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

共 1800 条记录，以下是131-140 订阅

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The Atmospheric Light Estimation by Divergence Operator 19

The Atmospheric Light Estimation by Divergence Operator

引用

2nd international conference on computer Science and Software Engineering (CSSE)

作者： Ai, De-Zhi Wu, Yuan Gu, Li-Dan Wang, Chao Zhejiang Ocean Univ Sch Math Phys & Informat Sci Zhoushan Zhejiang Peoples R China

ISBN: (纸本)9781450371728

In the field of optics and computer vision, image defogging has attracted much attention due to its wide application. On the premise of fully analyzing the characteristics of foggy images, this paper proposes a new method to improve the estimation of atmospheric light by improving the divergence information. Experimental results show that compared with the traditional defogging algorithm, this algorithm has a faster processing speed, and the recovered image details are prominent, which can effectively remove the haze in the image and has a better visual effect.

关键词： image dehazing Dark channel prior Atmospheric light Divergence

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image Segmentation in Constrained IoT Servers 2nd

Image Segmentation in Constrained IoT Servers

引用

2nd international conference on Recent Trends in Advanced Computing, Disruptive Innovation (ICRTAC-DTI)

作者： Sharma, Nishant Sultana, Parveen H. Singh, Rahul Patil, Shriniwas Pareek, Sumit Vellore Inst Technol Vellore 632014 Tamil Nadu India

image segmentation forms an important concept in the computer vision technology. image segmentation breaks the image into boundaries that differentiate meaningful components. For computer vision to realize its full potential it is essential that the image segmentation algorithms give accurate results in a fast and efficient way. In hierarchical architecture based IoT networks set up to "see" the world, methods of computer vision need more analysis. The need for low cost setup for IoT networks in terms of memory and their computational capabilities demands research for developing methods that are resource sensitive and can be successfully integrated into such networks of low end IoT servers. Addressing this need, a refined graph cut segmentation technique for low to medium resolution images and for constrained devices is presented in the paper. Implementation and analysis of the refined graph cut segmenter for linux based IoT servers is discussed. A comparison with the contemporary segmentation methods under similar constraints is also presented. (C) 2019 The Authors. Published by Elsevier B.V.

关键词： Foreground extraction Graph-cut segmentation IoT image processing MM-cut max-flow RGCS Segmentation

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Remote sensing image matching method based on neural network 2

Remote sensing image matching method based on neural network

引用

2nd international conference on computer vision, image, and Deep Learning

作者： Qiao, Weihua Shandong University of Science and Technology 579 qianwangang Road Shandong Qingdao China

ISBN: (数字)9781510646827

ISBN: (纸本)9781510646810

The traditional remote sensing image matching method based on registration algorithm has problems in the smoothness of the matching results in practical application. Therefore, a remote sensing image matching method based on neural network is proposed. Based on neural network to extract remote sensing image control points, visual processing of remote sensing image feature points, matching remote sensing image control points, a new matching method is proposed. The experimental results show that the new matching method can effectively improve the anti-interference ability, reduce the noise in the matching behavior and improve the smoothness of the matching results. © 2021 SPIE.

关键词： image matching

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image Registration between Visible and Infrared images for Electrical Equipment Inspection Robots based on Quadrilateral Features 2

Image Registration between Visible and Infrared Images for E...

引用

2nd international conference on Robotics and Automation Engineering (ICRAE)

作者： Chen, Yahui Dai, Jindun Mao, Xianyin Liu, Yadong Jiang, Xiuchen Shanghai Jiao Tong Univ Dept Elect Engn Shanghai Peoples R China China Southern Power Grid Guizhou Power Grid Corp Elect Power Res Inst Guiyang Guizhou Peoples R China

ISBN: (纸本)9781538613061

Visible and infrared images are essential for electrical inspection robots to detect equipment or components. Here how to combine these two kinds of information is a critical problem. image registration is one of the necessary processing procedures. While used in practice, traditional intensity-based or feature-based registration methods appear many deficiencies such as low accuracy, low reliability or low speed. In this paper, we propose an efficient registration method based on the quadrilateral features of electrical equipment. Contour and straight line detection technology is utilized to reconstruct the quadrilateral structural information of the monitoring object from original images. Experimental results indicate that our proposed registration method can align visible and infrared images fast with high accuracy and be less likely to be influenced by image quality or other irrelevant objects.

关键词： image registration robot vision processing electrical equipment inspection robot quadrilateral feature

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computer vision Approach for Controlling Educational Robotic Arm based on Object Properties. 2

Computer Vision Approach for Controlling Educational Robotic...

引用

2nd IEEE international conference on Emerging Technology Trends in Electronics, Communication and Networking (ET2ECN)

作者： Rai, Neerparaj Rai, Bijay Rai, Pooja SMIT Elect & Elect Dept Sikkim India

ISBN: (纸本)9781479969869

This research presents an autonomous robotic frame work for academic, vocational and training purpose. The platform is centred on a 6 Degree Of Freedom (DOF) serial robotic arm. Two on-board cameras develop a computer vision system for detection and autonomous object/target manipulation placed randomly on a target surface and controls an educational robotic arm to pick it up and move it to a predefined destination. The computer vision is initially used to identify the colour and shape of the object. The system applies Centre-Of-Mass based computation, filtering and colour segmentation algorithm to locate the target and the position of the robotic arm. The proposed platform finds its potential to teach technical courses (like Robotics, Control, Electronics, image-processing and computer vision) and to implement and validate advanced algorithms for object manipulation and grasping, trajectory generation, path planning, etc. Experimental results demonstrated the effectiveness and robustness of the system.

关键词： computer-vision robotic arm autonomous system

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Measurement of Stain Area in Metal Surface with Particle Analysis 2

Measurement of Stain Area in Metal Surface with Particle Ana...

引用

2nd international conference on Applied Information Technology and Innovation (ICAITI)

作者： Riandini Dewantoro, Shahnan Kamil Istoni, Reza Politekn Negeri Jakarta Dept Elect Engn KampusUI Depok Indonesia

ISBN: (纸本)9781728130163

Measurement of the object dimension in terms of digital image processing is one of the computer vision applications. The digital image is obtained from the camera / webcam, where calibration and settings are carried out to convert the output of the camera which is a pixel of images into physical unit values (length and area). The distance between the two points on the image is known by counting the number of pixels in the image. Regression analysis method is used to get the conversion equation between variable number of pixels into units of length. The conversion equation is used to measure the length and area of 10 pieces of template cut by a CNC machine with sizes from 1x1cm to 10x10cm. The validity of the pixel calibration results in units of length was tested by measuring 10 template sizes. Measurement of the area of the stain / defect due to corrosion on metal plates is carried out on a number of samples with a random stain size, by counting the number of pixels that exist with the help of the developed LabVIEW-NI vision application. Data acquisition and analysis systems have worked in accordance with the design concept, pixel data can be measured and converted into physical units of millimeters or centimeters, with a measurement resolution of the instrument of 0.1220 mm.

关键词： image processing computer vision digital image corrosion regression analysis

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Linguistic support of the knowledge base for image analysis and understanding system

Linguistic support of the knowledge base for image analysis ...

引用

2nd international conference on computer vision Theory and Applications, VISAPP 2007

作者： Trusova, Yulia Gurevich, Igor Beloozerov, Victor Murashov, Dmitri Dorodnicyn Computing Center Russian Academy of Sciences 40 Vavilov str. Moscow 119991 Russia

The problem of lexical and semantic support of the knowledge base for the system for automation of scientific research in image processing, analysis and understanding is discussed. The main contribution is the image analysis thesaurus which has been developed as a main tool for solving this problem. A structure of the thesaurus and functional characteristics of the basic version of the thesaurus are described. Lexical categories of terms and relationships between terms in the domain of image processing, analysis and recognition are considered. The thesaurus was implemented as an autonomous program module. The description of the thesaurus module and its use are provided. The developed thesaurus was applied for automation of early diagnosis of hematological diseases on the base of cytological specimens.

关键词： Ontology

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Multi-Scale Hybrid Attention Integrated with vision Transformers for Enhanced image Segmentation 2

Multi-Scale Hybrid Attention Integrated with Vision Transfor...

引用

2nd international conference on Algorithm, image processing and Machine vision, AIPMV 2024

作者： Gong, Zhaoxuan Chanmean, Meas Gu, Wenwen School of Computer Engineering Shenyang Aerospace University Liaoning Shenyang China School of Computer Science Shenyang Aerospace University Liaoning Shenyang China

ISBN: (纸本)9798350390254

In this paper, we present an advanced approach for image segmentation that enhances vision Transformers (ViTs) by integrating multi-scale hybrid attention mechanisms. While ViTs use self-attention to capture global dependencies in images, they often miss local details crucial for segmentation tasks. Our method addresses this by incorporating convolutional layers with different kernel sizes to extract local features at multiple scales. These features are then merged with the global self-attention outputs, creating a hybrid attention map that captures both fine details and overall structures. Testing on standard benchmarks shows our approach significantly improves segmentation accuracy and robustness compared to traditional ViTs, demonstrating its potential for handling complex visual scenes. © 2024 IEEE.

关键词： Convolutional neural networks

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A VHDL Based Moore and Mealy FSM Example for Education 2

A VHDL Based Moore and Mealy FSM Example for Education

引用

2nd IEEE international conference on Signal and image processing (ICSIP)

作者： Alsubaei, Sultana Qaisar, S. M. Alhalabi, W. Effat Univ Elect & Comp Engn Dept Jeddah Saudi Arabia Effat Univ Dept Comp Sci Jeddah Saudi Arabia

ISBN: (纸本)9781538609699

With recent technological advancements, modern societies are becoming more and more dependent on the automated machines. It is in order to cope with their fast-going lives. Modern automated machines adapt their sequence of actions depending on their environment and events. The FSM (Finite state machine) is used to mathematically express those sequences of actions or instructions. In this article two FSM machines types, Moore and Mealy, are discussed. Showing different results in order to demonstrate the importance of FSM modeling. An edge detector circuit is designed by employing both Moore and Mealy machines. It is a FSM design example, can be used for students concepts building and demonstration. These designs are implemented in VHDL. A comparison is also made based on both implementations.

关键词： FSM automation VHDL Xilinx-ISE timing diagram computer aided design

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A Critical Review of Object Detection using Convolution Neural Network 2

A Critical Review of Object Detection using Convolution Neur...

引用

2nd international conference on Communication, Computing and Digital Systems (C-CODE)

作者： Nisa, Sehar Un Imran, Muhammad Shaheed Zulfikar Ali Bhutto Inst Sci & Technol SZ Islamabad Pakistan

ISBN: (纸本)9781538696095

To recognize an object, for a human, is an easy task but for machines, to perform the same task with same efficiency is a complex task. For computer systems, images are sets of numeric values that have no meaning in itself. To make these numbers useful, diverse techniques have been proposed. Comparative to others, deep learning approaches achieved state-of-the-art performance in many computer vision applications, such as object detection, image classification, image retrieval, human pose estimation. To detect object of interest, Convolutional Neural Network (CNN) has been observed widely successful method. Few factors are there to get better accuracy and performance for instance efficient model, larger datasets and hardware support. This study aims to review CNN methods for object detection by highlighting the contribution and challenges from few recent research papers. Also how well to use these CNN techniques in combination to other methods for best suited results with other. Better performance such as increased accuracy, fast processing reduce error rates also introduced few new concerns and issues in parallel regarding the discussed methods such as time consumption, anonymous behavior of Neural Network. To address these issues a conceptual model is presented using CNN and Lease Square Support Vector Machine (LS-SVM).

关键词： computer vision Convolutional Neural Network detection image Lease Square Support Vector Machine object

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