understanding ability, and combines pixel aggregation algorithms to propose the PAViT network. The improved network model can effectively address various challenges in document images, such as dense text, mixed print and handwriting, background noise, etc. It accurately detects handwritten text lines in document images and performs experiments on the SCUT-HCCDoc dataset, achieving good results. © 2024 SPIE.

关键词： detection and tracking algorithms Image segmentation Transformers Convolution Feature extraction Image processing Education and training Head Image fusion Visualization Document image analysis

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Track-to-track association and bias removal

Track-to-track association and bias removal

引用

14th Conference on Signal and Data Processing of Small Targets

作者： Stone, LD Williams, ML Tran, TM Metron Inc Reston VA 20190 USA

ISBN: (纸本)0819444782

This paper develops methods for associating two sets of sensor tracks in the presence of missing tracks and translation bias. Key results include (1) Extension of the Maximum A Posteriori Probability method of matching tracks to use feature information as well as kinematic information;(2) translation bias removal techniques that are computationally tractable for large numbers of tracks, and effective in the presence of missing tracks. These methods were evaluated by Monte Carlo simulation. The experimental results indicate that the Maximum A Posteriori Probability method with its adaptive threshold achieves close to its best performance for matching tracks without an additional threshold adjustment.

关键词： Sensors Target detection Monte Carlo methods Computer programming Fourier transforms Computer simulations detection and tracking algorithms Signal to noise ratio Kinematics Copper

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Comparison of edge detection methods using a prototype overlay calibration artifact

Comparison of edge detection methods using a prototype overl...

引用

Conference on Metrology, Inspection, and Process Control for Microlithography XV

作者： Silver, RM Jun, J Kornegay, E Morton, R Natl Inst Stand & Technol Gaithersburg MD 20899 USA

ISBN: (纸本)0819440302

Accurate overlay measurements rely on robust, repeatable, and accurate feature position determination. In our effort to develop traceable overlay standards we have examined a number of edge detection methods and the parameters which affect those measurements. The samples used in this study are a comprehensive set of prototype overlay wafer standards. The methods for determining the position of a feature generally rely on some determination of edges, and the resulting feature centerline can be significantly affected by the method of choice. We have compared cross-correlation, centroid, and edge-threshold methods as well as an integrated least squares method. This paper is focused on empirical results obtained through the measurement of relevant overlay targets and pitch specimens. The data presented in this paper was acquired using charge coupled device (CCD)-based arrays.

关键词： Semiconducting wafers Overlay metrology Calibration Silicon Edge detection Reticles Image processing Prototyping detection and tracking algorithms Standards development

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