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检索条件"任意字段=2023 IEEE International Conference on Image Processing and Computer Applications, ICIPCA 2023"

共 4811 条记录，以下是221-230 订阅

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Research on contour extraction and edge detection of sugarcane image based on MATLAB 3

Research on contour extraction and edge detection of sugarca...

引用

3rd ieee international conference on Power, Electronics and computer applications, ICPECA 2023

作者： Chen, Mingyou Wang, Jiyue Zhu, Liucun Deng, Haofeng Wu, Hongwei Zhang, Zhenyu Beibu Gulf University University School of College of Mechanical and Marine Engineering Qinzhou China Beibu Gulf University University School of Institute of Advanced Science and Technology Qinzhou China

ISBN: (纸本)9781665472784

Using image processing technology to study sugarcane image contour extraction and edge detection methods has important research value and practical application significance for realizing pre-seed sugarcane planter to complete the seeding task stably, quickly, accurately and efficiently. In this regard, with the help of the MATLAB platform, this paper uses the hollowing out internal point algorithm to achieve the contour extraction of the sugarcane image, and uses five more classic edge detection operators for the same original sugarcane image to realize the edge detection of the sugarcane image. Analyze the results and draw the conclusion that Canny operator is the most suitable and effective edge detection operator for sugarcane image edge detection. This also provides an important reference for subsequent monitoring of the seeding status and efficiency of the precut sugarcane planter. © 2023 ieee.

关键词： image processing

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Panoptic-aware image-to-image Translation 23

Panoptic-aware Image-to-Image Translation

引用

23rd ieee/CVF Winter conference on applications of computer Vision (WACV)

作者： Zhang, Liyun Ratsamee, Photchara Wang, Bowen Luo, Zhaojie Uranishi, Yuki Higashida, Manabu Takemura, Haruo Osaka Univ Suita Osaka Japan Osaka Inst Technol Osaka Japan

ISBN: (纸本)9781665493468

Despite remarkable progress in image translation, the complex scene with multiple discrepant objects remains a challenging problem. The translated images have low fidelity and tiny objects in fewer details causing unsatisfactory performance in object recognition. Without thorough object perception (i.e., bounding boxes, categories, and masks) of images as prior knowledge, the style transformation of each object will be difficult to track in translation. We propose panoptic-aware generative adversarial networks (PanopticGAN) for image-to-image translation together with a compact panoptic segmentation dataset. The panoptic perception (i.e., foreground instances and background semantics of the image scene) is extracted to achieve alignment between object content codes of the input domain and panoptic-level style codes sampled from the target style space, then refined by a proposed feature masking module for sharping object boundaries. The image-level combination between content and sampled style codes is also merged for higher fidelity image generation. Our proposed method was systematically compared with different competing methods and obtained significant improvement in both image quality and object recognition performance.

关键词： image quality Training image segmentation computer vision Codes image synthesis Semantics

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A Survey of Forensic applications using Digital image processing: image Improvement Case Study 7

A Survey of Forensic Applications using Digital Image Proces...

引用

7th international conference on Computing Methodologies and Communication, ICCMC 2023

作者： Manaswini, Deevi Ghanta, Sri Sai Vidyadhari Manogna, Tubati Lavanya Naga Keerthana Kolakalapudi, L. Chaitanya, Gogineni Krishna Kumar, Anguraj Dinesh Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Guntur India

ISBN: (纸本)9781665464086

To gather reliable evidence and submit it to the court, forensic applications are used. Due to recent advancements in technology, many crimes now involve the modification of photos. Finding the original evidence and presenting it to the court has been simpler with the development of forensic software. The notion of digital image processing is combined with forensic applications to discover the original evidence with better evidence quality and to extract, analyse the most evidence feasible from the crime scenes. Analysing an image is absolutely necessary to determine the order of occurrences. Because image processing techniques lack a formal basis, forensic findings lose their legal value. To ensure that any image transformation meets high standards of safety and reliability, more rigorous methods should be applied to image processing applications. This paper focuses on how image enhancement technique s of digital image processing are used in the forensic applications. © 2023 ieee.

关键词： image enhancement

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Investigating the Effectiveness of image Restoration Algorithms in Digital image processing

Investigating the Effectiveness of Image Restoration Algorit...

引用

2023 ieee international conference on Paradigm Shift in Information Technologies with Innovative applications in Global Scenario, ICPSITIAGS 2023

作者： Sidhu, Amritpal Kantak, Ganesh Kumar Naveena, S. Sathiya Shinde, Gitanjali R. Singh, Vaishali Zaidi, Taskeen Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Vivekananda Global University Department of Mechanical Engineering Jaipur India Prince Shri Venkateshwara Padmavathy Engineering College Department of Master of Business Administration Chennai127 India Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Department of Computer Science and Information Technology Karnataka Bangalore India

ISBN: (纸本)9798350329773

This paper examines the effectiveness of image healing algorithms for virtual photo processing. The research makes a specialty of different forms of picture recovery algorithms, inclusive of side-retaining methods and regression-based totally methods and their outcomes on photo nice. It proposes a quantitative assessment framework based on a hard and fast of goal metrics for the overall performance of these algorithms. The assessment framework includes simulations to acquire sensible dimension consequences. Outcomes have shown that the regression-based techniques outperformed the brink-keeping techniques in phrases of picture constancy and sharpness. The paper concludes that the proposed quantitative evaluation framework may be used to assess the performance of different picture restoration algorithms in digital picture processing. © 2023 ieee.

关键词： image reconstruction

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image Data Hiding in Neural Compressed Latent Representations

Image Data Hiding in Neural Compressed Latent Representation...

引用

2023 ieee international conference on Visual Communications and image processing, VCIP 2023

作者： Huang, Chen-Hsiu Wu, Ja-Ling National Taiwan University Dept. of Computer Science and Information Engineering Taipei Taiwan

ISBN: (纸本)9798350359855

We propose an end-To-end learned image data hiding framework that embeds and extracts secrets in the latent representations of a generic neural compressor. By leveraging a perceptual loss function in conjunction with our proposed message encoder and decoder, our approach simultaneously achieves high image quality and high bit accuracy. Compared to existing techniques, our framework offers superior image secrecy and competitive watermarking robustness in the compressed domain while accelerating the embedding speed by over 50 times. These results demonstrate the potential of combining data hiding techniques and neural compression and offer new insights into developing neural compression techniques and their applications. © 2023 ieee.

关键词： Steganography

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ResAttUNetPlus: An Attention Network Architecture for Polyp image Segmentation

ResAttUNetPlus: An Attention Network Architecture for Polyp ...

引用

image processing and computer applications (icipca), ieee international conference on

作者： Xinlin Gu Luqiao Zhang Cyberspace Security Academy Chengdu University of Information Technology Chengdu China

Intestinal polyps are a prevalent colorectal condition, and early detection and precise identification of lesion areas are crucial to prevent polyp malignancy and enhance treatment outcomes. Colonoscopy is commonly utilized for examining intestinal polyps. In this research, we combine deep learning frameworks from the field of artificial intelligence, specifically computer vision, to perform image segmentation. To develop a more accurate intestinal polyp segmentation model, we propose ResAttUNetPlus, a deep learning network that builds upon ResUNet++ by incorporating improvements in the attention mechanism. The ResAttUNetPlus model comprises three main components: the Encoding layer, Bridge layer, and Decoding layer. Our findings demonstrate that ResAttUNetPlus exhibits a highly effective segmentation performance. When tested on the publicly available dataset Kvasir-SEG using the same hardware facility, the ResAttUNetPlus model achieves more than a one percent improvement in accuracy and mIoU coefficient compared to the ResUNet++ model. This proposed method provides gastroenterologists and patients with a more accurate and efficient technique for image segmentation of intestinal polyps.

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RECTANGULAR-OUTPUT image STITCHING 30

RECTANGULAR-OUTPUT IMAGE STITCHING

引用

30th ieee international conference on image processing (ICIP)

作者： Zhou, Hongfei Zhu, Yuhe Lv, Xiaoqian Liu, Qinglin Zhang, Shengping Harbin Inst Technol Weihai 264209 Peoples R China

ISBN: (纸本)9781728198354

image stitching aims to combine two images with overlapping fields to expand the field-of-view (FoV). However, the stitched images of existing methods are irregular, and need to be processed by rectangling methods, which is time-consuming and prone to be unnatural. In this paper, we propose the first end-to-end framework, Rectangular-output Deep image Stitching Network (RDISNet), to directly stitch two images into a standard rectangular image while learning color consistency between image pairs and maintaining the authenticity of the content. To further preserve the structure of large objects in the stitched image, we design a dilated BN-RCU block to expand the receptive field of RDISNet for extracting enriched spatial context. Furthermore, we design a novel data synthesis pipeline and build the first rectangular-output deep image stitching dataset (RDIS-D) for jointing image stitching and rectangling. Experimental results demonstrate that RDISNet performs favorably against the state-of-the-art methods.

关键词： image stitching image rectangling dilated convolutions end-to-end computer vision

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A MATLAB Expedition into image processing 7

A MATLAB Expedition into Image Processing

引用

7th international conference on Electronics, Materials Engineering and Nano-Technology, IEMENTech 2023

作者： Karmakar, Samit Mandal, Debangshu Pratihar, Maitree Chakraborty, Arindam Biswas, Aparna Talukdar, Sayantan University of Engineering and Management Electronics & Communication Engineering Department Institute of Engineering and Management Kolkata India

ISBN: (纸本)9798350305517

This paper deals with cutting-edge techniques in image processing, addressing critical aspects such as edge detection, noise cancellation, histogram analysis, image compression, and upgradation using MATLAB. Evaluating both traditional and deep learning approaches, the study explores methods to enhance image quality, reduce noise, optimize contrast through histogram manipulation, and implement efficient compression algorithms. MATLAB's image processing toolbox facilitates the implementation and validation of these techniques, with results demonstrating significant improvements in various aspects of image enhancement. This research contributes a versatile toolkit for researchers, practitioners, and enthusiasts in the field of digital image processing, catering to diverse applications from medical imaging to computer vision. © 2023 ieee.

关键词： image enhancement

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Multi-View image Rectification for UAV-Captured image Sequences

Multi-View Image Rectification for UAV-Captured Image Sequen...

引用

2023 ieee international conference on Visual Communications and image processing, VCIP 2023

作者： Zou, Shun Jin, Xin Fan, Yihui Tsinghua University Shenzhen International Graduate School Shenzhen China

ISBN: (纸本)9798350359855

The image sequences captured by Unmanned Aerial Vehicles (UAVs) can be applied to many computer vision tasks. However, due to the instability of UAV flight, the captured image sequences will deviate from the preset trajectory and pose, which reduce the quality of subsequent applications such as panoramic image stitching. In this paper, a novel method is proposed to rectify UAV-captured image sequences by transforming the images to a regular trajectory with the uniform pose. First, to minimize the total transformation deviation, virtual regular camera trajectory is derived by minimizing the global error of coordinates between actual and virtual camera trajectories. Then, camera-pose-relevant local homography is proposed by inserting the camera pose into local homography to transform the images to the derived virtual trajectory with the uniform pose and correct translation parallax. The experimental results demonstrate the effectiveness of the proposed rectification algorithm from both theoretical and application levels. © 2023 ieee.

关键词： Cameras

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Analysis of computer image processing Technology based on Intelligent Optimization Algorithm 3

Analysis of Computer Image Processing Technology based on In...

引用

3rd international conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Li, Hui Shanxi Provincial Eye Hospital Shanxi Taiyuan030002 China

ISBN: (纸本)9798350319125

With the continuous development of computer technology, computer image processing technology has become an indispensable part of modern society. computer image processing technology mainly includes image acquisition, image enhancement, image compression, image recognition and so on. In this process, intelligent optimization algorithm plays a very important role. This paper will introduce the application of intelligent optimization algorithm in computer image processing technology in detail. © 2023 ieee.

关键词： artificial intelligence computer technology image processing technology Intelligent optimization algorithm

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