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检索条件"任意字段=16th Image Processing: Algorithms and Systems Symposium 2018"

共 650 条记录，以下是11-20 订阅

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Robust image watermarking scheme based on orientation of local image texture 16

Robust image watermarking scheme based on orientation of loc...

引用

16th International Conference on Signal processing systems, ICSPS 2024

作者： Li, Qiutong Zhang, Qiyuan Yuan, Xiaochen Faculty of Applied Sciences Macao Polytechnic University China

ISBN: (纸本)9781510689251

With the rapid development of big data and Internet of things (IoT), more and more digital products are emerging. However, this has also brought about a growing problem of copyright violation. Digital image robust watermarking technology can effectively resist various attacks and protect image copyright. Most of the existing robust watermarking schemes generally adopt the global embedding method and often ignore the texture orientation of the cover image itself leading to poor imperceptibility and robustness. In this paper, we propose an innovative digital image robust watermarking scheme. Firstly, we conduct the Oriented FAST and Rotated BRIEF (ORB) and Speeded Up Robust Features (SURF) feature point detection algorithms, combined with the texture complexity of the cover image to select the most complex texture region as the local embedding location of the watermark. Secondly, to further improve the robustness of the watermarked image, we conduct the Discrete Cosine Transform (DCT) adaptive inter-block correlation algorithm. We embed the watermark into the cover image by adjusting the difference between the image embedding block and the adjacent block. We have tested a dataset containing multiple images, in which various common attacks are simulated and multiple cover images are tested. By comparing the experimental results, our scheme performs better regarding robustness and imperceptibility. © 2025 SPIE.

关键词： Cosine transforms

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Dual-band image Sequence Registration based on Description of Velocity and Curvature Distribution 16

Dual-band Image Sequence Registration based on Description o...

引用

16th International Conference on Signal processing systems, ICSPS 2024

作者： Zhao, Bingqing Tang, Shanjun Li, Chuchen Yang, Beier Yang, Qingyu Shanghai Electro-Mechanical Engineering Institute Shanghai201109 China

ISBN: (纸本)9781510689251

the composite seeker based on multi-band imaging detection is the development focus of future precision-guided weapons. A certain seeker adopts a recognition and tracking strategy based on the fusion of long-wave infrared and visible light images. the quality of the fused image is closely related to the image registration accuracy. In order to solve the problem that the feature description of infrared and visible dual-band images is not identical due to large difference in grayscale texture information, we propose a registration algorithm based on description of velocity and curvature distribution. In particular, we first extract the infrared and visible light target foreground, and use the created velocity distribution description to complete the FAST corner point matching on the foreground contour. All the matched point pairs are used to achieve coarse contour registration. then, we use the created curvature distribution description to complete the CSS corner point matching of the target foreground. Finally, a real-time updated matching reservoir is built to calculate the fine registration matrix. the experimental results of multiple sets of actual infrared/visible light image sequences show that the proposed algorithm can achieve better feature description identity and better registration accuracy than the other algorithms. © 2025 SPIE.

关键词： image fusion

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Joint Dehazing and Low-light image Enhancement with Complete Atmospheric Model 16

Joint Dehazing and Low-light Image Enhancement with Complete...

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16th International Conference on Signal processing systems, ICSPS 2024

作者： Wu, Yong Xia, Kexiang Ge, Liyong Ye, Jiongkai Zhejiang Institute of Communications Hangzhou311112 China The School of Automation Hangzhou Dianzi University Hangzhou310000 China

ISBN: (纸本)9781510689251

Current image dehazing algorithms often encounter issues of contrast reduction and color distortion in the shadow regions of images. To address this challenge, this paper proposes a comprehensive atmospheric model that simultaneously considers haze and low-light conditions. this model incorporates a global darkness factor as a disturbance variable alongside the atmospheric scattering model, enabling adaptive luminance balancing without the need to estimate the global atmospheric light or the global darkness factor. Building on the principle of object color rendition, this paper justifies the use of the dark channel prior for haze removal and extends the bright channel prior for low-light image enhancement. Furthermore, we explore the mapping relationship between normal and inverted images based on the complete atmospheric model. By solving for the transmission rates of the global atmospheric light and global darkness factor, we propose an image enhancement algorithm capable of concurrently processing haze and low-light images. the proposed algorithm effectively mitigates issues of contrast reduction and color distortion. Experimental results demonstrate the efficacy of our approach, showing that the visual outcomes of simultaneous haze removal and low-light enhancement surpass those achieved through single-task haze removal. © 2025 SPIE.

关键词： Demulsification

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High-efficiency Reconfigurable Crypto Accelerator Utilizing Innovative Resource Sharing and Parallel processing 16

High-efficiency Reconfigurable Crypto Accelerator Utilizing ...

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16th IEEE International symposium on Embedded Multicore/Many-core systems-on-Chip (MCSoC)

作者： Le, Vu Trung Duong Pham, Hoai Luan Tran, thi Hong Duong, thi Sang Nakashima, Yasuhiko Nara Inst Sci & Technol 8916-5 Takayama Cho Ikoma Nara 6300192 Japan Osaka Metropolitan Univ Osaka 5588585 Japan

ISBN: (纸本)9798350393613

In decentralized IoT ecosystems, four cryptographic algorithms, including SHA256, BLAKE256, BLAKE2s, and Chacha20, are principal to ensure data integrity and confidentiality. However, existing cryptographic hardware is often limited to supporting a single algorithm and suffers from low performance, which falls short of meeting the diverse requirements of these systems. To address these limitations, we introduce a reconfigurable crypto accelerator (RCA) that offers high flexibility, superior performance, and optimal hardware efficiency. Our RCA includes three novel optimizations, specifically, a homogeneous multi-core architecture, a register-adder sharing approach, and a multi-level pipeline scheduler. the RCA was successfully verified and implemented at the system-on-chip level on a ZCU102 FPGA. the real-time performance evaluation of the RCA, during the execution of various cryptographic algorithms, demonstrates an energy efficiency ranging from 94.3-160.4 Mbps/W, which is 3.1-10.5 times higher compared to modern CPUs. Experiments conducted on several FPGAs show that the RCA is higher flexibility while still outperforming previous works by 1.63-31.65 times in throughput and 1.04-2.76 times in area efficiency. Furthermore, in ASIC synthesis, the RCA exhibits exceptional throughput (48.79-92.16 Gbps), area efficiency (66.2-102.31 Gbps/mm2), and energy efficiency (186.22-287.8 Gbps/W), surpassing other related ASICbased works.

关键词： Multi-core Cryptography FPGA ASIC SHA256 Homogeneous

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A Novel Pixel Block-Based Data Hiding Method for Improved Payload Capacity Using 2-Dimensional Block Segmentation 16

A Novel Pixel Block-Based Data Hiding Method for Improved Pa...

引用

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

作者： Tahara, Enrico Almer Dlayla, Adifa Widyadhani Chandra De La Croix, Ntivuguruzwa Jean Ahmad, Tohari Institut Teknologi Sepuluh Nopember Department of Informatics Surabaya Indonesia College of Science and Technology University of Rwanda Kigali Rwanda

ISBN: (纸本)9798331505264

Steganography is the practice of hiding information by embedding it as secret data within various types of digital media to strengthen security. Numerous algorithms have been proposed for image steganography with a common purpose of minimizing the perceptibility of the secret data existence to the human vision system. the most used in images steganography is the Least Significant Bit (LSB) technique;however, it is vulnerable to steganalysis and lacks robust verification processes. To address this, in this article, a new steganographic approach is proposed to optimize the image's pixels use for embedding the secret data. the proposed method, considering adjacent pixels, introduces a new data-hiding technique that enhances payload capacity by using two-dimensional block segmentation to embed information within pixel blocks. Experimental results show that the method outperforms previous studies reviewed in this work, achieving a Peak Signal-to-Noise Ratio (PSNR) between 49.7054 and 73.0848 decibels (dB) and Structural Similarity Index Measure (SSIM) between 0.9977 to 1.0000 for the selected difference range between -4 and 4, indicating high-quality stego images. © 2024 IEEE.

关键词： data hiding digital images processing information security steganalysis steganography

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Machine Learning-based Predictive Channel Modeling for 6G Wireless Communications Using image Semantic Segmentation 34

Machine Learning-based Predictive Channel Modeling for 6G Wi...

引用

IEEE 34th Annual International symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Wu, Tong Wang, Cheng-Xiang Li, Junling Huang, Chen Southeast Univ Sch Informat Sci & Engn Natl Mobile Commun Res Lab Nanjing 210096 Peoples R China Purple Mt Labs Pervas Commun Res Ctr Nanjing 211111 Peoples R China

ISBN: (纸本)9781665464833

the research on 6G wireless communications has become a focal point in the global technological competition. For 6G wireless systems, channel modeling is the foundation for the design and deployment of wireless communication systems. With unexplored channel characteristics expected to emerge from new frequency bands and scenarios in 6G wireless channels, predictive channel modeling becomes particularly important. this paper proposes an image-based real-time predictive channel modeling using image processing and machine learning (ML) algorithms, which extracts effective channel information from images and has been validated through channel measurement data and synthetic channel data. the proposed channel model considers large-scale identification and small-scale feature extraction. the former aspect is accomplished by training DeepLabv3+ on our image dataset and classifying the scenarios. For feature extraction, we use VGG-16 as the backbone network and validate it with the 3GPP Uma path loss model for comparison. the results show that predictive channel modeling using segmented images is superior to that of the 3GPP Uma path loss model. Even more, it performs better than the original image-based prediction.

关键词： 6G wireless communications predictive channel modeling machine learning image processing semantic segmentation

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Research on dynamic measurement of hot ring rolling dimension based on machine vision 16th

Research on dynamic measurement of hot ring rolling dimensio...

引用

16th IFAC symposium on Large Scale Complex systems - theory and Applications (LSS)

作者： Xiong Zhihao Zuo Zhijiang Li Han Pan Libo Jianghan Univ State Key Lab Precis Blasting Wuhan 430056 Peoples R China

In the process of ring rolling, the rolling process parameters of the equipment have an important influence on the forming process and forming quality of the ring. the ring rolling process has the characteristics of non-linearity, easy interference, rapid growth and asymmetric shape. these factors have resulted in the inability to measure the dimensions of the ring directly. In this work, we established a vision measurement system, and performed a series of operations on the image, such as threshold segmentation, hot ring contour extraction, oxide scale filtering, inner and outer ring extraction, inner and outer ring sampling, data visualization, etc. Moreover, we measured the dynamic dimension characteristics of small and medium size hot ring in the rolling process. the circularity, dimensional difference, center swing and vibration characteristics of the ring in the rolling process are obtained through the algorithm design, which characterizing the size change of the hot ring. the study provides practical methods and theoretical guidance for the subsequent measurement of large-size rings and feedback control of the rolling ring. Copyright (C) 2022 the Authors.

关键词： Hot ring rolling image processing Dimension measurement

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Retinex by Autoencoders 16

Retinex by Autoencoders

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16th International Conference on Signal-image Technology and Internet-Based systems (SITIS)

作者： Pezzoni, Claudio Mio, Corrado Barsotti, Annalisa Univ Milan Dipartimento Informat Giovanni degli Antoni Via Celoria 18 I-20133 Milan Italy Khalifa Univ Sci & Technol EBTIC Abu Dhabi City U Arab Emirates Univ Milan Dipartimento Informat I-20133 Milan Italy

ISBN: (纸本)9781665464956

the Retinex algorithms find wide applications as image enhancers, for their capability of preserving edges, while at the same time attenuating smooth gradients and chromatic dominants. they are characterized by the fact that the output chromatic intensity of a pixel is not determined in isolation (or looking only at the contiguous pixels) but through an operation of comparison to different local and remote areas of the image. this local/global comparison implies also a high computational cost for the algorithms: their complexity is not linear with the number of pixels;furthermore, the more systematic the comparison, the higher the complexity. thus, most Retinex algorithms are unfit for real-time processing. the recent development of efficient Machine Learning architectures for image processing has raised the question of whether one of the Retinex "transforms" could be efficiently learned by training a feed-forward Artificial Neural Network, thus creating a model characterized by short processing time. Selecting a variant of the Random Spray Retinex model - FuzzyRSR - as representative of the Retinex family, and choosing suitably structured autoencoder neural networks, we found that we could accurately reproduce the Retinex effects. the computational cost of the training phase was moderate, while that of the inference phases was linear in the number of pixels, and three orders of magnitude lower than the one of FuzzyRSR, thus making the ANN implementation of Retinex suitable for real-time processing.

关键词： Autoencoders FuzzyRSR image Enhancement Random Spray Retinex Retinex

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Real-time Low Vision Simulation in Mixed Reality 16

Real-time Low Vision Simulation in Mixed Reality

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16th International Conference on Signal-image Technology and Internet-Based systems (SITIS)

作者： Acevedo, Valeria Colantoni, Philippe Dinet, Eric Tremeau, Alain Univ Jean Monnet Univ Lyon Lab Hubert Curien UMR 5516 St Etienne France

ISBN: (纸本)9781665464956

Visual impairments are a global health issue with profound socioeconomic ramifications in both the developing and the developed world. there exist ongoing research projects, that aim to investigate the influence of light in the perception of low vision individuals. But as of today, there is neither clear knowledge nor extensive data regarding the influence of light in low vision situations. this research will address these issues by introducing a methodology and a system to simulate visual impairments. A pipeline based on eye anatomy coupled with real-time image processing algorithms allows to dynamically simulate low vision specific characteristics of selected impairments in mixed reality. An original new approach based on massively parallelized processing combined with an efficient modeling of eye refractive errors aims to improve the accuracy of the low vision simulation.

关键词： mixed reality low-vision simulation parallel programming image processing

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Role of Artificial Intelligence Techniques in Active Safety using image processing for Autonomous Driving Vehicles 16

Role of Artificial Intelligence Techniques in Active Safety ...

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16th IEEE International symposium on Applied Computational Intelligence and Informatics, SACI 2022

作者： Moga, Delia Filip, Ioan Politehnica University of Timisoara Department of Automation and Applied Informatics Timisoara Romania

ISBN: (数字)9781665481250

ISBN: (纸本)9781665481250

this paper presents a study on the importance of using Artificial Intelligence methods in developing self-driving vehicles. Advances in Artificial Intelligence are one of the key enablers of the Autonomous Vehicles development. there are several ways to increase the level of autonomy of a vehicle and make it capable to avoid or prevent crashes. Advanced Driver Assistance systems will help autonomous vehicles become a reality. image processing of various traffic scenarios can be drastically improved by the use of the superior degrees of computer processing and computer vision techniques. With the help of convolutional neural networks (CNNs), not only that a single object can be detected and tracked in a sequence, but all relevant objects can be detected and classified for further processing. CNN s, the current state-of-the art for efficiently implementing deep neural networks for vision, are more efficient because they reuse a lot of weights across the image. Also, an introduction in synthetic data generation field is presented as a way to overcome the lack of labeled datasets for training networks. © 2022 IEEE.

关键词： Autonomous vehicles

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