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检索条件"任意字段=2nd International Conference on Computer Vision and Image Processing, CVIP 2017"

共 1803 条记录，以下是881-890 订阅

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Low bit-rate image compression based on post-processing with grouped residual dense network 32

Low bit-rate image compression based on post-processing with...

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32nd IEEE/CVF conference on computer vision and Pattern Recognition Workshops, CVPRW 2019

作者： Cho, Seunghyun Lee, Jooyoung Kim, Jongho Kim, Younhee Kim, Dong-Wook Chung, Jae Ryun Jung, Seung-Won Broadcasting and Media Research Laboratory Electronics and Telecommunitcaions Research Institute 218 Gajeong-ro Yuseong-gu Daejeon34129 Korea Republic of Department of Multimedia Engineering Dongguk University 30 Pildong-ro 1-gil Jung-gu Seoul04620 Korea Republic of

ISBN: (纸本)9781728125060

In this paper, an image compression method implemented for CVPR 2019 Challenge on Learned image Compression (CLIC) is introduced. It is designed to satisfy both requirements of image compression,"higher compression ratio" and"better quality", at the same time. To this end, a neural network based image quality enhancement is incorporated into the most recent traditional image/video coding technique. The decoders, ETRIDGU, ETRIDGUlite, and ETRIDGUfast, which implement the proposed image compression method are designed to have different degrees of complexity and compression efficiency. ETRIDGU, which provides the highest compression efficiency, is reported to achieve the 2nd highest PSNR in the lowrate track of CLIC. ETRIDGUlite, which compromises between the compression efficiency and the complexity, is reported to be the fastest one among the decoders with high mean opinion score (MOS) in the same track. © 2019 IEEE computer Society. All rights reserved.

关键词： image compression

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Modelling vision angles of optical camera zoom using image processing algorithm 2

Modelling vision angles of optical camera zoom using image p...

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2nd international Scientific conference on Pure Sciences ... Brilliant Creativity and Renewed Building

作者： Abbas, Heba Kh. Mohamad, Haidar J. Al-Saleh, Anwar H. Al-Zuky, Ali A. Department of Physics College of Science for Women University of Baghdad Baghdad Iraq Department of Physics College of Science Mustansiriyah University Baghdad Iraq Department of Computer Science College of Science Mustansiriyah University Baghdad Iraq

A challenge of adding a new feature to the optical properties of a camera is solved in this paper. image processing gives the possibility to enhance the quality, resolution and details of images fast these days. Within this paper, the introduced algorithm used to determine the vision angles (horizontal and vertical) of a digital camera (Nikon). The quality and efficiency of the camera are evaluated using determine the spatial resolution of the captured images. A scale factor algorithm is used also in this paper. A mathematical model introduced to describe the camera angle vision. This model works with different zoom degrees and different camera-object distances. Thus, a general mathematical equation obtained which describes the real image. The comparisons between the real and resulted images give a strong matching with small error rate. © 2019 Published under licence by IOP Publishing Ltd.

关键词： Digital cameras

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Bird Species Detection and Classification Based on HOG Feature Using Convolutional Neural Network 2nd

Bird Species Detection and Classification Based on HOG Featu...

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2nd international conference on Recent Trends in image processing and Pattern Recognition, RTIP2R 2018

作者： Ghosh, Susanto Kumar Islam, Md. Rafiqul Computer Science and Engineering Discipline Khulna University Khulna9208 Bangladesh

ISBN: (纸本)9789811391804

Bird detection and classification for real time image are com-plex tasks but crucial improvement can be performed by the best computer vision algorithms to solve such kinds of problems. Some challenges like lighting conditions of the images, similarities in subspecies of birds may be raised. During the last few years, CNN appeared as the state of the art with regard to the accuracy for a number of computer vision work such as image classification, object detection, and segmentation. To identify the object like bird CNN has been used in this work. Here, we have designed bird detection and classification system based on Gaussian and Gabor filters, HOG as well as Convolutional Neural Networks. HOG is one of the accepted features for object detection and it can be extracted from all portions of the image. So, Histogram of Oriented Gradients (HOG) is used to implement the CNN. We have done experiment with the standard datasets and have found better results than other methods by applying above procedures. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Birds

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Research on dimensional measurement method of large parts 2

Research on dimensional measurement method of large parts

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2nd international conference on Information Technologies and Electrical Engineering, ICITEE 2019

作者： Shan, Dongri Xu, Jiancong Jinan Shan dong China Jinan Shan dong China

ISBN: (纸本)9781450372930

Firstly, the size definition of large parts is given, and the importance of large-scale part size measurement methods is analyzed. Then, the existing large-scale parts measurement methods are studied, including large-scale three-coordinate measurement method, double theodolite measurement method, and laser. Tracker measurement method, indoor GPS measurement method and machine vision measurement method. The measurement principle, structure composition and research status of each measurement method are analyzed and summarized, and the SIFT image mosaic algorithm is introduced. Finally, the research and development trend of large-scale part size measurement methods is prospected. © 2019 ACM.

关键词： computer vision

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Effect and correction of segregation error in coal size distribution estimation by image analysis on a conveyor belt 2

Effect and correction of segregation error in coal size dist...

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2nd international conference on Physics, Mathematics and Statistics (ICPMS)

作者： Zhang, Zelin Hu, Qi Zhang, Zhiwei Wang, Li Wuhan Univ Sci & Technol Sch Resource & Environm Engn Hubei Key Lab Efficient Utilizat & Agglomerat Met Wuhan 430080 Hubei Peoples R China

Online monitoring of rock size is of great significance for mining and mineral processing, and machine vision is regarded as the most suitable approach. Segregation error of coal piles is inherent in image-based size distribution estimation, leading to the difference between surface size distribution and overall size distribution. In this research, we analysed the segregation error and proposed a correction method for image-based size distribution estimation of coal piles on a conveyor belt. The paint spraying of rock particles makes the compare of actual surface size distribution and overall size distribution possible. Rosin-Rammler particle characteristic equation was used to build the correction model to reduce the segregation error in size distribution estimation. Test results indicated that the corrected overall size distribution is close to the actual overall size distribution, and the maximal absolute error reduces from 19.98% to 2.04%. This investigation is useful and valuable for the optimization and improvement of image-based size distribution estimation of coal piles on a conveyor.

关键词： Size distribution

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Real-Time Two Way Communication System for Speech and Hearing Impaired Using computer vision and Deep Learning 2

Real-Time Two Way Communication System for Speech and Hearin...

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2nd international conference on Smart Systems and Inventive Technology, ICSSIT 2019

作者： Bohra, Tanuj Sompura, Shaunak Parekh, Krish Raut, Purva Dwarkadas J. Sanghvi College of Engineering Information Technology Mumbai India

ISBN: (纸本)9781728121192

Sign Language is the most expressive form of communication for speech and hearing impaired people to communicate with normal person but a normal person cannot understand sign language. So in order to break this barrier of communication there needs to be a system that can enable conversion of sign language to voice or text and voice or text to sign language and do it in real time. The systems that currently exist are not real time, do not facilitate two-way communication, require static surrounding conditions or have low recognition accuracy. There exist systems that have good accuracy but require external hardware like gloves [3] which increases the cost. Our contribution to solving this problem consists of a Sign Language Communication System. It is a real-time communications system built using the advancements in image processing, Deep Learning and computer vision that provides real-time sign language to text and text to sign language conversion. The project is software-based which can be installed on any computer with good specifications. It is also a two-way communication system allowing not just speech and hearing impaired to communicate with normal people but also other way around. The primary goal of our system is to enable hearing and speech impaired people to communicate with people that are not disabled in real time by interpreting alphabets, numbers and words in the Indian sign language. The system is able to predict 17600 test images in 14 seconds with an average prediction time of 0.000805 seconds with an accuracy of 99%. © 2019 IEEE.

关键词： Convolutional neural networks

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Material Classification Using Color and Texture Features 2nd

Material Classification Using Color and Texture Features

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2nd international conference on Recent Trends in image processing and Pattern Recognition, RTIP2R 2018

作者： Sapkale, Shubhangi S. Patil, Manoj P. School of Computer Sciences Kaviyatri Bahinabai Chaudhari North Maharashtra University Jalgaon India

ISBN: (纸本)9789811391804

Classification of texture is a very tedious problem in computer vision and pattern recognition. In this problem, the material is assigned to particular class of texture using its properties. This paper used both color and texture features to improve the recognition performance of Flickr Material Database (FMD). Authors described method of combining Color features (RGB), Luminance and Texture features. Gray-Level Co-occurrence Matrix (GLCM) is used to extract Texture features. The classification using, K-Nearest Neighbors (KNN) classifier is discussed with the experimental results. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Textures

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2nd international conference on Recent Trends in image processing and Pattern Recognition, RTIP2R 2018

2nd International Conference on Recent Trends in Image Proce...

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2nd international conference on Recent Trends in image processing and Pattern Recognition, RTIP2R 2018

ISBN: (纸本)9789811391866

The proceedings contain 173 papers. The special focus in this conference is on Recent Trends in image processing and Pattern Recognition. The topics include: Breaking News Recognition Using OCR;siamese Network for Learning Genuine and Forged Offline Signature Verification;multi-scale Local Binary Patterns- A Novel Feature Extraction Technique for Offline Signature Verification;ekush: A Multipurpose and Multitype Comprehensive Database for Online Off-Line Bangla Handwritten Characters;shonkhaNet: A Dynamic Routing for Bangla Handwritten Digit Recognition Using Capsule Network;reader System for Transliterate Handwritten Bilingual Documents;Recognition of Marathi Numerals Using MFCC and DTW Features;a Filter Based Feature Selection for Imbalanced Text Classification;a Combined Architecture Based on Artificial Neural Network to Recognize Kannada Vowel Modifiers;word Level Plagiarism Detection of Marathi Text Using N-Gram Approach;english Character Recognition Using Robust Back Propagation Neural Network;recognition of Signature Using Neural Network and Euclidean Distance for Bank Cheque Automation;a Semi-automatic Methodology for Recognition of Printed Kannada Character Primitives Useful in Character Construction;Distance Based Edge Linking (DEL) for Character Recognition;analysis of Segmentation and Identification of Square-Hexa-Round-Holed Nuts Using Sobel and Canny Edge Detector;3D Reconstruction of Plants Under Outdoor Conditions Using image-Based computer vision;automated Soil Tester;Crop Discrimination Based on Reflectance Spectroscopy Using Spectral Vegetation Indices (SVI);use of Spectral Reflectance for Sensitive Waveband Determination for Soil Contents;image processing Based Vegetation Cover Monitoring and Its Categorization Using Differential Satellite imageries for Urmodi River Watershed in Satara District, Maharashtra, India;UHTelPCC: A Dataset for Telugu Printed Character Recognition.

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Multidirectional wavelet-based fringe analysis for surface diagnosis by optical profilometry 2

Multidirectional wavelet-based fringe analysis for surface d...

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2nd international conference on Intelligent Computing in Data Sciences (ICDS)

作者： Bailich, Mohammed Bahich, Mustapha Amar, Said Bellach, Benaissa Rahmoun, Mohammed Mohamed First Univ EIT Dept ENSAO Oujda Morocco Moulay Ismail Univ Fac Sci Phys Dept Meknes Morocco Hassan II Univ Fac Sci Bern Msik Phys Dept Casablanca Morocco

Scientists, engineers, and manufacturers have a critical need for better techniques of diagnosis and quality control. The optical metrology uses the practical light and computer sciences, in order to perform simulation, design, computing and inspection for many scientific and industrial applications, such as optics, mechanics, aeronautics, electronics and many others. The fringe pattern analysis is a method to perform some operations on the optical images, in order to get an interferometric phase map and then to extract some useful information from it. In this paper, an exciting improvements of local fringe demodulation algorithm are presented, which are based on a new multidirectional wavelet. The numerical and experimental works show interesting gains compared to the other standard algorithms. Our approach executes as fast as the popular phase retrieval methods, but with substantially improved accuracy in demodulating noisy fringes. All of this comes without any pre-processing by filtering models. (C) 2019 The Authors. Published by Elsevier B.V.

关键词： Optical imaging computer vision image processing Multidirectional wavelets Phase recovery Fringe projection

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Intelligent control system for substation automatic grounding wire operation robot 2nd

Intelligent control system for substation automatic groundin...

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2nd CCF international conference on Artificial Intelligence, CCF-ICAI 2019

作者： Fu, Yuan Tan, Rongbin Lu, Jiaxing Tian, Yuewei Lu, Shouyin Guizhou Power Company Guiyang Power Supply Bureau Guiyang550000 China Shandong Jianzhu University Jinan250101 China Department of Computer Science Stevens Institute of Technology HobokenNJ07030 United States

ISBN: (纸本)9789813292970

This paper proposes an intelligent control system for the development of substation automatic grounding wire working robot. The system consists of two parts: robot motion control subsystem and robot visual servo subsystem. The system realizes autonomous control algorithm of robot operation process through robot vision servo technology, which combines stereo vision algorithm with equipment tracking algorithm. The object tracking algorithm and Kalman filter algorithm are used to extract and track the equipment area, and the binocular stereo vision algorithm is used to obtain the three-dimensional information of the equipment accurately, and the position information is fed back to the robot control system, which forms a servo control system. The system can realize unmanned operation of live working in the unattended situation, and improve the automation level and work efficiency of the operation. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Stereo image processing

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