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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81-90 订阅

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Face Recognition Implementation Based on image processing Techniques 2

Face Recognition Implementation Based on Image Processing Te...

引用

2nd International conference on Signal processing and Intelligent Computing, SPIC 2024

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

ISBN: (纸本)9798350368888

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. © 2024 IEEE.

关键词： MATLAB

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FPGA Based image processing: A Comparative Study of Software-Centric and Hardware-Accelerated Approaches

FPGA Based Image Processing: A Comparative Study of Software...

引用

2024 International conference on Smart Electronics and Communication systems, ISENSE 2024

作者： Parameswaran, P.N. Janardan, S. Nair, Siddharth R Thejaswitha, K.T. Nikhil, M. Adersh, V.R. College of Engineering Trivandrum Dept of Electronics and Communication Thiruvananthapuram India

ISBN: (纸本)9798331528126

This work compares two different approaches to image processing algorithm implementation in Zynq Zybo and Zedboard Field Programmable Gate Array (FPGA) boards. There are three main phases for the study, namely, Hardware-Accelerated image processing (HAIP), Software-Centric image processing (SCIP), and an in-depth analysis of their corresponding performance metrics. image processing algorithms were implemented in the SCIP phase, exclusively using the Zynq processing System (PS). On the other hand, the HAIP phase comprised creating distinct Intellectual Properties (IPs) for image processing tasks and integrating them with the Zynq PS through Direct Memory Access (DMA) and the Advanced eXtensible Interface (AXI) *** all assessed techniques, HAIP considerably outperformed SCIP in terms of processing time, for different image sizes, across both Zynq Zybo and Zedboard. On the other hand, as SCIP is software-centric, it showed minimal resource utilization and lower power consumption than HAIP, which showed higher resource utilization and power consumption. However, both methods produced processed images that were similar, highlighting the stability and dependability of FPGA-based image processing implementations. A comparative analysis between Zynq Zybo and Zedboard reveals insights into how different FPGA architectures impact the performance and resource utilization of image processing implementations. This work offers insights into the trade-offs between hardware-accelerated and software-centric approaches to image processing on FPGA platforms, guiding future design decisions for practical uses. © 2024 IEEE.

关键词： image analysis

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Enhanced Multilingual image Captioning: Integrating Text-to-Speech Translation and Sentiment Analysis

Enhanced Multilingual Image Captioning: Integrating Text-to-...

引用

2024 International conference on Innovative Computing, Intelligent Communication and Smart Electrical systems, ICSES 2024

作者： Reddy, Tanuja Konda Veeksha, S. Kavitha, C.R. Amrita School of Computing Department of Cse Bengaluru India

ISBN: (纸本)9798331543617

The aim of this project is to create a system that will improve the way we interact with text and images by using the capabilities of computer vision and natural language processing. The main purpose of using this system to generate human-readable image captions is to train a model that can accurately describe an image's contents. The project extends the functionality of the image captioning system by adding language translation inorder to give a multilingual support. The use of a few pre-trained models will enable users with varying language backgrounds use this system to acquire captions in different target languages. This involves integrating language translation techniques into the system and training different models for every target language. Further we extend the project by working in the field of sentiment analysis by identifying the sentiment (positive, negative, or neutral) of captions by examining text and images. For a better understanding of the emotional tone of the information, the system combines CNNs with natural language processing (NLP) algorithms for image analysis and text analysis. © 2024 IEEE.

关键词： Natural language processing systems

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A Novel Artistic image Compression Algorithm Based on Multi-Scale Adaptive Discrete Wavelet Transform

A Novel Artistic Image Compression Algorithm Based on Multi-...

引用

2025 International conference on Multi-Agent systems for Collaborative Intelligence, ICMSCI 2025

作者： Li, Yijun China Academy of Art Yuhang District Zhejiang Hangzhou311100 China

ISBN: (纸本)9798331509828

How to compress information is a challenge in the digital age, and the image compression has a wide range of application scenarios. In order to solve the challenges of low compression efficiency and high loss rate of the traditional algorithms, this study proposes a compression algorithm based on multi-scale adaptive discrete wavelet transform. The core of the proposed algorithm is to make reasonable use of the multiresolution analysis characteristics of discrete wavelet transform. Based on the feature extraction, the image information is decomposed into high-frequency and low-frequency parts. This operation can stably and effectively implement frequency domain threshold processing and reduce redundant data. The proposed algorithm optimizes the encoding efficiency of image features to the greatest extent by introducing block difference features and designing a new iterative function system. In view of the high redundancy and high complexity of the artistic images, the traditional wavelet analysis is improved and optimized, and a multi-scale adaptive model is introduced. In the experiment, the test used multiple sets of artistic image test sets and compared them with mainstream algorithms (JPEG, VAE, etc.). In PSNR analysis, the proposed algorithm achieves better performance. © 2025 IEEE.

关键词： Discrete wavelet transforms

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Enhancing Blurred image processing with IoT Integration for Improved Clarity 2

Enhancing Blurred Image Processing with IoT Integration for ...

引用

2nd IEEE International conference on Emerging Research in Computational Science, ICERCS 2024

作者： Tummalapalli, Geetamma Summia Parveen, H. Ramesh, S.M. Monica, P. Santhiya, B. Rajasekaran, Arun Sekar GMR Institute of Technology Department of Electronics and Communication Engineering Rajam India Sri Eshwar College of Engineering Department of Computer Science Engineering Coimbatore India KPR Institute of Engineering and Technology Department of Electronics and Communication Engineering Coimbatore India GITAM Deemed to be University Department of Electronics and Communication Engineering GST Visakhapatnam India Bannari Amman Institute of Technology Department of Information Technology Sathyamangalam India SR University Department of Electronics and Communication Engineering Warangal India

ISBN: (纸本)9798331534950

A blurred image is an image that has undergone a blurring or smoothing effect, resulting in a loss of sharpness and clarity. Blurring is a technique used in image processing to reduce noise, remove unwanted details, or create a visual effect. It involves averaging or blending neighboring pixels to create a smoother appearance. The specific processing techniques and algorithms used will depend on the nature and extent of the blur, the intended outcome, and the available software or programming tools. It's important to experiment with different methods and parameters to achieve the desired result. IoT (Internet of Things) can be used in image processing in several ways to enhance functionality, efficiency, and data processing capabilities enhances image processing by enabling real-time analysis, edge computing capabilities, integration with other IoT devices, and remote monitoring and control. These advancements facilitate applications such as object detection, image recognition, and real-time decision-making, contributing to more efficient and intelligent systems in various domains. Here is a proposed model for blurred image processing with IoT. This proposed model demonstrates the integration of IoT devices, image processing techniques, and cloud-based analytics to address the challenges of blurred image processing. It combines edge processing for real-time analysis and cloud-based processing for more complex algorithms, enabling efficient and intelligent image processing applications in various domains. © 2024 IEEE.

关键词： Edge computing

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Implementation of Intelligent Robotic systems for Pick and Place based on image processing 14

Implementation of Intelligent Robotic Systems for Pick and P...

引用

14th Asian Control conference (ASCC)

作者： Kang, Sang-Won Um, Tae-Wook Park, Nam-Jin Ahn, Hyo-Sung Gwangju Inst Sci & Technol Sch Mech Engn Gwangju South Korea

ISBN: (纸本)9798331540845;9789887581598

This paper introduces an intelligent delta robot system enhanced with image processing to optimize Pick & Place operations in Agricultural Produce Centers (APCs). Facing a critical demand for mechanization in agriculture due to a shrinking rural workforce, our system utilizes camera-based segmentation and depth estimation to efficiently automate the packaging of fruits and vegetables. It concentrates on essential tasks such as precise gripping and ungripping, supported by advanced camera-based visual sensors. Integrating these vision technologies with delta robot kinematics and specialized image processing algorithms allows the robot to execute highly accurate movements. Our implementation showcases significant enhancements in the efficiency and reliability of APC operations, advancing the field of agricultural robotic automation and establishing a new standard for future developments in automated food production.

关键词： Delta parallel robot automation image processing depth estimation instance segmentation

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Are Natural Domain Foundation Models Useful for Medical image Classification?

Are Natural Domain Foundation Models Useful for Medical Imag...

引用

IEEE/CVF Winter conference on Applications of Computer Vision (WACV)

作者： Huix, Joana Pales Soderberg, Magnus Ganeshan, Adithya Raju Matsoukas, Christos Haslum, Johan Fredin Smith, Kevin KTH Royal Inst Technol Stockholm Sweden Sci Life Lab Stockholm Sweden AstraZeneca Gothenburg Sweden

ISBN: (纸本)9798350318920;9798350318937

The deep learning field is converging towards the use of general foundation models that can be easily adapted for diverse tasks. While this paradigm shift has become common practice within the field of natural language processing, progress has been slower in computer vision. In this paper we attempt to address this issue by investigating the transferability of various state-of-the-art foundation models to medical image classification tasks. Specifically, we evaluate the performance of five foundation models, namely SAM, SEEM, DINOv2, BLIP, and OPENCLIP across four well-established medical imaging datasets. We explore different training settings to fully harness the potential of these models. Our study shows mixed results. DINOv2 consistently outperforms the standard practice of imageNET pretraining. However, other foundation models failed to consistently beat this established baseline indicating limitations in their transferability to medical image classification tasks.

关键词： algorithms algorithms and algorithms Applications Biomedical / healthcare / medicine Datasets and evaluations formulations Machine learning architectures

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Design of piezoelectric energy harvesters for cardiac applications based on medical image processing 18

Design of piezoelectric energy harvesters for cardiac applic...

引用

conference on Active and Passive Smart Structures and Integrated systems XVIII

作者： Talebpour, Leila Bhayadia, Amit Olivett, Anthony Karami, M. Amin Univ Buffalo Dept Mech & Aerosp Buffalo NY 14260 USA

ISBN: (数字)9781510671997

ISBN: (纸本)9781510671997;9781510671980

In this paper, we present designing vibration energy harvesters based on the heart motion data achieved through image processing. Energy harvesting is intended as a means to continuously produce energy by converting heart motion to electricity. This energy can be used to power pacemakers. Currently, pacemakers are powered by non-rechargeable batteries that run out in about 10 years. The pacemakers need to be surgically replaced when the batteries run out. Using energy harvesters could pave the way for permanent pacemakers that do not require periodic surgical replacement. We have developed low-frequency energy harvesting designs that have small size and at the same time can be tuned to the heart motion frequencies. One important aspect of the design process is having a reasonable estimate of the heart motion. We use image processing and specifically optical flow tracking techniques to track the motion of individual points in Echo, MRI, and ultrasonic images. We experimentally test the developed harvesters to examine their power generation.

关键词： Heart Design Energy harvesting image processing Detection and tracking algorithms Medical imaging

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Camera-based light source localization for precise luminous intensity measurement of airport lamps 27

Camera-based light source localization for precise luminous ...

引用

27th IEEE Signal processing: algorithms, Architectures, Arrangements, and Applications, SPA 2024

作者： Podbucki, Kacper Marciniak, Tomasz Poznan University of Technology Faculty of Automatic Control Robotics and Electrical Engineering Institute of Automatic Control and Robotics Division of Electronic Systems and Signal Processing Jana Pawla II 24 Poznań60-965 Poland

ISBN: (纸本)9788362065486

Measuring luminous intensity using electronic sensors requires their precise positioning. In the case of mobile measurement platforms, it is important to detect the light source and thus determine the correct direction of movement of the measuring device. This article presents research on a solution for the initial detection of glowing airport lamps based on camera images. The impact of the selection of parameters and image processing methods on the prepared data set was assessed. The histogram filtration method was introduced to improve the effectiveness of airport lamp localization. The proposed solution was investigated in different weather and daytime conditions. The overall accuracy of the proposed solution is more than 90%. © 2024 Division of Signal processing and Electronic systems, Poznan University of Technology (DSPES PUT).

关键词： image enhancement

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Recognition and Analysis of Glass Subsurface Defects by Integrating Machine Vision and image processing Technology 5

Recognition and Analysis of Glass Subsurface Defects by Inte...

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5th International conference on Computers, Information processing and Advanced Education, CIPAE 2024

作者： Lin, Chen Ling, Xiong Luo, Guangming Wuhan University of Science and Technology Wuhan China Changli Glass Honghu Co. Ltd Wuhan China

ISBN: (纸本)9798331527662

Machine vision and computer image processing technologies are widely used in the metallurgical industry, especially in recognizing and analyzing defects in glass. High surfaces of planer surface and quality in the glass and metal manufacturing sector primarily require automated and performance visual detection, and inspection systems and algorithms are constantly improving. This article, therefore, seeks to comprehensively recognize and analyze glass subsurface defects through the integration of image processing technologies and machine vision. According to the algorithm's properties and the image features typified in the process, the defects of identified glass components are primarily classified based on determining the cause and the optical features of characteristics exhibited. Given the nature of varied and detected effects determined mainly by the classifiers, an improved accuracy level was notable, and a reduction of the computational complexity was evident following the use of machine vision and image processing technologies. © 2024 IEEE.

关键词： Machine vision

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