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

共 13657 条记录，以下是741-750 订阅

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Development of a Procedure for Improving the Effectiveness of Personal Identification systems Based on the Analysis of Facial images 17

Development of a Procedure for Improving the Effectiveness o...

引用

17th International Scientific and Technical conference on Dynamics of systems, Mechanisms and Machines, Dynamics 2023

作者： Tatarkanov, A.A. Umyskov, A.A. Kuklin, V. Zh. Institute of Design and Technology Informatics of RAS Moscow Russia

ISBN: (纸本)9798350358315

This research aims to develop a new procedure to improve the performance of the personal identification system. This process will be based on the analysis of digital facial images using special artificial intelligence technologies. Additionally, it is emphasized that the successful development of a completely new neural network algorithm for personality identification and its special robust modification are required to achieve this goal. Furthermore, it is essential that this algorithm demonstrates increased effectiveness in identifying faces. As part of this algorithm, two key components are distinguished, namely, an algorithm aimed at determining the area where a face is located in an image, which involves the use of a standard version of a convolutional neural network. And the presented neural network algorithm is the second component, which is designed for personal identification with a specific robust modification. The studies presented have shown that an algorithm with a proposed architecture, will have around 25 times less weight parameters than the algorithms utilized at present. Also, unlike other algorithms, it was possible to improve the level of accuracy. © 2023 IEEE.

关键词： image enhancement

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Dynamic Scene Representation for Docking in Urban Waters Using a Stereo Camera 6

Dynamic Scene Representation for Docking in Urban Waters Usi...

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International Maritime and Port Technology and Development conference (MTEC) / 6th International conference on Maritime Autonomous Surface Ships (ICMASS)

作者： Nygard, Trym Anthonsen Brekke, Edmund Forland Mester, Rudolf Stahl, Annette Norwegian Univ Sci & Technol NTNU Dept Engn Cybernet Trondheim Norway Norwegian Univ Sci & Technol NTNU Dept Comp Sci Trondheim Norway

To navigate and dock safely in urban waters, an autonomous ferry must assess its safe navigation paths by identifying navigable free space and potential obstacles. A deep understanding of its surroundings is crucial for situational awareness. Knowing which objects are static and dynamic is an indispensable ingredient for path planning algorithms and collision avoidance systems, and is especially useful for docking operations, as moving obstacles can interfere with the optimal path to the dock. To handle all types of obstacles, we present a novel dynamic scene representation for docking in urban waters using a short baseline stereo camera. Obstacles protruding from the water surface are represented with vertically oriented rectangles, known as stixels. The stixels are tracked over consecutive frames with dense optical flow. Together with stereo correspondences, their 3D motion is estimated. Stixels representing the same object are grouped together into line segments which are classified as either dynamic or static based on the motion of its associated stixels. Our dynamic representation presents objects in the 3D camera coordinate system as a bird's eye view map. Additionally, stereo depth uncertainty can significantly impact depth estimates and is considered using a Kalman filter, providing smooth position and velocity estimates. We test our dynamic scene representation on a real docking scenario recorded with an autonomous ferry using a stereo camera. We evaluate the accuracy of the reconstructed 3D scene points and the velocity estimates of the dynamic objects using LiDAR and GNSS.

关键词： Stereo image processing

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Development of UAV image processing algorithms for Early Detection of Fires in Natural Ecosystems

Development of UAV Image Processing Algorithms for Early Det...

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IEEE International conference on Actual Problems of Unmanned Air Vehicles Developments Proceedings (APUAVD)

作者： Volodymyr Hnatushenko Tetiana Bulana Bohdan Molodets Daniil Boldyriev Information Technologies & Computer Engineering Department Dnipro University of Technology Dnipro Ukraine

ISBN: (数字)9798331534141

ISBN: (纸本)9798331534158

The article discusses image processing algorithms for creating a full-fledged fire detection system based on UAV collections. The wildfire detection issue is solved using artificial intelligence: YOLOv8 model. The fire classification based on the fuel map obtained using LiDAR data was also implemented. The scheme of the information system that will perform detection and classification is proposed. This information system is useful at the decision-making stage to determine the strategy and tactics of firefighting. With several improvements, the system can be used to process incoming data in real time.

关键词： Wildfires Laser radar image processing Ecosystems Autonomous aerial vehicles Real-time systems Classification algorithms Fuels Monitoring Information systems

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Automated Pneumonia Detection from Chest X-rays using Convolutional Neural Networks: Advancements, Optimization, and Performance Analysis 2

Automated Pneumonia Detection from Chest X-rays using Convol...

引用

2nd International conference on Sustainable Computing and Smart systems (ICSCSS)

作者： Bhuria, Ruchika Gill, Kanwarpartap Singh Upadhyay, Deepak Devliyal, Swati Chitkara Univ Chitkara Univ Inst Engn & Technol Rajpura Punjab India Graph Era Hill Univ Comp Sci & Engn Dehra Dun 248002 Uttarakhand India Graph Era Deemed Univ Comp Sci & Engn Dehra Dun 248002 Uttarakhand India

ISBN: (纸本)9798350391558;9798350379990

Pneumonia, an almost fatal bacterial disease generally affecting one or both lungs and brought on by the bacterium Streptococcus pneumonia, can strike any human. The World Health Organisation (WHO) reports that pneumonia accounts for one in three fatalities in India. Chest X-rays are used to detect pneumonia, require the examination of qualified radiotherapists. Establishing an automated approach to identify pneumonia would therefore be advantageous to treat the illness as soon as feasible, particularly in distant places. Convolutional Neural Networks (CNNs) have attracted a lot of interest for disease diagnosis because of the effectiveness of deep learning algorithms in evaluating medical imagery. Higher accuracy, scalability, and automation opportunities are only a few of the benefits of the suggested CNN-based approach over conventional methods. This study proposes to use deep learning methods to find intricate patterns and characteristics from medical imaging data that are suggestive of pneumonia, hence enhancing diagnosis accuracy. Additionally, picture categorization jobs benefit much from features obtained from big datasets using pre-trained CNN models. This study assesses the capability of these models in this work to diagnose abnormal and normal chest X-rays using pre-trained CNN models as feature extractors and various classifiers subsequently. There is an analytical identification of the optimal CNN model for the task.

关键词： Machine Learning image processing CNN model Classifier Evaluation Artificial Intelligence pneumonia Techniques Diseases Population Resources Medical Health

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Research on Traditional Art image Reconstruction Method Based on Computer Vision Analysis

Research on Traditional Art Image Reconstruction Method Base...

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Artificial Intelligence and Autonomous Robot systems (AIARS), International conference on

作者： Xunmiao Ruan Guangdong University of Science &Technology Dongguan Guangdong China

ISBN: (数字)9798350376173

ISBN: (纸本)9798350376180

In the information age, image processing technology has become prevalent across various domains. To enhance image correction, computer vision algorithms can be employed. Traditional methods for structural system identification rely on wired or wireless measurement systems for data gathering, which can be cumbersome and time-consuming due to the need for arranging sensors and data collection equipment. The proposed system involves two primary steps: line drawing extraction and rendering. During the extraction phase, an edge detection technique that integrates low and middle-level visual information is utilized. Based on the results of traditional edge detection, the edges are simplified and connected using computer vision principles. This approach treats image processing as the focal point and aims to establish a scientific model for distorted images. image restoration can be facilitated through sample image filtering and noise reduction techniques. Additionally, this article delves into the principles and associated technologies of computer vision, analyzing patterns of visual interaction. Chinese traditional art imagery, as a cultural medium and symbol, fulfills an artistic communication function while preserving the nation's rich cultural heritage. The image processing techniques grounded in computer vision algorithms offer numerous advantages and superior accuracy.

关键词： Computer vision Visualization Art Machine learning algorithms image edge detection Distortion Real-time systems Global communication Cultural differences image reconstruction

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algorithms for image processing of Micro-Objects of Medical Diagnostics systems

Algorithms for Image Processing of Micro-Objects of Medical ...

引用

International Russian Smart Industry conference (SmartIndustryCon)

作者： Isroil I. Jumanov Rustam A. Safarov Department of “Artifical intellegence and information systems” Samarkand State University named after Sharof Rashidov Samarkand Uzbekistan Department of Control Theory and Information Security Samarkand State University named after Sharof Rashidov Samarkand Uzbekistan

ISBN: (数字)9798331511241

ISBN: (纸本)9798331511258

Constructive approaches, principles, models for optimizing the identification of micro-objects based on the use of statistical, dynamic models with mechanisms for filtering noise, foreign particles on images of medical objects and pollen grains have been developed. Methods for optimizing the identification of micro-objects with the selection of characteristic objects in the image, the combination of image models with the mechanisms of segmentation, filtering, transformation, and alignment of the laser image processing zone with the CAD model are proposed. algorithms for selecting the contours of objects on an image using a border detector in the transverse direction to each vector of the CAD model have been developed. Modeling of images of microsamples for medical diagnostics of chest diseases was carried out. The width, straightness of the boundaries of structural objects, local defects, parameters of regulation and synchronization of the components of the vision system are determined. algorithms for image processing under conditions of a priori insufficiency, uncertainty of parameters, and low accuracy of data processing are studied. A mechanism for suppressing impulse noise and noise is implemented based on various filtering methods, preserving the boundaries of objects and small-sized parts. Mathematical expressions for estimating identification errors due to non-stationarity, inadequacy of approximation, interpolation, extrapolation of the image contourare obtained, which are synthesized with cubic, biquadratic, interpolation spline functions and wavelet transforms. A software package for recognition and classification of micro-objects has been developed.

关键词： Solid modeling Interpolation image segmentation Filtering Measurement by laser beam Laser modes Vectors Object recognition Synchronization Medical diagnosis

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Energy Efficient Approximate Bfloat-16 Floating Point Division Hardware for image processing

Energy Efficient Approximate Bfloat-16 Floating Point Divisi...

引用

Smart Electronics and Communication systems (ISENSE), International conference on

作者： M Nagakalyan G. Sujatha Noor Mahammad Sk Dept. of ECE Sri Venkateswara College of Engineering Tirupati India Dept. of CSE IIITDM Kancheepuram Chennai India

ISBN: (数字)9798331528126

ISBN: (纸本)9798331528133

Energy efficient designs are need of the hour and image processing applications are error tolerant application. Where the error present in the computing does not impact the output visual quality. This work proposes an efficient approach to design a Bfloat floating point division. This work proposes three algorithms that are implemented at the hardware level. All the proposed algorithms will produce lesser error in the output and does not impact the output visual quality. The proposed work reduces the energy sianlficantly than the existing works.

关键词： Visualization Power demand image coding Error analysis Transform coding Approximation algorithms Hardware Energy efficiency Delays Standards

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Advancing image processing through Cutting-Edge Optimization Methods: State-of-the-Art Techniques and Applications

Advancing Image Processing through Cutting-Edge Optimization...

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Self Sustainable Artificial Intelligence systems (ICSSAS), International conference on

作者： Usman Ahmad Usmani Junzo Watada Mohammed Umar Usmani Universiti Teknologi Petronas Waseda University Shinjuku City Tokyo Japan University of Malaysia Pahang

ISBN: (数字)9798350368413

ISBN: (纸本)9798350368420

In the image processing domain, the growth of digital data has intensified the need for efficient and robust optimization techniques. This research study aims to develop and evaluate advanced optimization methods tailored specifically for improving the performance of image processing tasks. It explores the latest advancements in optimization algorithms, including evolutionary algorithms, metaheuristic approaches, and deep learning-based optimization techniques. The study provides an in-depth analysis of these methods, elucidating their strengths, weaknesses, and areas of applicability across diverse image processing tasks such as image denoising, image reconstruction, image segmentation, and image enhancement. By comparing their performance through comprehensive experiments, the paper demonstrates substantial improvements in computational efficiency, accuracy, and generalization. These results highlight the potential of optimization methods to significantly enhance the quality and speed of image processing pipelines, opening new avenues for breakthroughs in computer vision, medical imaging, remote sensing, and other domains. Ultimately, this research not only empowers practitioners with cutting-edge tools but also paves the way for future exploration in the application of optimization techniques within image processing.

关键词： image segmentation Computer vision image processing Pipelines Metaheuristics Optimization methods Evolutionary computation Computational efficiency Remote sensing image reconstruction

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algorithms for image processing of Micro-Objects of Medical Diagnostics systems

Algorithms for Image Processing of Micro-Objects of Medical ...

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2025 International Russian Smart Industry conference, SmartIndustryCon 2025

作者： Jumanov, Isroil I. Safarov, Rustam A. Samarkand State University named after Sharof Rashidov Department of 'Artifical intellegence and information systems' Samarkand Uzbekistan Samarkand State University named after Sharof Rashidov Department of Control Theory and Information Security Samarkand Uzbekistan

ISBN: (纸本)9798331511241

关键词： image segmentation

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Optical Stealth Algorithm Under Photoelectric Countermeasures and Its Effectiveness Evaluation 18th

Optical Stealth Algorithm Under Photoelectric Countermeasure...

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18th International conference on Intelligent Information Hiding and Multimedia Signal processing, IIH-MSP 2022

作者： Yang, Zhonglin Jiang, Yutong Li, Junbao Li, Qiong Department of Automatic Test and Control School of Electronics and Information Engineering Harbin Institute of Technology Harbin150080 China China North Vehicle Research Institute 4 HuaiShuling Fengtai District Beijing China

ISBN: (纸本)9789819901043

With the diversification of reconnaissance equipment and methods in the military field, optical stealth technology has become a hot spot in military research under the operational needs of optoelectronic confrontation. An improved self-adaptive visible light and infrared waveband stealth algorithm is proposed here, and its effectiveness under photoelectric confrontation is evaluated. The current digital camouflage design method is mainly through background color mixing, image segmentation, spot combination, etc. It has the defects of smooth and clear edge contour, fixed color/texture scene, and cannot adapt to complex texture background or multiple types of scenes. An improved digital camouflage design method based on fuzzy C-means clustering (FCM) image processing technology is proposed to obtain the color characteristics of the background image. Then, the color block types of the camouflage spots are acquired to reduce the loss of texture information of the background image caused by clustering or segmentation to avoid the phenomenon of clear boundaries caused by single region segmentation. The results show that the use of adaptive optical stealth algorithms in the visible and infrared bands can reduce the probability of being discovered in optoelectronic countermeasures, thereby gaining a head start. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： image enhancement

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