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

共 16444 条记录，以下是1441-1450 订阅

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Face Recognition Implementation Based on image processing Techniques

Face Recognition Implementation Based on Image Processing Te...

引用

Signal processing and Intelligent Computing (SPIC), International conference on

作者： Bingcan Yang xiai Chen School of Automation and Electrical Engineering Shenyang Ligong University Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798350368888

ISBN: (纸本)9798350368895

image processing is a technique that involves the manipulation and enhancement of digital images. It encompasses various aspects such as image acquisition, image preprocessing, image enhancement, image segmentation, feature extraction, and object detection. The purpose of image processing is to process and enhance images using computer technology, aiming to achieve higher image quality for subsequent processing and applications. In practical applications, image processing techniques employ different algorithms and methods to achieve various processing and enhancement effects. Additionally, image processing techniques can be applied in fields such as medicine, security, autonomous driving, VR/AR, etc. For instance, in the medical field, image processing techniques can be utilized for image segmentation and diagnosis of medical images, thereby improving the accuracy and analytical capabilities of medical imaging. In the security field, image processing techniques can be employed for tasks such as video surveillance and facial recognition, enhancing the efficiency and accuracy of security monitoring. In the domain of autonomous driving, image processing techniques can be used for detecting and recognizing the surrounding environment of vehicles, thereby enhancing the safety and performance of autonomous driving systems. In conclusion, image processing technology is a very important technology. By continuously improving the accuracy and reliability of the algorithm, it is expected to be applied in a wider range of applications.

关键词： image segmentation image recognition Accuracy image processing Face recognition Signal processing algorithms Signal processing Video surveillance Medical diagnostic imaging Autonomous vehicles

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Direction-of-arrival estimation with new versions of Min-Norm algorithm based on Nyström method 7

Direction-of-arrival estimation with new versions of Min-Nor...

引用

7th International conference on image and Signal processing and their Applications, ISPA 2022

作者： Naceur, Aounallah Ali, Khalfa Kasdi Merbah University Faculty of New Information Technologies and Communication Department of Electronic and Telecommunications Ouargla30000 Algeria Mohamed Boudiaf University Faculty of Technologies Department of Electronic M'Sila28000 Algeria

ISBN: (纸本)9781665480420

Direction-of-arrival estimation is a significant problem in many telecommunication systems which their architecture is composed with antenna arrays. In literature, several algorithms were proposed as a challenge, for different scenarios, to detect rapidly and accurately the direction of impinging signals on the antenna array. In this paper firstly, we use the Nyström method to develop a low computational Min-Norm version for solving the problem of direction-of-arrival estimation by spectral peak searching. Then, we generalize the root version of the proposed algorithm. Finally, we give some simulation results for demonstrating the efficiency and the performances of the new proposed algorithm versions. © 2022 IEEE.

关键词： Array processing

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An Efficient Target Localization Method in MPR systems with Reduced Transmitter Dependency

An Efficient Target Localization Method in MPR Systems with ...

引用

IEEE International conference on Information Communication and Signal processing (ICICSP)

作者： Mingzhu Yan Haihong Tao Le Wang National Key Laboratory of Radar Signal Processing Xidian University Xi'an China

ISBN: (数字)9798350355895

ISBN: (纸本)9798350355901

In multistatic passive radar systems, addressing the target localization problem based on Bistatic Range Difference, this paper introduces an innovative search algorithm that integrates the Modified Weighted Least Squares with the Artificial Jellyfish Search, termed the MWLS-AJS algorithm. This algorithm is designed to overcome the reliance on a minimum of four transmitters required by current technologies for three-dimensional localization and to enhance the real-time performance of search algorithms. By constructing an innovative pseudo-linear model and applying the iterative search mechanism of the Artificial Jellyfish Search algorithm, the MWLS-AJS algorithm is capable of rapidly and accurately estimating target positions with only three transmitters. Simulation results demonstrate that the algorithm not only maintains a high level of localization accuracy but also shows significant improvements in noise resistance and search efficiency compared to traditional search algorithms.

关键词： Location awareness Resistance Jellyfish Accuracy Transmitters Simulation Noise Signal processing algorithms Search problems Real-time systems

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Low complexity processing method for drilling attitude sensor faults

Low complexity processing method for drilling attitude senso...

引用

Intelligent Control, Measurement and Signal processing and Intelligent Oil Field (ICMSP), International conference on

作者： Yiding Liu Fei Li Gang Qin School of Electronic Information Engineering Xi'an Technological University Weiyang Xi'an China School of Electronic Engineering Xi'an Petroleum University Yanta Xi'an China

ISBN: (数字)9798331516550

ISBN: (纸本)9798331516567

To address the issues of high cost, complex system design, fragile redundant components, and heavy burden on the main controller in traditional attitude measurement while drilling (MWD) sensor fault handling methods, as well as the limitations of current high-complexity algorithms in downhole resources and real-time performance, a low-complexity fault handling approach based on sensor information redundancy is proposed. First, a fault diagnosis theoretical framework and fault tree model are established, focusing on the impact of sensor faults on attitude determination. Next, fault location is diagnosed using the fault tree model, and attitude solving is performed via an algorithm switching strategy to isolate faults and generate accurate attitude parameters. A fault code corresponding to the studied fault conditions is designed, and attitude calculation under sensor fault conditions is validated through hardware-in-the-loop simulation. Experimental results demonstrate that, under hard sensor faults, the proposed fault detection and treatment method ensures attitude calculation meets drilling requirements. Complexity analysis confirms the low computational complexity of the method, ensuring reliable attitude output with acceptable accuracy even under sensor failure.

关键词： Drilling Location awareness Accuracy Attitude control Redundancy Signal processing algorithms Switches Signal processing Real-time systems Fault trees

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Computer-Aided Audit Software Based on Fuzzy Clustering Algorithm

Computer-Aided Audit Software Based on Fuzzy Clustering Algo...

引用

image processing and Computer Applications (ICIPCA), IEEE International conference on

作者： Yuan Fen Wuhan Qingchuan University Wuhan City Hubei Province China

ISBN: (数字)9798350360240

ISBN: (纸本)9798350384161

According to the needs of auditing work, efforts are made to develop suitable computer-aided auditing software to gradually change or enhance traditional auditing techniques and methods, which can better play the role of audit supervision. The purpose of this paper is to study the design and optimisation of computer-aided audit software based on fuzzy clustering algorithms. By analysing the technical difficulties of computer-aided auditing, this paper proposes the design concept of the project software. The improved fuzzy C-mean clustering algorithm DFCM and the fast audit steps of the project based on improved fuzzy clustering are specifically introduced, and the data processing methods of the system are described in detail, and the specific application of the project software is also presented. The experimental results show that the computer-aided audit software in this paper can be applied to calculate the audit price of the project to be audited and the software is feasible.

关键词： image processing Software algorithms Clustering algorithms Quality control Data warehouses Data processing Software Protection Expert systems Optimization

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Comparison and Application of Vehicle Target Detection Methods Based on YOLOv5s and YOLOv7 7

Comparison and Application of Vehicle Target Detection Metho...

引用

7th IEEE International conference on Information systems and Computer Aided Education, ICISCAE 2024

作者： Gu, Chenyu Du, Hong Zhang, xiaozheng Li, Lidan Yang, Zhonglin Liu, Gaotian China Northern Vehicle Research Institute Beijing China

ISBN: (纸本)9798350350760

Currently, the methods for pedestrian detection have undergone significant expansion, yet vehicle target detection still retains immense potential for widespread application in the field of intelligent recognition. Nevertheless, vehicle target detection encounters challenges in terms of detection effectiveness, impacted by factors such as lighting conditions, environmental variations, and occlusions. This study centers on vehicle target detection, aiming to tackle the issues of difficult detection, easy missed detection, and algorithm selection within complex backgrounds. By utilizing the YOLOv5s and YOLOv7 algorithms, we have constructed a dataset that encompasses images featuring vehicles against complex backgrounds and in small scales. This dataset is then used to train the models, which are subsequently employed to perform target recognition for vehicles individually. Through comparative experimentation, we have proven the superiority of the YOLOv7 algorithm in detecting vehicles amidst complex backgrounds and those of small scales. ©2024 IEEE.

关键词： image processing vehicle target detection YOLOv5s YOLOv7

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A Fast image Mosaic Algorithm Based on Feature Partition Extraction

A Fast Image Mosaic Algorithm Based on Feature Partition Ext...

引用

image processing, Electronics and Computers (IPEC), Asia-Pacific conference on

作者： Zhiyou Lian Jianhua Ren School of Electronics and Information Engineering Liaoning University of Engineering and Technology Huludao Liaoning China

ISBN: (数字)9798350374407

ISBN: (纸本)9798350374414

This paper proposes a fast image stitching algorithm based on feature partitioning extraction to address the issues of long processing time, high computational complexity, and poor stitching performance in existing image stitching algorithms. This algorithm is implemented through two stages: optimizing image registration and image fusion. In the image registration stage, feature extraction and accumulation are carried out using image partitioning and an improved Gaussian pyramid layer series method; In the image fusion stage, an improved adaptive weighted average fusion algorithm is used for image fusion operations to improve stitching efficiency and make the image clearer and more natural. Experimental verification shows that the algorithm has strong robustness, significantly improving feature extraction speed and matching rate. Compared with mainstream algorithms, the stitching speed has increased by nearly 2 times, and the image related evaluation indicators have increased by about $5 \%$, basically meeting the real-time and timely needs of image stitching in daily life.

关键词： image registration Deformation Feature extraction Robustness Real-time systems Partitioning algorithms Computational complexity image stitching image fusion image reconstruction

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Green Intelligence: A Sequential CNN Odyssey in Mustard Leaf Disease Detection

Green Intelligence: A Sequential CNN Odyssey in Mustard Leaf...

引用

2024 ASU International conference in Emerging Technologies for Sustainability and Intelligent systems, ICETSIS 2024

作者： Sakshi Sharma, Chetan Sharma, Shamneesh Sharma, Tushar Gochhait, Saikat School of Computer Science and Engineering Sharda University Uttar Pradesh Greater Noida India UpGrad Campus UpGrad Education Private Limited Karnataka Bangalore India School of Computer Science and Engineering Lovely Professional University Punjab Phagwara India Sidtm Symbiosis International Deemed University Maharashtra Pune India Nri Samara State Medical University Russia

ISBN: (纸本)9798350372229

Mustard plants are a crucial agricultural commodity for food and oil production. However, they are frequently vulnerable to various diseases that can substantially reduce crop yield. Early identification and diagnosis of these illnesses are essential for efficient management and control, ensuring sustainable production and agricultural output continuity. This research presents a new method for categorizing mustard leaf diseases using Convolutional Neural Networks (CNNs). The study utilizes sophisticated machine learning algorithms to differentiate between healthy and diseased mustard leaves, which is crucial for maintaining agricultural output and guaranteeing food security. The study involves training CNN architectures - Sequential CNN, ResNet-50, VGG, and AlexNet - on a meticulously curated dataset comprising images of healthy and diseased mustard leaves. The classifier's effectiveness is validated through comprehensive testing, demonstrating significant precision, recall, and F1-score advancements over conventional methods. This approach provides an efficient tool for disease detection in mustard crops and contributes to sustainable agricultural practices, aligning with the global goal of food security and environmental sustainability. © 2024 IEEE.

关键词： Agricultural productivity Crops Data Augmentation image processing Precision Agriculture Sustainable Agriculture

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A Structure-Aware Method for Crowd-Sourced Sparse-to-Dense GPS Trajectory image Generation

A Structure-Aware Method for Crowd-Sourced Sparse-to-Dense G...

引用

2023 IEEE International conference on Multimedia and Expo Workshops, ICMEW 2023

作者： Zhang, Ying Yin, Yifang Zimermann, Roger Yu, Zhiwen Northwestern Polytechnical University Xi'an China A STAR Singapore National University of Singapore Singapore

ISBN: (纸本)9798350313154

Crowdsourced vehicle trajectories are valuable resources to interpret city road networks in a fresh and live manner. Recently, trajectories have been popularly used together with other image data to facilitate various downstream location-based services, among which the very first step is to convert the trajectories data to an image layer. To achieve satisfying results, all these works require densely sampled GPS trajectories which is however sometimes unavailable. So this study explores the possibility to generate dense trajectory images from sparse trajectory data. In order to address the unique features of the trajectory images, we introduce a spatial structure-aware model with a novel triplet-based training strategy and a global-local loss. Experimental results on real-world trajectories show that by using just 1% of trajectory data we can restore most of the original information. © 2023 IEEE.

关键词： Location based services

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Smart Traffic Light Control System Using image processing

Smart Traffic Light Control System Using Image Processing

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2022 International conference on Augmented Intelligence and Sustainable systems, ICAISS 2022

作者： Banu, Asha S.M Lakchida, Soundarya A S Shanthini, V.S. Stinsha, S.L. Sri Krishna College of Engineering and Technology Dept of ECE India

ISBN: (纸本)9781665489621

Crossing the road is one of the major problems, due to the increase of fast-moving vehicles on the road. The challenges in the existing techniques utilized for traffic control can be overcome by using the Smart Traffic Light Control System using image processing, proposed in this paper and allowing pedestrians to walk on busy roads conveniently. It is found that the Canny Edge Detection Technique is a very effective method among the various edge detection algorithms. The suggested method reduces the waiting time in zebra crossing by immediately controlling the traffic light and gives more time for elderly and handicapped pedestrians to cross the roads safely even during heavy traffic. When compared to all the traditional techniques, image processing is an efficient method for traffic control. This technique removes the usage of unwanted hardware like sensors which are used to sense noises. This prevents the wastage of time for vehicles which is more essential for emergency vehicles. The output of the code is obtained by image matching. The results are shown in three scenarios: less traffic, moderate traffic, and more traffic. © 2022 IEEE.

关键词： Roads and streets

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