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

共 16210 条记录，以下是4871-4880 订阅

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Sensitivity Evaluation of Radiographs Based on Multi-dimensional Data Coupling Analysis

Sensitivity Evaluation of Radiographs Based on Multi-dimensi...

引用

International conference on Computer and Communications (ICCC)

作者： Hongquan Jiang Deyan Yang Qihang Hu Zelin Zhi Jianmin Gao xiaoqiao Wang xiaoming Zhang Huaxiang Pu Hua Li State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong University Xi'an China Shaanxi Special Equipment Inspection and Testing Institute Xi'an China

ISBN: (数字)9781728186351

ISBN: (纸本)9781728186368

The sensitivity evaluation of image quality indicator (IQI) is an important factor to judge the qualification of radiographs. In order to solve the problems of subjective and low efficiency of manual evaluation method, as well as the difficulty in IQI features extraction and accurate evaluation of sensitivity, a method for determining the sensitivity of radiographs based on coupling analysis of two-dimensional image and one-dimensional gray data is proposed. Firstly, the IQI location technology based on gradient region growth is proposed to realize IQI location in complex background in digital image. Secondly, the IQI image detail enhancement and noise reduction are realized through angle self-correction and enhancement processing. Thirdly, the two-dimensional image data is transformed into one-dimensional gray change data by integral projection method, and a method of IQI feature recognition and sensitivity evaluation based on gray data extreme value change analysis is proposed. The proposed method is evaluated using the actual industrial radiographs. The evaluation results demonstrate the effectiveness and superiority of the proposed method in automatic sensitivity evaluation of radiographs under complex background and low contrast.

关键词： Radiography Couplings Sensitivity Wires Metals Turbines Qualifications

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An approach to the applicability evaluation of moving target tracking algorithm 2nd

An approach to the applicability evaluation of moving target...

引用

2nd Chinese conference on Pattern Recognition and Computer Vision, PRCV 2019

作者： xi, Runping Xue, Shaohui Han, Qianqian Chen, Jiaxin School of Computer Science Northwestern Polytechnical University Xi’an710129 China National Engineering Laboratory of Integrated Aero-Space-Ground-Ocean Big Data Application Technology Xi’an710129 China Shaanxi Provincial Key Laboratory of Speech and Image Information Processing Xi’an710129 China

ISBN: (纸本)9783030317256

Objective and effective algorithm performance evaluation results are an important basis for the selection of tracking algorithms. Problems in the existing performance evaluation of moving target tracking algorithms include an enlarge number of trials, and in particular, failure to consider the influence of algorithm performance on the multifactor combination scenario. This study proposes a method based on the orthogonal test to evaluate algorithms. First, the factors and levels of the tracking algorithm are analyzed, and an orthogonal test dataset is constructed by using an orthogonal table. Second, the experiments of the performance evaluation are arranged with the dataset and the results are analyzed via range analysis. Finally, evaluation results show that the strong– weak sequence of factors affect the performance of the algorithm and the combination of levels form the factors that can achieve enhanced algorithm performance. Experimental results show that the proposed method can evaluate algorithms comprehensively, objectively, and effectively with decreased test and data volume. © Springer Nature Switzerland AG 2019.

关键词： Clutter (information theory)

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Real Time Density Based Traffic Surveillance System Integrated with Acoustic Based Emergency Vehicle Detection

Real Time Density Based Traffic Surveillance System Integrat...

引用

International conference on Computer, Communication and Signal processing (ICCCSP)

作者： Sai Surya Prakash Moka Sai Manikanta Pilla S. Radhika Sathyabama Institute of Science and Technology Chennai India

ISBN: (数字)9781728165097

ISBN: (纸本)9781728165103

As the problem of traffic congestion is prevalent in many metropolitan cities there is an urgent need for a traffic surveillance system which regulates the traffic in an efficient way. The current conventional methods such as timer based traffic control system is proved to be inferior to solve this issue and also the current systems does not give priority in the cases where emergency vehicles are detected. In this paper a smart traffic surveillance system has implemented where the access will be given to the lane having the highest density of traffic in the absence of emergency vehicle. When an emergency vehicle is detected in any lane, the priority shifts to the lane in which the emergency vehicle is present. Digital image processing techniques are used to compute the density of traffic and signal processing techniques are used to detect the presence of an emergency vehicle. The complete proposed system, from image and sound acquisition to canny edge detection and noise removal by Least Mean Square(LMS) filter and finally the green signal allotment to the lanes depending on the output results are illustrated with proper schematics and the final results are validated by hardware implementation.

关键词： image edge detection Signal processing algorithms Wiener filters Signal processing Roads Traffic control image processing

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Efficient image Watercolorization Based on Smart Phones

Efficient Image Watercolorization Based on Smart Phones

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High Performance Big Data and Intelligent systems (HPBD&IS)

作者： Huijuan Zhang Xuezhong xiao School of Computer Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (数字)9781728165127

ISBN: (纸本)9781728158976

image watercolorization is a hot research topic in the field of non-photorealistic rendering. There are many methods proposed to simulate the various features of watercolor painting including edge darkening, pigment dispersion, turbulence, and paper texture. However, almost all of them are implemented for desktop systems and cannot be directly transplanted to mobile devices. From the view of resultant effects and computing efficiency, an image watercolorization framework is proposed for smart phones, which employs several existing image processing algorithms to simulate the visual features of watercolor painting. Finally, the method is optimized in parallel to improve the efficiency. The experiments show the presented method has good performance.

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Infrared Dim and Small Targets Detection Based on Multi-scale Local Contrast Measure Utilizing Efficient Spatial Filters

Infrared Dim and Small Targets Detection Based on Multi-scal...

引用

International conference of Signal processing and Intelligent systems (ICSPIS)

作者： Iman Faramarzi Jinhui Han Yuanyuan Chen Faculty of Electrical and Computer Engineering Malek-e-Ashtar University of Technology Tehran Iran College of Physics and Telecommunication Engineering Zhoukou Normal University Zhoukou China

ISBN: (数字)9781728186290

ISBN: (纸本)9781728186306

Given the growing importance of infrared search and track (IRST) systems, in this paper, inspired by the mechanism of the human visual system (HVS), we present a robust algorithm for the detection of infrared (IR) dim and small targets based on Multi-scale Local Contrast Measure utilizing Efficient Spatial Filters, which is named as ESFMLCM. In the proposed algorithm by considering a nested structure, three efficient spatial filters, namely Gaussian filter, mean filter, and standard deviation filter, are applied to each pixel of the raw IR image, simultaneously. According to the idea of the matched filter, the Gaussian filter has been used to improve the actual targets and increase the detection rate. Also, two other filters have been used to suppress all the types of interferences (noise and background clutters) and reduce the false alarm rate. Finally, a simple adaptive threshold operation is applied to extract actual targets or remove fake targets. The numerical and visual results show that the proposed algorithm can detect IR dim and small targets under complex backgrounds with high accuracy in comparison with other algorithms.

关键词： Matched filters Visualization Signal processing algorithms Filtering algorithms Spatial filters Clutter Standards

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Secured Automated Complaint Generation System for Organizations

Secured Automated Complaint Generation System for Organizati...

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International conference on Computer, Communication and Signal processing (ICCCSP)

作者： K Vidya Lavanya Amalbabu K.S Sowndharya Swaathi Balaji College of Engineering Anna University Chennai India

ISBN: (数字)9781728165097

ISBN: (纸本)9781728165103

In our society, complaint systems are all done manually by humans and there are no automated system wherein the complaints are identified and sent to the respective authority all by itself. A complaint about our day to day activities based on the images can be identified and given as a report. This reduces lot of manual time and may speedup the remedial process. In this system, the users need to upload an image which will be analyzed and classified based on remedial departments. Thus the amount of manual work both on the user and the organization is minimized by feasibly producing an automated system that can generate a report about the problem without human intervention during the process. Based on the institutional requirements, the complaints are classified as website-based and object-based using an image classification system. The web-related complaints are handled by optical character recognition and the object-based complaints are handled by object detection and data mining techniques. The images are trained and tested through various classification system and their performances are compared. The user is also provided with a feature of adding location along with the complaint image which makes less complication in finding the place of fault and based on which a report is generated and forwarded to corresponding department. Thus, this paper aims in proposing an automated complaint generation and reporting system for Institutions by classifying user input images using image processing and data mining techniques.

关键词： Feature extraction Training Object detection Computational modeling Proposals Signal processing algorithms Classification algorithms

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image Color Reduction Using Progressive Histogram Quantization and Kmeans Clustering

Image Color Reduction Using Progressive Histogram Quantizati...

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Mechatronics, Remote Sensing, Information systems and Industrial Information Technologies (ICMRSISIIT), International conference on

作者： Ibrahim El rube’ Taif University Taif KSA

ISBN: (纸本)9781728104874

Color reduction is an important tool for different image processing and computer vision applications. In this paper, a progressive histogram-based color reduction (quantization) is used with the Kmeans clustering algorithm to speed up the quantization process of the Kmeans method. The progressive histogram quantization (PHQ) is a simple iterative algorithm where a single histogram bin is merged to one of its two nearest neighbors' bins at each iteration. The histogram bin is merged according to the differences in the value (pixel counts) and the location of the left and right bins. The PHQ algorithm is used as a pre-quantization for the Kmeans clustering to reduce the size of the data and speed up the clustering process. The experimental results show that the PHQ+Kmeans algorithm maintains good image quality and enhances the execution time compared to the Kmeans clustering algorithm alone when applied on remote sensing images.

关键词： image quality Histograms Quantization (signal) Mechatronics image color analysis Clustering algorithms Tools

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Convolutional neural networks application in cardiovascular decision support systems 2

Convolutional neural networks application in cardiovascular ...

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2nd International conference on image and Video processing, and Artificial Intelligence (IPVAI)

作者： Natalia, Konnova Mikhail, Basarab Michael, Khachatryan Anna, Domracheva Igor, Ivanov Bauman Moscow State Tech Univ Comp Sci & Control Syst Dept 2 Ya Baumanskaya St5 Moscow 105005 Russia

ISBN: (数字)9781510634107

ISBN: (纸本)9781510634107

The paper considers the possibilities of using neural network methods of machine learning to diagnose the states of the human cardiovascular system and support decision-making in cardiology and cardiac surgery. The issues of processing and preparation of electrocardiography signals, selection of architecture and tuning of neural network parameters for automation of diagnosis are discussed. Here, the results obtained with the help of multilayer perceptrons and convolutional neural networks to assign the submitted input cardiovascular data to one of the classes of states in the selected space are examined. Based on a specialized developed software, the proprietary numerical experiments with real clinical data were carried out. Given the above results, demonstrating the applicability of the used deep learning methods and algorithms to diagnostic automation, a model of a hierarchical decision support system is proposed.

关键词： decision support system deep learning digital signal processing machine learning neural networks

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Comparison research on X-ray image quality defects detection algorithm in semiconductor manufacturing

Comparison research on X-ray image quality defects detection...

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2019 IEEE International conference on Smart Manufacturing, Industrial and Logistics Engineering, SMILE 2019

作者： Hou, Hongyu Wu, Feng Key Lab of the Ministry of Education for Process Control Efficiency Engineering School of Management xi'An Jiaotong University Xi'an China

ISBN: (纸本)9781538679982

Detecting product quality defects through image recognition technology is one of the key technologies of intelligent manufacturing, and also an important step for enterprises to construct smart factory. In the capsulation step of the semiconductor enterprise, the internal wire bonding of the chip is easily to receive the interference and to produce the defects. Companies need to pick out defective chips to avoid them going to the market. Traditional way is to use artificial vision visual inspection, which may lead to low efficiency and high labor cost. This study intends to use machine vision detection method based on image processing technology to identify the defect of the chip and to replace the workers artificial detection work. This paper proposes two algorithms to solve such above problems. The template matching algorithm (TMA) is to determine whether the chip is defective mainly based on the standard template. The neighborhood comparison algorithm (NCA) mainly calculates similarity of the neighbor chips to judge the target chip's defects. The algorithm is implemented by Halcon software. A German semiconductor company has provided enough samples to support our research. The experimental results show that the two algorithms are effective in defect detection of specific products. The advantage of the TMA lies in its processing speed, but the applicability and accuracy of NCA is more excellent. The algorithm proposed in this study can be used for enterprise by being integrated into the actual detection process. © 2019 IEEE.

关键词： Template matching

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3rd International conference on Computational Intelligence and Informatics, ICCII 2018

3rd International Conference on Computational Intelligence a...

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3rd International conference on Computational Intelligence and Informatics, ICCII 2018

ISBN: (纸本)9789811514791

The proceedings contain 79 papers. The special focus in this conference is on Computational Intelligence and Informatics. The topics include: Click-through rate prediction using decision tree;a new framework approach to predict the wine dataset using cluster algorithm;study and ranking of vulnerabilities in the indian mobile banking applications using static analysis and bayes classification;analysis of object identification using quadrature bank filter in wavelet transforms;experimental analysis of the changes in speech while normal speaking, walking, running, and eating;uip—a smart web application to manage network environments;energy distribution in a smart grid with load weight and time zone;matrix approach to perform dependent failure analysis in compliance with functional safety standards;a cloud-based privacy-preserving e-healthcare system using particle swarm optimization;improved approach to extract knowledge from unstructured data using applied natural language processing techniques;word sense disambiguation in telugu language using knowledge-based approach;a study of digital banking: Security issues and challenges;encoding approach for intrusion detection using pca and knn classifier;materializing block chain technology to maintain digital ledger of land records;review of optimization methods of medical image segmentation;automatic temperature control system using arduino;performance analysis of fingerprint recognition using machine learning algorithms;a survey on digital forensics phases, tools and challenges;a brief survey on blockchain technology;energy-efficient based multi-path routing with static sink using fuzzy logic controller in wireless sensor networks;mst parser for telugu language;design of low-power vedic multipliers using pipelining technology;needleman–wunsch algorithm using multi-threading approach;quicksort algorithm—an empirical study.

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