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

共 12901 条记录，以下是391-400 订阅

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Implementation of an Efficient image Inpainting Algorithm using Optimization Techniques 6th

Implementation of an Efficient Image Inpainting Algorithm us...

引用

6th International conference on Soft Computing and Signal processing, ICSCSP 2023

作者： Revathi, K. Janardhana Rao, B. Odugu, Venkata Krishna Gade, Harish Babu Sphoorthy Engineering College Hyderabad India CVR College of Engineering Hyderabad India

ISBN: (纸本)9789819984503

To repair the demolished images and remove the particular unnecessary objects in the image, optimized image inpainting techniques are required. In this work, a novel exemplar-based image inpainting technique is suggested. In this technique, the patch priority is computed using the regulation factor and coefficients. Two optimization techniques as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) techniques are employed to attain the optimal values of regularization factor and coefficients. The best exemplar patch selection is carried out by calculating the sum of the absolute difference between the patches. Performance measures including peak-signal-to-noise ratio (PSNR), mean square error (MSE), and Structural Similarity Index (SSIM) are tested using the suggested image inpainting process on images based on datasets. These results are compared with the available inpainting methods. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Genetic algorithms

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image Reconstruction Leveraging Time-Event Feature Fusion for Event Cameras 7

Image Reconstruction Leveraging Time-Event Feature Fusion fo...

引用

7th International conference on Pattern Recognition and Artificial Intelligence, PRAI 2024

作者： Zhang, Jian Wu, Sheng Liu, Wenwei Feng, Hui Hu, Bo School of Information Science and Technology Fudan University Shanghai200433 China Shanghai Institute of Intelligent Electronics & Systems Shanghai200433 China

ISBN: (纸本)9798350350890

The event cameras generate asynchronous event sequences, rendering most existing image-based algorithms in-applicable for direct use and processing. Therefore, the development of a simulator that utilizes event streams captured by an event camera as input and reconstructs image sequences as output is crucial for subsequent tasks such as high-speed moving object tracking, object recognition and detection, and SLAM. Despite the extensive research and attention garnered by deep learning-based image sequence generation, there remains a problem of local representation information loss during the reconstruction process from event streams to image sequences. Existing solutions, whether based on Stacking Based on Time (SBT) or Stacking Based on Events (SBE), exhibit significant limitations when using a single stacking approach. To address the insufficiency in feature representation capability, this paper proposes a visual image conversion method based on multi-view feature fusion, effectively transforming event streams into traditional image sequences. Extensive experiments and dataset validations, utilizing multiple evaluation metrics including both global and local assessments, demonstrate the advantages of our proposed method. © 2024 IEEE.

关键词： image reconstruction

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Deep Learning-Based Noise Reduction Techniques in Electronic Signal processing 9

Deep Learning-Based Noise Reduction Techniques in Electronic...

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9th International conference on Science, Technology, Engineering and Mathematics, ICONSTEM 2024

作者： Johari, Lalit Ramya, P. Suganya, M. Praveena, Hirald Dwaraka Lathamageshwari, P.S. Rajendiran, M. Iftm University Department of Computer Applications Uttar Pradesh Moradabad244102 India Bannari Amman Institute of Technology Department of Electronics And Communication Engineering Tamil Nadu Sathyamangalam638401 India Annapoorana Engineering College Department of Electronics And Communication Engineering Tamil Nadu Salem636308 India Department of Electronics And Communication Engineering Andhra Pradesh Tirupati517102 India Tamil Nadu Kavaraipettai601206 India Panimalar Engineering College Department of Computer Science And Engineering Tamil Nadu Chennai600123 India

ISBN: (纸本)9798350365092

This paper explores the operation of deep literacy- grounded noise reduction ways in electronic signal processing. Noise hindrance poses a significant challenge in colorful signal processing operations, impacting the delicacy and trustability of data analysis and interpretation. Traditional noise reduction styles frequently calculate on heuristic approaches or signal processing algorithms, which may have limited effectiveness, especially in complex and dynamic surroundings. In discrepancy, deep literacy algorithms, similar as convolutional neural networks(CNNs) and intermittent neural networks(RNNs), offer promising results for noise reduction by learning complex patterns and connections directly from data. This paper determines the state- of- the- art deep literacy- grounded noise reduction ways, including denoising autoencoders, generative inimical networks(GANs), and intermittent neural network- grounded models. Case studies and experimental results demonstrate the effectiveness and performance of these ways in colorful signal processing tasks, similar as audio denoising, image restoration, and biomedical signal processing. The integration of deep literacy- grounded noise reduction styles into electronic signal processing systems shows significant eventuality for perfecting signal quality and enhancing the delicacy of data analysis in different operations. © 2024 IEEE.

关键词： Recurrent neural networks

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Research on image Encryption Algorithm Based on One-dimensional Logistic and Two-dimensional Hénon Chaotic System

Research on Image Encryption Algorithm Based on One-dimensio...

引用

2022 International conference on Computer Graphics, Artificial Intelligence, and Data processing, ICCAID 2022

作者： Wu, Xionghui Dong, Rui Yang, Kuo Zhang, Wenli PLA Beijing100043 China Taiyuan University of Technology Taiyuan030024 China

ISBN: (纸本)9781510663350

Aiming at the problems of high leakage risk and serious information loss that may exist in the encryption and decryption of digital images, an image encryption and decryption algorithm based on chaos theory is proposed. The algorithm introduces both one-dimensional Logistic mapping and two-dimensional Hénon mapping. In the encryption process, the digital image is dislocation encrypted by Logistic mapping and diffusion encrypted by Hénon mapping, and finally the cipher image is obtained. Compared with other similar algorithms, this algorithm has the advantages of low algorithm complexity and high operation efficiency. The simulation experiment is carried out on the MATLAB platform, and the results show that the algorithm can meet the test standard in the field of digital image encryption. © 2023 SPIE.

关键词： Chaotic systems

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Application of Particle image Velocimetry Method Based on Full Convolution Neural Network in Turbulence Field 16

Application of Particle Image Velocimetry Method Based on Fu...

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16th IEEE International conference on Computational Intelligence and Communication Networks, CICN 2024

作者： Xie, Zhicheng Guo, Shuqiang School of Computing Northeast Electric Power University Jilin China

ISBN: (纸本)9798331505264

Exploring fluid flow phenomena has always been a hot topic in fluid mechanics research. Particle image Velocimetry (PIV) is a non-contact technique applied in fluid mechanics laboratories for measuring the velocity field of fluids. The core of PIV lies in extracting displacement vector information from particle image pairs to ultimately generate a two-dimensional velocity field. Traditional methods typically estimate the two-dimensional velocity field using cross-correlation algorithms and optical flow techniques. In recent years, with the rapid development of artificial intelligence technologies and their high compatibility with PIV in image processing, there is significant potential and research value in designing deep learning techniques for accurately estimating fluid velocity vector fields in particle image velocimetry. Compared to traditional methods, the PIV technique proposed in this paper, based on fully convolutional neural networks, not only maintains the accuracy of velocity field estimation but also significantly enhances resolution and computational efficiency. Experiments demonstrate that the proposed method exhibits higher accuracy and stronger generalization capabilities. © 2024 IEEE.

关键词： Optical flows

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Analysis of the Noise in ECG Recordings on Different Devices 62

Analysis of the Noise in ECG Recordings on Different Devices

引用

62nd Annual conference of the Society-of-Instrument-and-Control-Engineers (SICE)

作者： Felix-Chavez, Andres Ikeura, Ryojun Hayakawa, Soichiro Mie Univ Grad Sch Engn Mie Japan

ISBN: (纸本)9784907764807

Cardiovascular diseases are one of the leading causes of mortality. Advances in technology have improved the monitoring of patients. However, these devices are still sensitive to noise from movement, therefore it is important to understand how the movement affects electrocardiographic recordings. In this research, three devices were tested. The signal-to-noise ratio (SNR) was used to determine the quality of the ECG recordings from each device. The Vitalgram system was the only device to present a positive average SNR value for EMA while the subjects were running. In Apandi's research the performance of several heartbeat detection algorithms was tested. Using Apandi's research data and the SNR values from this research, the performance of these algorithms on recordings from these devices was estimated.

关键词： Medical and Welfare systems Signal an/or image processing Electrocardiogram Noise Wavelet

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Modelling and Simulation Framework for ATR Design Evaluation 19

Modelling and Simulation Framework for ATR Design Evaluation

引用

conference on Electro-Optical and Infrared systems - Technology and Applications XIX

作者： Hickman, Duncan L. Koh, Eunjin Lee, Jaekyu Yoo, Hyunjung Baek, Jeonghyun Tektonex Ltd Argyll Rd Kilcreggan Argyll & Bute England Agcy Def Dev 160 Bugyuseong Dero 488beon Gil Daejeon South Korea

ISBN: (纸本)9781510655461

Automatic Target Recognition (ATR) and target tracking are fundamental functions in many military systems and so have a significant impact on a sensor system's performance. In response to the demand for increased capability, ATR designs have evolved from relatively simple filters to increasingly complex algorithms, using techniques such as artificial intelligence. Assessing the performance of image processing algorithms is a significant challenge, particularly with their increased design complexity. Increasing the complexity of a processing design tends to result in greater sensitivity to variations in scene conditions, rendering the system performance more nuanced with respect to the image content. There is a need to develop modelling and simulation design tools that better reflect the impact of image processing on the overall system performance when subjected to a wide variation in input scene and sensor platform characteristics. In this paper, the development and design of the System Performance Model (SPM) is described which provides the modelling and simulation of different image processing algorithms such as ATR. The approach taken within the SPM is to use real imagery and convert this to imagery that would be generated by the modelled camera. This process, which is described in the paper, is critical to the design of the SPM and underpins its effectiveness and accuracy. Example results are given that illustrate the design of the SPM's image conversion process.

关键词： Infrared Sensor Modelling image Simulation image Flow Models Statistical Models Infrared Camera Performance ATR Trials imagery image Restoration image Conversion image Metrics

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Efficiency Evaluation of Noise Based Camera Measurements algorithms

Efficiency Evaluation of Noise Based Camera Measurements Alg...

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2023 systems of Signals Generating and processing in the Field of on Board Communications, SOSG 2023

作者： Egorov, Dmitry Egorova, Anastasia Potashnikov, Aleksey Moscow Technical University of Communications and Informatics Moscow Russia

ISBN: (纸本)9798350397727

Nowadays digital cameras are being used in many practical applications. Therefore, problem of parameter estimation and quality evaluation becoming more and more significant. Recently computational photography trend become more notable and many devices started to use advanced algorithms to mask out weak characteristics of hardware. This makes traditional deterministic approaches of measurement less relevant. But random methods used these days have limitations too. This article compares measurement approaches and highlights limitation of each case and brings recommendation for measuring process creating foundation for future measuring method development. © 2023 IEEE.

关键词： image resolution

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Effectiveness of image processing and Different Machine Learning Models in Classifying Local Soybean Varieties in the Philippines 12

Effectiveness of Image Processing and Different Machine Lear...

引用

12th IEEE conference on systems, Process and Control, ICSPC 2024

作者： Dioses, Isaac Angelo M. Salum, Romero Dante Nayga, Desiray Asuncion, Mark Joseph Dioses, Jesusimo L. Castillo, Wendell M. MAPUA University School of Information Technology Makati Campus Metro Manila Makati Philippines Isabela State University College of Computing Studies Information and Communication Technology San Fabian Echague Isabela Philippines

ISBN: (纸本)9798350391398

Deceptive providers offering inferior products threaten the integrity of soybean exportation and product quality. To uphold fair trade standards and protect consumer rights, it is essential to classify and trace different soybean varieties accurately. Implementing stringent legislation and reliable technology for crop origin identification is crucial in maintaining order in the soybean trading market. This study uses artificial intelligence, specifically machine learning, image processing, and computer vision, to develop a standard model for soybean classification. Researchers collected two bags of soybeans from CVRC Cagayan at Ilagan Isabela, resulting in a dataset of 1562 soybean images, with 810 images of PSB SY2 and 752 images of CL1 Soy. The study employed Support Vector Machine (SVM) and K-Nearest Neighbors (KNN) algorithms to create models for classifying and predicting soybean varieties. The SVM model achieved an accuracy of 88.2%, while the KNN model, using the FINE KNN preset, outperformed with an accuracy of 94.4%. Although the KNN algorithm exhibited slower training speed and time, it demonstrated superior accuracy over the SVM model, as evidenced by its confusion matrix. Feature selection using the MRMR algorithm identified perimeter and equivalent diameter as the most significant features for soybean classification, while minor axis length was deemed the least important. To improve the precision and dependability of soybean variety classification and safeguard customer interests, this research emphasizes the potential of machine learning approaches in conjunction with image processing and morphology feature extraction. © 2024 IEEE.

关键词： Support vector machines

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Evolution of real-time processing of visual information over four decades: a retrospective as outlook to the future of real-time imaging

Evolution of real-time processing of visual information over...

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Real-time processing of image, Depth and Video Information 2023

作者： Carlsohn, Matthias F. Engineering and Consultancy Dr. Carlsohn for Computer Vision and Image Communication Bremen Germany

ISBN: (数字)9781510662636

ISBN: (纸本)9781510662629

The expectations and demands for real-time performance for processing of visual information usually overloaded contemporary computer systems at all times. Increasing hardware performance enabled the use of more complex analysis and vice versa. For a long time, this led to a mutual fertilization of electronics and computer programs or architectures and algorithms with coherent data structures. Appropriate tool sets marked corner stones and boosted some significant developments. However, up to now one got always the impression that the requirements were always heading the possible performance and the open question becoming more serious is: where will it end? This paper provides a short rush through four decades of real-time image processing with a conclusion for an outlook into future opportunities and current developments providing guidelines to host corresponding research results by this conference in the coming years. New concepts, programming paradigms and production technologies are paving the way for future image processing solutions providing real-time capabilities. © 2023 SPIE.

关键词： Parallel architectures

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