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检索条件"任意字段=18th Image Processing: Algorithms and Systems Conference, IPAS 2020"

共 258 条记录，以下是141-150 订阅

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Grape Downy Mildew On-line Detection Based on Accurate image processing Method Preformed on Embedded Ambient Intelligence System 4th

Grape Downy Mildew On-line Detection Based on Accurate Image...

引用

4th International conference on Intelligent, Interactive systems and Applications, IISA2019

作者： Xu, Peifeng Jiang, Qiyou Zhao, Zhongying Yang, Ning Zhang, Rongbiao School of Electrical and Information Engineering Jiangsu University Zhenjiang212013 China Jiangsu Vocational College of Agriculture and Forestry Jurong212400 China

ISBN: (纸本)9783030343866

In this paper, an accurate and intelligent Grape Downy Mildew (GDM) detection method based on common image processing and artificial neural network (ANNs) is proposed. In view of the structure of grape leaves and the distribution characteristics of GDM on leaves, firstly, image processing is mainly to solve the extraction of downy mildew areas on leaves, which is mainly composed of gray-scale processing, gray-scale linear transformation and binarization, and the effects of different processing algorithms and parameters on the results are discussed. Secondly, an ANNs is used to reduce the interference of grape leaf vein on the spot area statistics. Finally, the hardware and software platform based on ARM9 integrated processor, Linux and QT is used to realize the system integration. Compared with the traditional detection method, the accuracy of this detection method can reach 97%, which is close to the accuracy of the human eye, which can be used as an ambient intelligence system in the vineyard inspection, automatic completion of grape GDM detection and grading. © 2020, Springer Nature Switzerland AG.

关键词： image processing

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image Noise Recognition Algorithm Based on Improved DenseNet 1

引用

18th Web Information systems and Applications conference (WISA)

作者： Huang, Mengxing Zeng, Lirong Zhang, Yu Li, Yuchun Ni, Zehao Wu, Di Feng, Siling Hainan Univ State Key Lab Marine Resource Utilizat South Chin Coll Informat Sci & Technol Haikou Hainan Peoples R China Hainan Univ Sch Comp Sci & Technol Haikou 570288 Hainan Peoples R China

ISBN: (数字)9783030875718

ISBN: (纸本)9783030875718;9783030875701

In the process of image generation or transmission, the image quality is often degraded due to the interference and influence of speckle noise, which will adversely affect the subsequent image processing. However, most of the existing Optical Coherence Tomography (OCT) image denoising methods usually only use part of the prior information of the OCT image, and ignore the changes in the texture and structure of the OCT image. there is often a problem that the network is too deep and the calculation complexity is too large. Aiming at this shortcoming, this paper proposes an improved deep convolutional neural network image denoising algorithm based on the original DenseNet algorithm idea. First, by constructing a speckle noise image data set, a series of preprocessing is performed on the input image data set, then the visual statistical feature map of the image is extracted, and finally the DenseNet network structure is improved for network training. the experimental results show that the improved DenseNet has better performance no matter compared with BM3D, which is recognized as the best denoising algorithm in the field of image denoising, or compared with DnCNN, an advanced image denoising algorithm in the field of deep learning.

关键词： OCT image Speckle noise image noise recognition DenseNet network

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Development of low-cost real-time driver drowsiness detection system using eye centre tracking and dynamic thresholding 18th

Development of low-cost real-time driver drowsiness detectio...

引用

Joint conferences on 18th International conference on Intelligent systems Design and Applications, ISDA 2018 and 10th World Congress on Nature and Biologically Inspired Computing , NaBIC 2018

作者： Khan, Fuzail Sharma, Sandeep Department of Electronics and Communication Engineering National Institute of Technology Karnataka Surathkal575025 India

ISBN: (纸本)9783030166564

One in every five vehicle accidents on the road today is caused simply due to driver fatigue. Fatigue or otherwise drowsiness, significantly reduces the concentration and vigilance of the driver thereby increasing the risk of inherent human error leading to injuries and fatalities. Hence, our primary motive being - to reduce road accidents using a non-intrusive image processing based alert system. In this regard, we have built a system that detects driver drowsiness by real time tracking and monitoring the pattern of the driver’s eyes. the stand alone system consists of 3 interconnected components - a processor, a camera and an alarm. After initial facial detection, the eyes are located, extracted and continuously monitored to check whether they are open or closed on the basis of a pixel-by-pixel method. When the eyes are seen to be closed for a certain amount of time, drowsiness is said to be detected and an alarm is issued accordingly to alert the driver and hence, prevent a casualty. © Springer Nature Switzerland AG 2020.

关键词： Real time systems

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CRIST900: A fully-labeled natural image dataset for multi-operator content aware image retargeting 18th

CRIST900: A fully-labeled natural image dataset for multi-op...

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Joint conferences on 18th International conference on Intelligent systems Design and Applications, ISDA 2018 and 10th World Congress on Nature and Biologically Inspired Computing , NaBIC 2018

作者： Abhayadev, M. Santha, T. Department of Computer Science Dr G R Damodaran College of Science CoimbatoreTamilnadu641014 India

ISBN: (纸本)9783030166564

A fully-labeled image dataset provides an exclusive resource for reproducible analysis, investigation inquiries and data analyses in different research computational fields like machine learning, computer vision and deep learning machine intelligence. this research paper present a large scale fully-labeled natural image dataset for Multi-Operator content aware image retargeting techniques. the image dataset is feely available for image processing research field. the current research natural image dataset entitled CRIST900, it include 900 natural images and uses for content aware image retargeting. the proposed CRIST is an image retargeting Multi-Operator method called Content Retargeting image reSizing Technique. the proposed image resizing method has three phases, image object boundary identification, the image objects feature importance visual saliency map generation and Multi-Operator techniques for efficient retargeting of image objects. the Multi-Operator retargeted image quality assessment was done by different subjective and objective image quality assessment matrices. the experimental result shows that the proposed approach can attain better result than the traditional methods and content aware state-of-the-art image retargeting techniques. the research dataset is publicly available at https://***/view/abhayadevmalayil/home. © Springer Nature Switzerland AG 2020.

关键词： image quality

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A low power reprogrammable parallel processing VLSI architecture for computation of B-spline based medical image processing system for fast characterization of tiny objects suspended in cellular fluid

A low power reprogrammable parallel processing VLSI architec...

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International conference on VLSI Design

作者： Sabyasachi Mondal Arijit De P.K. Biswas Department of Electronics and Electrical Communication Engineering Indian Institute of Technology Kharagpur West Bengal India

ISBN: (纸本)0769522645

In this paper a novel medical image processing system is discussed. the core of the system is developed using a 16-bit fixed-point parallel architecture B-spline signal processing system. the statistical measure of finite word length effect is analytically developed. A modified algorithm for the reduced hardware reprogrammable interpolator has been designed. Finally some suitable modification in the hardware is made to reduce the power consumption.

关键词： Parallel processing Very large scale integration Computer architecture Concurrent computing Spline Biomedical image processing Signal processing algorithms Hardware Parallel architectures Length measurement

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Real time precise position measurement based on low-cost CMOS image sensor: DSP implementation and sub-pixel measurement precision verification

Real time precise position measurement based on low-cost CMO...

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International conference on systems, Signals and image processing, IWSSIP

作者： Ondrej Pribula Jan Fischer Department of Measurement Faculty of Electrical Engineering Czech Technical University Prague Czech Republic

Construction of an embedded position measurement sensor based on the real-time image processing and a low-cost CMOS image sensor is presented in this work. Position measurement task is simplified with the use of assisted videometry concept - the target object is equipped with an additional marker (active or passive). An effective implementation of algorithm for the marker position estimation for Digital Signal Processor Blackfin ® is presented. Having realized a set of measurements in the real-world conditions it has been shown that achievable linearity of the position measurement in the short-range of ±7 pixels is about 1/52 of pixel with pixel-size dependent period of linearity error. Position measurement resolution is better than 1/200 of pixel.

关键词： Pixel Position measurement Signal processing algorithms Estimation image resolution Linearity

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Scheduling of image processing Using Anytime Algorithm for Real-time System

Scheduling of Image Processing Using Anytime Algorithm for R...

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International conference on Pattern Recognition

作者： W.W. Kywe D. Fujiwara K. Murakami Graduate School of Information Science and Technology Aichi Prefectural University Nagakute Aichi Japan

this paper proposes an adaptive scheduling method using anytime algorithm under such a condition that the processing time is restricted or is not enough. By using typical image processing procedure as an example, this paper discusses how to modify conventional image processing algorithms to anytime algorithmic image processing, modeling of time-precision function and an adaptive scheduling method to realize the maximum performance in the restricted time

关键词： image processing Scheduling algorithm Real time systems Adaptive scheduling Information science Error analysis Process planning Artificial intelligence image analysis Algorithm design and analysis

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A ringing metric to evaluate the quality of images restored using iterative deconvolution algorithms

A ringing metric to evaluate the quality of images restored ...

引用

IEEE International conference on systems Engineering

作者： M. Balasubramanian S.S. Iyengar J. Reynaud R.W. Beuerman Computer Science LSU USA Eye Centre LSUHSC USA Ophthalmology LSUHSC USA

Iterative deconvolution algorithms exhibit increased ringing artifacts at higher number of iterations. Quantitative image analysis techniques such as optical flow algorithms are sensitive to these artifacts. We propose to use an image quality metric to identify the terminal step of iterative restoration algorithms. Frequency based metrics have difficulties in distinguishing the ringing artifacts from the image features. Spatial analysis techniques require extensive processing making them unsuitable for real-time image quality measurement as needed in iterative image restoration. We propose a novel ringing metric using binary morphological operators and demonstrate the method on the images of random cotton fibers acquired using white light confocal microscope.

关键词： image restoration Deconvolution Iterative algorithms image analysis image quality Optical sensors image motion analysis Frequency Cotton Microscopy

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Application of non-iterative method in digital image restoration

Application of non-iterative method in digital image restora...

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International conference on systems, Signals and image processing, IWSSIP

作者： Igor Stojanovic Sofija Bogdanova Momcilo Bogdanov Faculty of Computer Science University Goce Delcev Stip Republic of Macedonia Faculty of Electrical Engineering & Computing UKIM Skopje Macedonia

A method for digital image restoration, based on the algorithm of Lagrange multipliers, has many practical applications. We apply the method to remove blur in an image caused by uniform linear motion. this method assumes that linear motion corresponds to an integral number of pixels. Compared to other classical methods, this method attains a higher value of the Improvement in Signal to Noise Ration (ISNR) parameter and a lower value of the Mean Square Error (MSE) parameter. Moreover, this method is more time-efficient. We give an implementation in the MATLAB programming package.

关键词： image restoration Wiener filter Pixel Mathematical model Filtering algorithms Equations Optical filters

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Combined block sparse PNLMS/NLMS algorithms

Combined block sparse PNLMS/NLMS algorithms

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International conference on systems, Signals and image processing, IWSSIP

作者： Kirill Sakhnov Boris Simak Department of telecommunications engineering Czech Technical University Prague Czech Republic

In some applications of adaptive filtering, such as echo cancellation and active noise reduction, an adaptive filter may be required to have a large number of coefficients in order to model unknown systems with a sufficient accuracy. the computational complexity of adaptive filtering algorithms is proportional to the number of filter coefficients being adapted. the main purpose of partial coefficient updating is to reduce high computational complexity associated with long echo paths. So as to reach computational savings, only a subset of the filter coefficients rather than the entire filter is updated. the filter weights to be updated are usually chosen in accordance with the amplitudes of input signal. However, this approach does not achieve similar performance comparing to the fully updated counterpart. there are opinions that for sparse impulse responses the convergence speed can be improved, if the coefficients amplitudes are used in selection criterion. this paper presents a study on proportionate, partially and sparse partial updated algorithms, and provides their generalization to the Proportionate Normalized Least Mean Squares algorithm. Computer simulations show a reasonable performance of the algorithm with applications, which require an identification of sparse regions within long echo paths.

关键词： Adaptive filters Convergence Filtering algorithms Algorithm design and analysis Measurement Echo cancellers Signal processing algorithms

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