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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems III"

共 14631 条记录，以下是4951-4960 订阅

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IMPROVEMENT OF LINKED PYRAMID SEGMENTATION SCHEME WITH VARIABLE WEIGHTING FUNCTION.

IMPROVEMENT OF LINKED PYRAMID SEGMENTATION SCHEME WITH VARIA...

引用

conference Proceedings - 28th Midwest Symposium on Circuits and systems.

作者： Sethi, A.S. Ahmadi, M. Univ of Windsor Windsor Ont Can Univ of Windsor Windsor Ont Can

Machine extraction of meaningful features from the digitized representation of an image (picture, scene etc. ) is of great interest to investigators working in such diverse fields as Robotic Vision, Scene Analysis, Pattern Recognition, and Automatic part identification in manufacturing processes. In this paper the authors describe their algorithms for implementing the linked pyramid segmentation scheme and a suggested improvement on it through the use of a variable weighting function and preprocessing the input image. Results reported here were obtained on images digitized to a spatial resolution of 256 multiplied by 256 pixel squared. The results of the improved algorithm are superior to the earlier ones.

关键词： image processing

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In-factory calibration of multiocular camera systems

In-factory calibration of multiocular camera systems

引用

conference on Optical Metrology in Production Engineering

作者： Krüger, L Wöhler, C Würz-Wessel, A Stein, F DaimlerChrysler Res & Technol D-89013 Ulm Germany

ISBN: (纸本)081945379X

A complete framework for automatic calibration of camera systems with an arbitrary number of image sensors is presented. This new approach is superior to other methods in that it obtains both the internal and external parameters of camera systems with arbitrary resolutions, focal lengths, pixel sizes, positions and orientations from calibration rigs printed on paper. The only requirement on the placement of the cameras is an overlapping field of view. Although the basic algorithms are suitable for a very wide range of camera models (including OmniView and fish eye lenses) we concentrate on the camera model by Bouguet (http://***/bouguetj/). The most important part of the calibration process is the search for the calibration rig, a checkerboard. Our approach is based on the topological analysis of the corner candidates. It is suitable for a wide range of sensors, including OmniView cameras, which is demonstrated by finding the rig in images of such a camera. The internal calibration of each camera is performed as proposed by Bouguet, although this may be replaced with a different model. The calibration of all cameras into a common coordinate system is an optimization process on the spatial coordinates of the calibration rig. This approach shows significant advantages compared to the method of Bouguet, esp. for cameras with a large field of view. A comparison of our automatic system with the camera calibration toolbox for MATLAB, which contains an implementation of the Bouguet calibration, shows its increased accuracy compared to the manual approach.

关键词： Cameras Calibration Imaging systems Distortion Transform theory image processing Detection and tracking algorithms MATLAB Sensors image sensors

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Design of Unified Support Vector Machine Circuit for Pedestrians and Cars Detection

Design of Unified Support Vector Machine Circuit for Pedestr...

引用

10th IEEE International New Circuits and systems conference (NEWCAS)

作者： Kim, Soojin Lee, Seonyoung Min, Kyoungwon Cho, Kyeongsoon Hankuk Univ Foreign Studies Dept Elect & Informat Engn Yongin South Korea Korea Elect Technol Inst SoC Platform Res Ctr Sungnam South Korea

ISBN: (纸本)9781467308595

This paper describes the design of unified support vector machine circuit for pedestrians and cars detection. By unifying the algorithms and architectures of linear and nonlinear SVM classifications, the proposed circuit can support both linear and non-linear classifications very efficiently in terms of circuit size and performance. The circuit size is minimized by sharing most of the resources required in the computation for both classification types. Parallel architecture with pipeline is adopted to accelerate the processing speed to handle a large amount of operations for real-time processing. 48x96 and 64x64 sliding windows with 6 window strides are used to detect pedestrians and cars, respectively. The synthesized circuit using 65nm standard cell library consists of 848,349 gates and its maximum operating frequency is 435MHz. The circuit can process 91.9 640x480 image frames per second assuming three cameras equipped on front, right and left side positions of the vehicle.

关键词： Pedestrians Cars Support Vector Network maximum operating frequency ARCHITECTURE processing SPEED Building construction pipeline Linear

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MEMS Performance Challenges - Packaging and Shock Tests

MEMS Performance Challenges - Packaging and Shock Tests

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conference on Micro- and Nanotechnology Sensors, systems, and Applications iii

作者： Chang, Jiyoung Yang, Chen Zhang, Bin Lin, Liwei Univ Calif Berkeley Berkeley Sensor & Actuator Ctr Berkeley CA 94720 USA

ISBN: (纸本)9780819486059

This paper describes recent advances in the MEMS performance challenges with emphases on packaging and shock tests. In the packaging area, metal to metal bonding processes have been developed to overcome limitations of the glass frit bonding by means of two specific methods: (1) pre-reflow of solder for enhanced bonding adhesion, and (2) the insertion of thin metal layer between parent metal bonding materials. In the shock test area, multi-scale analysis for a MEMS package system has been developed with experimental verifications to investigate dynamic responses under drop-shock tests. Structural deformation and stress distribution data are extracted and predicted for device fracture and in-operation stiction analyses for micro mechanical components in various MEMS sensors, including accelerometers and gyroscopes.

关键词： Microelectromechanical systems Metals Aluminum Packaging Tin Interfaces Semiconducting wafers Glasses image processing Sensors

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Thorax Disease Classification Based on the Convolutional Network SqueezeNet 12

Thorax Disease Classification Based on the Convolutional Net...

引用

12th IEEE International conference on Intelligent Data Acquisition and Advanced Computing systems: Technology and Applications, IDAACS 2023

作者： Avanzato, Roberta Beritelli, Francesco University of Catania Dieei Catania95125 Italy

ISBN: (纸本)9798350358056

Chest radiography allows a detailed inspection of a patient's thorax via an imaging modality, but requires specialized training for proper interpretation. With the advent of high performance general purpose image analysis and computer vision algorithms, the accurate automated analysis of chest radiographs is becoming increasingly of interest to researchers. In this paper, we propose a classification algorithm distinguishing between chest radiographs performed on people with or without lung disease. The dataset used as the input to the SqueezeNet neural network is Chest X-ray. The only pre-processing phase applied to the dataset is the resize to 224×224 and the conversion to grayscale. The accuracy percentage obtained during the network testing phase is 94%. © 2023 IEEE.

关键词： computer vision Convolutional neural network deep learning healthcare image processing

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Human-in-the-Loop Extension to Stream Classification for Labeling of Low Altitude Drone imagery

Human-in-the-Loop Extension to Stream Classification for Lab...

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conference on Autonomous systems - Sensors, processing, and Security for Vehicles and Infrastructure

作者： Schulz, Jeffrey Buck, Andrew R. Anderson, Derek T. Keller, James M. Scott, Grant J. Luke, Robert H., iii Univ Missouri Dept Elect Engn & Comp Sci Columbia MO 65211 USA US Army DEVCOM C5ISR Ctr Ft Belvoir VA USA

ISBN: (数字)9781510643345

ISBN: (纸本)9781510643345

In general, there is a severe demand for, and shortage of, large accurately labeled datasets to train supervised machine learning (ML) algorithms for domains like smart cars and unmanned aerial systems (UAS). This impacts a number of real-world problems from standing up ML on niche domains to ML performance in/across different environments. Herein, we consider the task of efficiently, meaning requiring the least amount of human intervention possible, converting large UAS data collections over a shared geospatial area into accurately labeled training data. Herein, we take a human-in-the-loop (HITL) approach that is based on coupling active learning and self-supervised learning to efficiently label low altitude UAS imagery for the goal of training ML algorithms for underlying tasks like detection, localization, and tracking. Specifically, we propose an extension to our stream classification algorithm StreamSoNG based on human intervention. We also extend StreamSoNG to rely on a second and initially more mature, but assumed incomplete, ML classifier. Herein, we use the Unreal Engine to simulate realistic ray-traced low altitude UAS data and facilitate algorithmic performance analysis in a controlled fashion. While our results are preliminary, they suggest that this approach is a good trade off between not overloading a human operator and circumventing fundamental stream classification algorithm limitations.

关键词： active learning self-supervised learning human-in-the-loop HITL drone unmanned aerial vehicle unmanned aerial system object detection Unreal Engine stream classification StreamSoNG

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Performance Improvement of Segmentation-Based Depth Representation in 3D imagery by Region Merging

Performance Improvement of Segmentation-Based Depth Represen...

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5th International conference on Advanced Technologies for Communications (ATC)

作者： De Raffaele, Clifford Camilleri, Kenneth P. Farrugia, Reuben A. Debono, Carl J. Univ Malta Dept Syst & Control Engn Msida Malta

ISBN: (纸本)9781467343527;9781467343510

The feasible implementation of immersive 3D video systems entails the need for a substantial reduction in the amount of image information necessary for representation. Multiview image rendering algorithms based on depth data have radically reduced the number of images required to reconstruct a 3D scene. Nonetheless, the compression of depth maps still poses several challenges due to the particular nature and characteristics of the data. To this end, this paper outlines a depth representation technique, developed in our earlier work, that exploits the correlation intrinsically present between color intensity and depth images capturing a natural scene. In this technique, a segmentation-based algorithm that is backwards compatible with conventional video coding systems is implemented. The effectiveness of our previous technique is enhanced in this contribution by a region merging process on the segmented regions, which results in a decrease in the amount of information necessary for transmission or storage of multiview image data by a factor of 20.5 with respect to the reference H. 264/AVC coding methodology. This is furthermore achieved whilst maintaining a 3D image reconstruction and viewing quality which is quasi identical to the referenced approach.

关键词： 3D scene processing depth-map representation multiview images segmentation-based video coding

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Subjective Evaluation of Compressed SAR images using JPEG and HEVC intra coding: Sometimes, Compression Improves Usability 15

Subjective Evaluation of Compressed SAR Images using JPEG an...

引用

15th European Radar conference (EuRAD)

作者： Pestel-Schiller, Ulrike Ostermann, Joern Leibniz Univ Hannover Inst Informat Verarbeitung Hannover Germany

ISBN: (纸本)9782874870538

Human evaluation of SAR is time-consuming and costly. Typically it requires the indirect usability-based assessment of SAR system components or SAR systems from which the images arose. We investigate an assessment system which aims at finding digital signal processing algorithms to simulate, complement and partly replace the human evaluation of SAR images. To better understand the human evaluation, expert SAR interpreters have been asked to solve tasks on SAR images whose different image qualities result from a specific SAR system by varying the parameter settings of one SAR system component. The SAR system component investigated first is the coding system where the spatial and the amplitude resolution are fundamental parameters. In this paper, we describe first results of a human evaluation with expert interpreters where the two coding standards JPEG and HEVC intra coding were evaluated at different spatial resolutions and data rates. The SAR image quality preferred to work with was identified by the interpreters.

关键词： image quality synthetic aperture radar data compression image coding

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A Study on Smart Parking Solutions Using IoT

A Study on Smart Parking Solutions Using IoT

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International conference on Intelligent Sustainable systems (ICISS)

作者： Chandana, M. Aniruddh, M. C. Fathima, Anam Chandan, G. Kumari, Chaya H. A. Vidyavardhaka Coll Engn CSE Dept Mysuru India

ISBN: (纸本)9781538677995

With the evolution of Internet of things and the popularity of concepts of smart cities, it is now possible to achieve these concepts and implement them in reality. Lots of efforts are being put in to increase the productivity and reliability of infrastructures in urban city space. Key problems of the urban cities are traffic congestion, limited availability of parking spaces and time wasted in search of these limited parking spaces. These problems can be addressed using IoT systems. In this paper we have conducted a survey on the existing parking systems and have explained the main methodology used in each of the existing systems mentioned. Besides the main findings from the survey, with our engineering insights we have also come up with the solution that can efficiently be used for smart parking to overcome the disadvantages that we have discovered in the existing systems. Lastly, we describe the architecture and functionality of our solution using IoT.

关键词： Internet of Things image processing Smart Parking Smart City Cloud of Things Open CV algorithms GSM module RFID tags HSV images Cameras Arduino boards

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Feature level sensor fusion

Feature level sensor fusion

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conference on Sensor Fusion - Architectures, algorithms, and Applications iii

作者： Peli, T Young, M Knox, R Ellis, K Bennett, F Atlantic Aerosp Elect Corp Waltham MA 02154 USA

ISBN: (纸本)0819431931

This paper describes two practical fusion techniques (hybrid fusion and cued fusion) for automatic target cueing that combine features derived from each sensor data at the object-level. In the hybrid fusion method each of the input sensor data is prescreened (i.e. Automatic Target Cueing (ATC) is performed) before the fusion stage. The cued fusion method assumes that one of the sensors is designated as a primary sensor, and thus ATC is only applied to its input data. If one of the sensors exhibits a higher Pd and/or a lower false alarm rate, it can be selected as the primary sensor, However, if the ground coverage can be segmented to regions in which one of the sensors is known to exhibit better performance, then the cued fusion can be applied locally/adaptively by switching the choice of a primary sensor. Otherwise, the cued fusion is applied both ways (each sensor as primary) and the outputs of each cued mode are combined. Both fusion approaches use a back-end discrimination stage that is applied to a combined feature vector to reduce false alarms. The two fusion processes were applied to spectral and radar sensor data and were shown to provide substantial False alarm reduction. The approaches are easily extendable to more than two sensors.

关键词： Sensors image fusion Data fusion Synthetic aperture radar Target detection Feature extraction Sensor fusion image processing Infrared sensors Target recognition

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