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

共 15616 条记录，以下是4421-4430 订阅

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Impact of Camera vibration Frequencies on image Noise for Unmanned Aerial System Applications

Impact of Camera Vibration Frequencies on Image Noise for Un...

引用

2018 IEEE Southeastcon, Southeastcon 2018

作者： Huang, Wei-Hao Daniel Otero, Luis Otero, Carlos E. Moyou, Marka Department of Engineering Systems Florida Institute of Technology MelbourneFL United States Department of Electrical and Computer Engineering Florida Institute of Technology MelbourneFL United States

ISBN: (纸本)9781538661338

In the transportation systems engineering field, there is a fast growing interest to use small unmanned aerial systems (UAS) for structural inspections. Of particular importance is the development of image processing algorithms to process UAS collected data for transportation infrastructure (e.g., bridges) defect detection/classification purposes. Results from preliminary experiments using image data collected with a UAS have shown the presence of significant image noise, which negatively impacts the efficiency of algorithms to detect/classify structural defects. This research study presents an ongoing effort to understand the relationship between UAS camera vibrations to image noise. Ultimately, the objective is to identify maximum camera vibration frequencies that will result in acceptable image noise levels for effective detection and classification of defects. © 2018 IEEE.

关键词： Cameras

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Automatic Pavement Crack Detection using Multi-Scale image & Neighborhoods Information

Automatic Pavement Crack Detection using Multi-Scale Image &...

引用

International conference on Mechatronics, Robotics and systems Engineering (MoRSE)

作者： Taiki Komori Kousuke Matsushima Osamu Takahashi Advanced Engineering Course National Institute of Technology Kurume College Fukuoka Japan National Institute of Technology Kurume College Fukuoka Japan Nagaoka University of Technology Niigata Japan

Pavement cracks are dangerous because they can cause accidents such as tire punctures, slips, and collapses. Therefore, it is necessary to repair them properly. In recent years, various crack detection methods using pavement images have been proposed. However, in many cases, there are problems with accuracy and processing time. In this paper, we propose a new crack detection method using multi-scale image and neighborhood information. Experimental results show that the proposed method is superior to the most advanced crack detection methods in both accuracy and processing time.

关键词： Probability Roads image generation Testing Clustering algorithms image segmentation Training

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Nonlinear Compensation in 32 Gbauds PM-16QAM and PM-QPSK Coherent Optical systems

Nonlinear Compensation in 32 Gbauds PM-16QAM and PM-QPSK Coh...

引用

International conference on image and Signal processing and their Applications (ISPA)

作者： Hadjadji Narimane Hamdi Rachid dept. of electronic and Telecommunications University 8 May 1945 Guelma Algeria

ISBN: (纸本)9781728131573

The huge capacity of the coherent optical systems is restricted by fiber nonlinearity. Using digital signal processing algorithms has the opportunity to reduce this limitation. In this work, we investigate the compensation of fiber nonlinearities by digital backpropagation in both Polarization-division-multiplexed 16-level quadrature amplitude modulation system and polarization multiplexed 0.3 return-to-zero quadrature phase-shift keying system. The comparison is done at the same symbol rate. The systems performances are measured in terms of bit error rate, optical signal noise ratio penalty, and the maximum reach. The polarization multiplexed 0.3 return-to-zero quadrature phase-shift keying system performs better by increased sensitivity and the maximum transmission distance.

关键词： Coherent optical systems Nonlinear effects Manakov equation Format modulation Digital signal processing Digital signal processing algorithm of digital signal process Bit error rate Optical systems gap distance nonlinear effect compensated Polarization Quadrature phase shift keying nonlinearity return-to-zero quadrature phase MULTIPLEXOR

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Real-time video thresholding using evolutionary techniques and cross entropy 11

Real-time video thresholding using evolutionary techniques a...

引用

11th IEEE International conference on Evolving and Adaptive Intelligent systems (EAIS)

作者： Hinojosa, Salvador Oliva, Diego Cuevas, Erik Perez-Cisneros, Marco Pajares, Gonzalo Univ Complutense Madrid Fac Informat Dept Ingn Software & Inteligencia Artificial Madrid Spain Univ Guadalajara Div Elect & Comp CUCEI Guadalajara Jalisco Mexico

ISBN: (纸本)9781538613764

Evolutionary algorithms (EAs) are present in most areas of science and engineering where difficult problems arise. However, EAs are often applied to design problems where the speed is not a crucial factor. This tendency has lead EAs to be excluded from real-time applications due to its iterative nature. image processing has benefited from EAs on many off-line applications, but little research has been made for real-time image processing problems. This paper presents the evaluation of EAs applied to the thresholding of a stream of images in real-time. Results indicate that Differential Evolution (DE) can be modified to achieve real-time performance on a single core implementation without any form of parallelization. These circumstances indicate that the performance can be further improved with multi-core implementations or GPU parallelization.

关键词： evolutive algorithms image processing thresholding real-time

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Machine Learning based image processing Techniques for Satellite image Analysis -A Survey

Machine Learning based Image Processing Techniques for Satel...

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International conference on Machine Learning, Big Data, Cloud and Parallel Computing (COMITCon)

作者： Anju Asokan J Anitha ECE Department Karunya Institute of Technology and Sciences Coimbatore India

ISBN: (纸本)9781728102122

This paper presents the detailed comparison of various image processing techniques for analyzing satellite images. The satellite images are large in size, acquired from long distances and are affected by noise and other environmental conditions. Hence it is necessary to process them so that they can be used by the researchers for analysis. Satellite images are widely used in many real time applications such as in agriculture land detection, navigation and in geographical information systems. In this paper, a review of some popular machine learning based image processing techniques is presented. Also a detailed comparison of various techniques is performed. Limitations in each image processing method are also described. In addition to reviewing of different methods, different metrics for performance evaluation in each of the image processing areas is studied.

关键词： Feature extraction Satellites image segmentation Classification algorithms image enhancement image fusion

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Optimization of image Filtering Architectures for Real Time systems 7

Optimization of Image Filtering Architectures for Real Time ...

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7th IEEE International conference on Communication and Signal processing (IEEE ICCSP)

作者： Jakkula, Manoj Kumar Pavan, A. Sai Narayan, Gautam VIT Sch Elect Engn SENSE Vellore Tamil Nadu India

ISBN: (纸本)9781538635216

In many image and video processing algorithms, pre-processing filters are the first and most important step. These filters reduce the noise present in the images, preserving the required information depending on the action performed. Due to increasing demands for real time processing systems, the traditional software solutions cannot be chosen. In this paper, we are introducing a new hardware architecture for image processing filters, which are optimized to increase the speed of processing, which is vital for real time systems. The decision based algorithm used for optimizing the median filter helps in avoiding corruption of original pixels and the hardware optimization used for the Gaussian filter reduces the required computations, making it faster. The proposed architecture is simulated in ModelSim and the simulation results are presented.

关键词： Median filter Decision based algorithm Gaussian filter Hardware complexity Reduced computations Real time systems Salt and pepper noise gaussian noise

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A New Conical Helix Antenna based on MEMS Technology using Genetic algorithms

A New Conical Helix Antenna based on MEMS Technology using G...

引用

International conference on image and Signal processing and their Applications (ISPA)

作者： M. Chetioui A. Boudkhil M. Damou N. Benahmed Laboratory of Telecommunications University of Abou-Bekr Belkaid Tlemcen Algeria Laboratory of Tech of Communications University of Dr. Tahar Molay Saida Algeria

ISBN: (纸本)9781728131573

The manufacturing of Micro-Electromechanical systems (MEMS) antennas has recently outperformed major hurdles by reducing the long and expensive development cycles due to adequate Computer Aided Design (CAD) equipments with advanced optimization methods to address the special need for a new class of terahertz (THz) antennas, and model accurately the physical behavior of such three dimensional (3D) micro-devices. In this paper a new design of a highly miniaturized MEMS conical helix antenna modeled by High Frequency Structure Simulator (HFSS) based on Genetic algorithms (GA), is proposed for THz wireless systems to present very low return losses of less than -20dB to -70dB and excellent voltage standing wave ratios of less than 1.20 to 1.00 for a wide frequency band ranging from 3.5 to 4.5 THz, resulting in excellent electromagnetic response and good directivity due to the high geometrical accuracy achieved using effective automatic techniques to rectify various tunable parameters embedded in silicon platform divided into helix variables and feeding line characteristics.

关键词： Micro-electromechanical systems (MEMS) technology THz applications Wideband antenna Helix antenna 3D HFSS Genetic algorithms Genetic Algorithm (GA) Conical helix Microelectromechanical systems broadband antennas ANTENNA terahertz Standing wave ratios geometric accuracy RETURN LOSS updated design Helical antennas antennae

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Improvement of Edge-Tracking Methods using Genetic Algorithm and Neural Network

Improvement of Edge-Tracking Methods using Genetic Algorithm...

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International conference of Signal processing and Intelligent systems (ICSPIS)

作者： Sajjad Ghazanfari Shabankareh Saeid Ghazanfari Shabankareh Faculty of Electrical Engineering Islamic Azad University Shiraz Iran Faculty of Science and Technology Aix-Marseille University Marseille France

ISBN: (数字)9781728153506

ISBN: (纸本)9781728153513

One of the most basic and important operations in the field of image processing is image extraction and detection. Edge recognition is very important for image clarity and image segmentation. The importance of edge detection is that the human eye can recognizes the existence of different objects by observing the edges. So it makes sense to do edge detection before interpreting images in automated systems. Edges are points in the image where the two pixels are two different values, or two values very large in numerical value. It can be said that one of the goals of edge reduction in data size in images is to preserve the original structure and shape of the images. Editing has various applications, including object recognition, segmentation and image coding, in a variety of medical images. One of the problems we encounter when editing images has noises. In this paper, a combination of several standard edge- matching algorithms, neural network and multi-objective genetic algorithm NonDominated Sorting Genetic Algorithm (NSGA-II) is used to edge detection. In the proposed method, we give the standard multiedge finder to a forward propagating (FP) neural network as input. A multi-objective genetic algorithm with Non- Dominated Sorting Genetic Algorithm (NSGA-II was used to select the number of edge detectors to access the neural network and to select the most accurate ones. The genetic algorithm selects the least accurate number of edge detectors to enter the neural network. To evaluate the proposed method, TP, TN, FP, FN criteria were used to compare with other methods. Finally, by comparing the results obtained on different images using existing methods and the proposed method it is observed that the proposed method has better accuracy in detecting the edge of noise images.

关键词： image edge detection Detectors Signal processing algorithms Genetic algorithms Biological neural networks Sociology

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A system for image acquisition and processing operating in the visible and the IR bands 2019

A system for image acquisition and processing operating in t...

引用

Proceedings of the 13th International conference on Distributed Smart Cameras

作者： J. A. Leñero-Bardallo J. Bernabéu-Wittel J. Ceballos-Cáceres Á. Rodríguez-Vázquez Inst. Microelectrónica de Sevilla (IMSE-CNM) CSIC-Univ. Sevilla (Spain) Hospital Virgen de Rocío Sevilla (Spain)

ISBN: (纸本)9781450371896

This demo displays an autonomous image acquisition and processing system that operates simultaneously with two image sensors either in the visible and the Long Wave Infrared Band (LWIR), inside the Infrared (IR) band. The entire system is controlled a Raspberry Pi board that allows to easily program image processing algorithms to process the images acquired with each sensor. It is a competitive alternative to conventional commercial closed systems with infrared cameras. The proposed imaging system can be easily adapted to different operation scenarios by adding new peripherals, sensors and full custom image processing algorithms.

关键词： image processing IR camera Raspberry Pi Camera interface Multi-spectral imaging

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Machine vision Based Weight Prediction for Flatfish 18

Machine Vision Based Weight Prediction for Flatfish

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18th International conference on Control, Automation and systems (ICCAS)

作者： Hwang, K. H. Choi, J. W. Pusan Natl Univ Sch Mech Engn Busan 46241 South Korea

ISBN: (纸本)9788993215151

In fisheries industry, flatfish accounts for about half of the domestic fish production and is a specie with active aquaculture activities. As flatfish grows, classification according to the size should be periodically carried out for efficient growth. In this paper, the correlation between area and weight of flatfish required for classification algorithms using machine vision is derived. 120 simulations are performed using flatfish models and the area is obtained through image processing. In image processing process, the area of flatfish model is calculated using a reference square known in size. The weight of actual fish corresponding to the length of the model is obtained using the reference equation. Then, regression analysis is performed to derive the interpolation of linear and power equations which show correlation between area and weight of the flatfish.

关键词： Machine vision Regression analysis Parameter estimation image processing

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