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检索条件"任意字段=3rd International Conference on Computer Vision and Image Processing, CVIP 2018"

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Research on Intelligent Recognition of Train image Based on Machine vision

Research on Intelligent Recognition of Train Image Based on ...

引用

international conference on Cloud Computing and Internet of Things (CCIOT)

作者： Yu Zeng Jianhai Yue School of Mechanical Electronic and Control Engineering Beijing Jiaotong University Beijing China

ISBN: (数字)9781538671412

ISBN: (纸本)9781538671429

Machine vision has become a new technique in the AI field of image processing as an important and useful technique. Thus, it is significant to study image fusion on train fault. image fusion mainly studies the image data fusion technology to obtain a synthetic image including the multiple images of the same scene from many different patterns by the image sensors or the same sensor at the different time. In this paper, the images are collected form the bogie and coupler draft devices in the operation of train, and these images are merged based on wavelet transform. Compared with the weighted average fusion method about the fusion results of subjective and objective evaluation the superiority of wavelet transform is fully proved.

关键词： image fusion image edge detection Time-frequency analysis Discrete wavelet transforms Standards

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A Fuzzy-Rough-Based Approach for Uncertainty Classification on Hybrid Information System

A Fuzzy-Rough-Based Approach for Uncertainty Classification ...

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international conference on image, vision and Computing (ICIVC)

作者： Renjun He Chao Xu Daiwei Li Wenfeng Hou Xi Yu Haiqing Zhang AVIC Chengdu Aircraft Design & Research Institute Chengdu China College of Software Engineering Chengdu University of Information Technology Chengdu China School of Information Science and Technology Southwest Jiaotong University Chengdu China School of Computer Science Chengdu University Chengdu China

ISBN: (纸本)9781538649923

Hybrid information system (HIS) contains variety types of data including boolean, categorical, missing, real-valued, and set-based data, which are becoming very important for meaningful information analysis in real applications. The defect of the previous classification algorithms mainly lies in that the feature types of dataset haven't been comprehensively considered. In this paper, the internal relations among objects based on features that can reflect multiple data types have been expressed by heterogeneous distance function. And then, a new fuzzy-rough relation calculation under HIS and a new fuzzy-rough lower and upper approximation have been analyzed. Finally, the fuzzy-rough nearest neighbor classification under HIS (FRNN-HIS) algorithm has been proposed. Eight datasets has been adopted to conduct experiments. The experiments have shown that the proposed FRNN-HIS algorithm can significantly outperform FRNN and VQNN algorithms in terms of predicting classification results.

关键词： Classification algorithms Approximation algorithms Prediction algorithms Information systems Rough sets Task analysis Uncertainty

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A Method of Camera Link image Data processing Based on FPGA

A Method of Camera Link Image Data Processing Based on FPGA

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2018 3rd international conference on Computational Modeling, Simulation and Applied Mathematics (CMSAM 2018)

作者： Shi-feng WANG

Camera Link is based on the development of Channel Link Technology. The data is transmitted using low voltage differential signal(LVDS). It has some advantages, such as fast speed, strong anti-interference ability and so on. Camera Link is widely used in the field of robot vision applications. FPGA integrates rich gate circuit resources and has the advantages of high speed, which makes it suitable for processing parallel data. In this paper, a Camera Link image data processing method based on FPGA is proposed, which is verified by simulation and has been successfully applied to practical projects.

关键词： Camera Link image Data processing FPGA

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Object Sorting Automated System using Raspberry Pi

Object Sorting Automated System using Raspberry Pi

引用

international conference on Communication and Electronics Systems (ICCES)

作者： Sushrut Nagesh Kulkarni Sanjay Kumar Singh Department of Electronics and Communications Engineering Vellore Institute of Technology Vellore India

ISBN: (纸本)9781538647660

Typically sorting of items is done manually requiring human work. Identifying a particular object and placing it in the required order is a taxing work especially in the industrial field wherein one needs to sort a large number of objects in a small interval of time and also weight of the objects is much larger than what an average human can bear. Automation plays a noteworthy role in such cases. Taking mentioned factors under consideration alongside providing a cost efficient solution, we have presented our system in this paper. We are using Raspberry Pi, which is an open source board based on Linux. In today's technology, raspberry pi has been a key in a major number of applications in automation. Our objective will be to examine its utility and effective use as a mechanical system in Sorting of *** we are making use of a web camera that scans the image of the particular object to be sorted. The scanned image is then further processed using OpenCV to detect the shape and color of the object. OpenCV (Open Source computer vision) is a library of programming functions mainly aimed at real-time computer vision. With the help of the processed information in OpenCV, motor driver is instructed to control the servo motors which will help drive the object to the required sorted section. In our project, objects of 3 different colors and shapes, i.e. Pentagon, Square and Triangle with Red, Green and Blue colors.

关键词： image color analysis Shape Servomotors Sorting Robots Universal Serial Bus

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A Design of Mobile Partition Piles System in Urban Road

A Design of Mobile Partition Piles System in Urban Road

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2018 3rd international conference on computer Science and Information Engineering(ICCSIE 2018)

作者： Yuan Hang Nie Shangshang Zhong Fahai Luo Ronghui School of Civil Engineering Zhengzhou University

As it is known to all,more and more traffic pressure lead to traffic *** one way traffic jams happened in two-way *** system is designed to solve this *** is a mobile partition piles system,which contains three *** are information acquisition module,image processing module and automatic control *** system can monitor the condition of roads in real time by using machine vision *** can also move partition piles according to the traffic condition,which can ease traffic ***,partition piles will be back to original position when the problem is *** hardware and software of control system and mechanical structure has been *** tests verified the characteristics of this system,such as distinguish accurately,react rapidly,high intellect,low cost and run stably.

关键词： mobile partition piles smart city dynamic traffic assignment image recognition auto-control STM32

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Compressive Hyperspectral Imaging and Super-resolution

Compressive Hyperspectral Imaging and Super-resolution

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international conference on image, vision and Computing (ICIVC)

作者： Han Yuan Fengxia Yan Xinmeng Chen Jubo Zhu College of Liberal Arts and Sciences National University of Defense Technology Changsha Hunan China PLA 91604 91550 Dalian Liaoning China

ISBN: (纸本)9781538649923

Coded aperture snapshot spectral imager (CASSI) has been a popular spectral imaging architecture for its ability of capturing hyperspectral images with high temporal resolution. However, such snapshot imaging system entails a large sacrifice in the spatial resolution of the data cube, since only a small amount of light gets into the imager during one snapshot. Also, the spatial resolution of the CASSI system is limited by the pixel size (and amount) of the detector, while it is difficult to fabricate a dense detector with small pixel size, especially for infrared spectral bands. Super-resolution is an advanced post-processing technique to alleviate such problem by exploiting the prior information of the image. In this letter, we try to realize image super-resolution from the perspective of developing new form of measurements by taking advantage of a modified CASSI system equipped with a coded aperture with higher spatial resolution than the detector, merging the SR model into the hardware configuration. Then the original data cube can be reconstructed from lower resolution measurements, thus the super-resolution is realized during the compressive sensing reconstruction process. The new system can be achieved based on the classical CASSI architecture in two dual ways, one by replacing the coded aperture with a higher resolution one and the other by substituting the focal plane array (FPA) detector with a lower resolution one. The experiments show that, we can recover images of higher quality with the first modification of CASSI system above, simply using a higher resolution coded aperture.

关键词： Spatial resolution Detectors Apertures Hyperspectral imaging image reconstruction Imaging

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Study of Target Tracking and Recovery with Low Resolution image Series 3

Study of Target Tracking and Recovery with Low Resolution Im...

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3rd IEEE international conference on computer and Communications (ICCC)

作者： Bao, Xueting Zhan, Hongchen Yuan, Jie Nanjing Univ Sch Informat Sci & Engn Jinling Coll Nanjing 210089 Jiangsu Peoples R China Nanjing Univ Sch Elect Sci & Engn Nanjing 210093 Jiangsu Peoples R China

ISBN: (纸本)9781509063529

Object tracking is one of the most important tasks in computer vision. It is aimed to track and identify the targets in every frame automatically, thus making it possible extracting the targets in the frames for the post-processing. The described method encompasses two important issues in image tracking system that have received increased attention in the few years: moving object tracking and object recognition. It is based on kernel algorithm and due to the continuously changing background and moving targets, object tracking has been a challenging task We review strategies under kernel algorithm and successfully track and restore the image.

关键词： object tracking image restoration kernel algorithm ensemble tracking image extraction

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CNN Design for Real-Time Traffic Sign Recognition 3

CNN Design for Real-Time Traffic Sign Recognition

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3rd international conference on Information Technology and Nanotechnology (ITNT)

作者： Shustanov, Alexander Yakimov, Pavel Samara Natl Res Univ Moskovskoye Shosse 34 Samara Russia

Nowadays, more and more object recognition tasks are being solved with Convolutional Neural Networks (CNN). Due to its high recognition rate and fast execution, the convolutional neural networks have enhanced most of computer vision tasks, both existing and new ones. In this article, we propose an implementation of traffic signs recognition algorithm using a convolution neural network. The paper also shows several CNN architectures, which are compared to each other. Training of the neural network is implemented using the TensorFlow library and massively parallel architecture for multithreaded programming CUDA. The entire procedure for traffic sign detection and recognition is executed in real time on a mobile GPU. The experimental results confirmed high efficiency of the developed computer vision system. (C) 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the scientific committee of the 3rd international conference "Information Technology and Nanotechnology".

关键词： TensorFlow Convolutional Neural Networks Traffic Sign Recognition image processing computer vision Mobile GPU

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Modified Level-Set for Segmenting Breast Tumor from Thermal images

Modified Level-Set for Segmenting Breast Tumor from Thermal ...

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international conference for Convergence of Technology (I2CT)

作者： Swathi Gopakumar K Sruthi Shivasubramani Krishnamoorthy Amrita Center for Wireless Networks & Applications (AmritaWNA) Amrita School of Engineering Amritapuri Amrita Vishwa Vidyapeetham India Dept of Computer Science and Engineering Amrita School of Engineering Amritapuri Amrita Vishwa Vidyapeetham India

Contactless, painless and radiation-free thermal imaging technique is one of the preferred screening modalities for detection of breast cancer. However, poor signal to noise ratio and the inexorable need to preserve edges defining cancer cells and normal cells, make the segmentation process difficult and hence unsuitable for computer aided diagnosis of breast cancer. This work uses a modified version of level-set called marker-controlled level-set for segmentation along with pre-processing. This paper presents key findings from a research conducted on the appraisal of two promising techniques, for the detection of breast cancer: a) marker-controlled Level-set segmentation of anisotropic diffusion filtered preprocessed image versus b) Segmentation using marker-controlled level-set on a Gaussian-filtered image. The proposed method was carried out on images from an online database with samples collected from women of varying breast characteristics. It was observed that the breast was able to be segmented out from the background by adjustment of the markers. From the results, it was observed that as a pre-processing technique, anisotropic filtering with level-set segmentation, preserved the edges more effectively than Gaussian filtering. Segmented image, by application of anisotropic filtering was found to be more suitable for feature extraction, enabling automated computer aided diagnosis of breast cancer.

关键词： image segmentation Filtering Breast cancer Level set image edge detection

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image processing Based Analysis of Cracks on Vertical Walls

Image Processing Based Analysis of Cracks on Vertical Walls

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international conference on Internet of Things: Smart Innovation and Usages (IoT-SIU)

作者： Jayneel Vora Maitree Patel Sudeep Tanwar Sudhanshu Tyagi Department of Computer Engineering Institute of Technology Nirma University Ahmedabad Gujarat India ThaparInstitute of Engineering & Technology Deemed University Patiala (Pb.) India

ISBN: (纸本)9781538638330

Building defects are a regular occurring in constructions all over. There is a need to identify the type of defect present and accordingly take the necessary steps for correcting the defect. This paper focuses on the various construction defects that take place on different types of walling systems for buildings. A major problem is the lack of knowledge regarding the construction concepts in the residents of the building. The study undertook tackles this problem using image processing and identifying various defects in an android app. This study is conducted on the walls of K-Block, Nirma University. The defects are observed and monitored through this study. The collected images are analysed and proper intimations can be pursued. Based on the recordings, various types of building defects were identified and proper gradations were given. Work is under process to monitor a house in the Virtual World, and create a visualiser of degradation of the house over the years.

关键词： Estimation image edge detection Skeleton Buildings Gray-scale Degradation

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