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检索条件"任意字段=Conference on Applications of Digital Image Processing XIX"

共 10246 条记录，以下是21-30 订阅

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Development of a multi-modality based approach for Plastic Waste Segregation 6

Development of a multi-modality based approach for Plastic W...

引用

6th IEEE International conference on image processing, applications and Systems, IPAS 2025

作者： Smari, Wejdene Mahdi, Mouna Zouari Elleuch, Jihen Frikha Fakhfakh, Ahmed Sellami, Dorra National Engineering School of Sfax Electrical Engineering Department Sfax Tunisia Sfax Digital Research Center Sfax Tunisia

ISBN: (纸本)9798331506520

Plastic waste is becoming nowadays a huge environmental problem. Circular economy seems to be the best choice for preserving the environment, by reinserting plastic waste into the industrial process and use. A key step for that is the plastic waste segregation from other waste. This paper proposes a new plastic waste segregation approach based on two modalities: spectroscopy and optical images. The research handles an optical camera for waste image acquisition, while the ground truth for plastic type identification, with respect to the seven primary plastic types: PET, HDPE, LDPE, PP, PS, PVC, and Other, is established through spectroscopic analysis. Various deep learning models were trained and evaluated on a dataset of publicly available and custom-collected images, aiming to achieve human-level accuracy in distinguishing between plastic types. The proposed methodology is based on a set of steps, where the model is first built implicitly on a segregation of different wastes, and then applied via transfer learning for separating the seven plastic types. The system performances demonstrate the feasibility and effectiveness of this combined approach for accurate and efficient plastic waste sorting. The proposed system has been implemented on Raspberry Pi 4 Model B+ as the central processing unit, integrating computer vision and deep learning techniques for efficient and accurate sorting. © 2025 IEEE.

关键词： computer vision deep learning embedded system Plastic waste segregation Raspberry Pi YOLOv8

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An image encryption algorithm based on non-degenerate chaos and dynamic Bi-directional permutation 16

An image encryption algorithm based on non-degenerate chaos ...

引用

16th International conference on Signal processing Systems, ICSPS 2024

作者： Liao, Yunlong Xu, Qingyang Zhang, Qiyuan Xing, Zheng Yuan, Xiaochen Faculty of Applied Sciences Macao Polytechnic University China

ISBN: (纸本)9781510689251

In the wake of the accelerated advancement of Internet of Things(IoT) technology, a significant volume of multimedia information is emerging as the dominant component of IoT applications. However, this information also led to big security risks. Therefore, a secure and reliable image encryption scheme based on non-degenerate hyper chaos and dynamic bidirectional permutation is proposed for the characteristic of digital images which the primary information carrier in the IoT communication environment. The scheme uses non-degenerate discrete chaos to generate pseudo-random sequences and applies them to the encryption process involving image confusion, dynamic permutation, and dynamic diffusion. Through theoretical analysis and experimental verification, the algorithm exhibits high sensitivity to both the plaintext images and the ciphertext images. Concurrently, it can effectively resist common noise attacks and cryptographic attacks. In conclusion, the proposed scheme offers superior encryption capabilities and stands as a secure solution, compatible with a diverse range of IoT environments. © 2025 SPIE.

关键词： Chaos theory

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Optimizing Fabric Welding Using image Processed Laser Inspection 5th

Optimizing Fabric Welding Using Image Processed Laser Inspec...

引用

5th International conference on Data Science, Machine Learning and applications, ICDSMLA 2023

作者： Ansari, Tabish Sekhar, Malepati Chandra Alam, Intekhab Bargavi, Manju Department of Civil Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bengaluru India

ISBN: (纸本)9789819780426

Material welding is used in expanding industrial and industrial applications and depends on accuracy and precision to ensure satisfaction and protection. Laser inspection technology has been developed to help enhance the procedure's accuracy and performance by presenting rapid, reliable imaging that may be processed to decide where changes are wished. Through photograph processing, particular modifications to cloth welding can be recognized quickly and effectively. Additionally, photograph-processed laser inspection can hit upon any irregularities or defects in the welding method that can cause premature failure or decreased functionality. With this generation, designers and manufacturers can also develop higher control structures for his or her tasks, making more accurate and price-effective use of their assets. Sooner or later, the laser inspection era can offer actual-time remarks for automatic tactics, allowing changes to be made quickly with minimal disruption. Using this image processing technology, fabric welding groups can improve exceptional accuracy and value across merchandise. Optimizing material welding through image-processed laser inspection is a valuable method for controlling the pleasantness of welds. This technique uses a laser scanner, mild source, and a digital camera to seize detailed photos of the welds before and after welding. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Inspection

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Hardware-Aware Depth image Classification Model for In-Sensor AI Integration

Hardware-Aware Depth Image Classification Model for In-Sens...

引用

International conference on applications in Electronics Pervading Industry, Environment and Society, APPLEPIES 2024

作者： Fasolino, Andrea Licciardo, Gian Domenico Vitolo, Paola Liguori, Rosalba Di Benedetto, Luigi Rubino, Alfredo Pau, Danilo Department of Industrial Engineering University of Salerno Fisciano Salerno84084 Italy System Research and Applications STMicroelectronics Agrate Brianza20041 Italy

ISBN: (纸本)9783031840999

The shift of computing capabilities towards edge sensing elements in image classification tasks is leading to the substitution of cameras in some industrial and consumer tasks with ultra-low-resolution (ULR) Time-of-Flight (ToF) sensors, thanks to their compactness and ultra-low power consumption. To effectively integrate classification capabilities into edge devices, a hardware-aware design of the classification algorithm and a careful custom Hardware (HW) post-processing core are needed. This work proposes a new compact and ultra-low power Neural Network (NN) that enables the implementation of a HW post-processing core for real-time classification tasks inside the sensor packaging. The resulting HW architecture has been prototyped on an AMD Xilinx Artix-7 FPGA, reaching an Energy per Inference consumption of 65.6 nJ and a power consumption of 1.095 μW at the maximum Output Data Rate of the sensor. Moreover, the implementation in Skywater 130 nm technology reveals an area occupation below 1 mm2, with a total power compared to the sensor consumption of about 11%. These results are significantly lower than the typical energy and power consumption of the sensor, enabling real-time post-processing of depth images and encouraging research in integrating classification capabilities next to sensing elements. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： digital storage

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image Texture Data Blocks Produced with 2D-Cellular Automata Linear Rules 12th

Image Texture Data Blocks Produced with 2D-Cellular Automata...

引用

12th International conference on Frontiers of Intelligent Computing: Theory and applications, FICTA 2024

作者： Jahan, Wani Shah Firdous, Ahmad Muzamil, Hussan Aiman, Jan Government College Frisal University of Kashmir Kulgam India Department of Electronics S. P. College Cluster University Srinagar Srinagar India Department of Electronics University of Kashmir Srinagar India

ISBN: (纸本)9789819601387

Cellular Automata rules are producing an evolution type phenomenon that has been used for a wide range of applications. CA rules have been used for various aspects of image processing, and this study is carried on generation of texture data using images for multiple functions. Here an image is converted to numerous texture data blocks that can be used for dynamic and static data security over networks depending on discrete time calendar or frequency of use. With the application of various 2D-Cellular Automata linear rules on images, a series of texture data blocks are produced. Numerous texture patterns being linked to a single digital image is used to create dynamic data blocks depending on the number of iterations of a CA rule being applied. Some application areas for this block sequence generation are network security, user/data authentication, data hiding and cryptography. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： image texture

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image Search Engine with Recognition 4

Image Search Engine with Recognition

引用

4th International conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Kumar, Jmsv Ravi Dheeraj, Bellaganti Gowtham, Geddada Babu, Dokala Vivek Kiran, Bonthu Asha Srikanth, M. Srkr Engineering College Department of Information Technology Andhra Pradesh Bhimavaram India

ISBN: (纸本)9798331523923

The image Recognition Search Engine is one of the modern advances in artificial intelligence and image analysis and processing. This advanced system surpasses typical functionalities in image identification as it captures features to solve new problems faced in existing systems of digital media authentication, content designing, and improvement of images. The system core relies on advanced AI algorithms that can rasterically recognize and analyze various forms of image objects ranging from objects, faces, scenes, and brand logos converting what appears to be simple images into indexical, analyzable data. One feature is that the system can integrate deepfake detection technology, which is relevant in the context of increasing the amount of manipulated content in the media space. Using special algorithms to learn even the least detectable abnormality in images including the presence of unnatural distinctive facial characteristics and changes in lighting conditions, we obtain a highly effective tool for improving the reliability of image identification. Furthermore, the platform allows for new features to convert an image into a video by implementing frame interpolation and motion estimation through animating the images to allow users to create interesting clips for applications regarding marketing or any personal use. © 2025 IEEE.

关键词： Motion estimation

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Performance Evaluation of Edge Detectors for Automated Book Spine Segmentation in Library Bookshelf images 16th

Performance Evaluation of Edge Detectors for Automated Book ...

引用

16th International conference on Genetic and Evolutionary Computing, ICGEC 2024

作者： Maung, Myat Min Zu Aung, Zu Nwe, Than Than University of Information Technology Hlaing Campus Parami Road Yangon Myanmar

ISBN: (纸本)9789819615346

A well-maintained library is a valuable resource for educational institutions and research facilities. Efficient management of libraries requires a reliable system for cataloging books. This paper evaluates four prominent edge detectors - Canny, Sobel, Prewitt and Roberts, analyzing their performance using metrics such as mean square error (MSE), root mean square error (RMSE) and peak signal-to-noise ratio (PSNR). Why we study on the evaluation of edge detectors initiated from the studying of the University of Information Technology’s Library, which houses over 100,000 books. We aim to address the challenges of efficiently cataloging and retrieving books in the digital library of this extensive collection to collaborate with an IT research center for future improvements. In these days, optimizing edge detection for book spine recognition is essential for efficient cataloging, inventory management and quick retrieval in digital library applications. Thus, this paper presents a comparative analysis of the edge detection techniques to support in solving the challenges of a digital library in future. These techniques are within computer vision and image processing to enhance book spine detection accuracy, reduce manual labor and minimize errors in robotic libraries. Our evaluation results indicate that the Canny edge detector consistently outperforms the others, demonstrating superior performance with lower MSE, RMSE and higher PSNR values. Integrating the Canny edge detector into existing systems will enhance book organization and retrieval in the digital library. This accurate and noise-resistant detector addresses book spine segmentation issues by solving cataloging inefficiencies and improving overall management. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： image segmentation

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Per-Pixel Solution of Multispectral Photometric Stereo

Per-Pixel Solution of Multispectral Photometric Stereo

引用

2025 IEEE/CVF Winter conference on applications of Computer Vision, WACV 2025

作者： Ishihara, Shin Sato, Imari National Institute of Informatics 2-1-2 Hitotsubashi Chiyoda-ku Tokyo Japan

ISBN: (纸本)9798331510831

Photometric Stereo (PS) estimates surface normals by analyzing images lit from different angles. Enhancing PS with spectral imaging, known as multispectral photometric stereo (MPS), uses varying light source colors for simultaneous image capture. As in traditional PS, obtaining a unique solution is challenging in MPS when the reflectance properties of the object are unknown. This paper presents an approach utilizing the spatial arrangement and color of light sources to solve the MPS problem in the condition of spatially varying reflectance from a minimum of seven spectral images without spatial smoothness constraints. A robust optimization technique is introduced to manage real data. Experiments on synthetic and real scenes validate the method's effectiveness, including for non-Lambertian surfaces. The method can contribute to advanced digital archiving that simultaneously records surface normal and spectral reflectance. © 2025 IEEE.

关键词： Stereo image processing

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3D Reconstruction of Building Models Based on 2D Floor Plans Using Statistical Analysis 12th

3D Reconstruction of Building Models Based on 2D Floor Plans...

引用

12th International conference on Frontiers of Intelligent Computing: Theory and applications, FICTA 2024

作者： Gasiorowski, Pawel Vassilev, Vassil School of Computing and Digital Media Cyber Security Research Center London Metropolitan University 166-220 Holloway Road LondonN7 8DB United Kingdom

ISBN: (纸本)9789819601424

The focus on interior architecture within the real estate sector has intensified, with floor plans serving as the primary method for illustrating spatial layouts, encompassing rooms, doors, and windows. With advancements in image processing, computer vision, and graphics, it is now feasible to reconstruct and visualize building interiors in 3D. This paper concentrates on the approximate reconstruction of a suburban kindergarten in Sofia, Bulgaria, in 3D for future visualization of indoor pollution levels on a basis of data produced by sensors installed on the premises. We use well-established image processing algorithms for extracting features from a 2D floor plan, classify them statistically, and convert them into GeoJSON format for subsequent 3D reconstruction in Unity game engine. By successfully approximating the internal structure of the kindergarten building, our approach demonstrates significant potential. The results suggest avenues for refinement and application in comparable settings, offering advancements in building analysis and environmental monitoring alike. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Floors

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InVideo Search: Scene Description Clustering and Integrating image and Audio Captioning for Enhanced Video Search 21st

InVideo Search: Scene Description Clustering and Integrating...

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21st International conference on Distributed Computing and Intelligent Technology

作者： Khan, Almira Asif Muhammed Shaji, Asher Mathews Sujith, Devika Nath, Aneesh G. Udmale, Sandeep S. TKM Coll Engn Dept Comp Sci & Engn Kollam Kerala India Veermata Jijabai Technol Inst VJTI Dept Comp Engn & Informat Technol Mumbai 400019 Maharashtra India

ISBN: (纸本)9783031814037;9783031814044

In the digital era, the vast amount of long videos highlights the need for an advanced system to efficiently find specific segments based on text descriptions. The proposed solution aims to develop a video content retrieval system by utilizing established tools in video analysis, image/video captioning, and information retrieval. The work is organized into three modules: Keyframe extraction, Captioning, and Query-based searching. Our primary focus is on effectively identifying key elements within these videos, achieving a semantic understanding of these videos in the form of captions, and establishing precise matches of user queries. In short, users input descriptive text prompts, and the application, equipped with pre-trained models, promptly and accurately identifies and retrieves the video segments. This application carries significant potential across various domains, from enabling efficient scene location in movies to helping extract knowledge from educational lectures. Furthermore, this research fundamentally departs from conventional video search methods that heavily rely on metadata or manually assigned tags, which often fall short of capturing the nuances of video content. This work also focuses on a multimodal captioning strategy to integrate more semantic content. Clustering of captions was also incorporated to improve search performance in the case of long videos. This approach allows us to deliver a robust and efficient solution, taking advantage of the extensive knowledge and research underlying these established technologies. Beyond the immediate applications, this research has broader applications in fields like natural language understanding, multimedia analysis, and information retrieval.

关键词： Clustering Keyframe extraction Natural language processing Video content retrieval system

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