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8th International conference on video and image processing, ICVIP 2024

作者： Li, Yanfei Zeng, Yuan Gong, Yi Department of Electronics and Electrical Engineering Southern University of Science and Technology China College of Big Data and Internet Shenzhen Technology University China

ISBN: (数字)9781510689244

ISBN: (纸本)9781510689237

Monocular 3D object detection is a crucial topic in autonomous driving and Intelligent transportation systems (ITS). Most existing methods are evaluated on clean datasets but exhibit arresting performance degradation in the real world with varying weather conditions. image enhancement methods have been introduced in existing vehicle-centric works to address the impact of diverse weather on detection performance and improve the robustness of the model. Unlike vehicle-centric systems, roadside infrastructure can enlarge perception range and is less affected by vehicle occlusion to increase the response time in case of danger. To enhance the robustness of detection models on roadside infrastructure, this work introduces an image enhancement method incorporating depth information in modeling climate changes. We use a classification network trained on real weather data to validate the effectiveness of the enhancement and use state-of-the-art roadside infrastructure monocular detection models to evaluate the effectiveness of our method on object detection. Extensive experiments demonstrate that our method can enhance the robustness and generalization of detection models under various weather conditions. © 2025 SPIE.

关键词： Object detection Rain image enhancement Data modeling Education and training Cameras 3D modeling Adverse weather Performance modeling image contrast enhancement

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image Quality Improvement and Reduction of Parameters by Utilizing Learning-based Noise Reduction Method for Surveillance Camera images 24

Image Quality Improvement and Reduction of Parameters by Uti...

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6th International conference on Intelligent Medicine and image processing, IMIP 2024

作者： Goto, Tomio Department of Computer Science Nagoya Institute of Technology Japan

ISBN: (纸本)9798400710032

It is well known that video images captured by in-vehicle cameras and surveillance cameras are degraded due to noise introduced by their shooting environments. In this paper, we remove such noise using a learning method to improve the image quality. Furthermore, we propose a practical method for real-time processing by making the process lighter and faster. In order to make practical use of denoising techniques, it is necessary to develop lightweight models with high denoising performance. Experimental results show the effectiveness of our proposed method. © 2024 ACM.

关键词： image quality

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real-time superficial vein imaging system for observing abnormalities on vascular structures

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MULtimeDIA TOOLS AND APPLICATIONS 2024年第7期83卷 21045-21064页

作者： Altay, Ayse Gumus, Abdurrahman Izmir Inst Technol Dept Elect & Elect Engn Izmir Turkiye

Circulatory system abnormalities might be an indicator of diseases or tissue damage. Early detection of vascular abnormalities might have an important role during treatment and also raise the patient's awareness. Current detection methods for vascular imaging are high-cost, invasive, and mostly radiation-based. In this study, a low-cost and portable microcomputer-based tool has been developed as a Near-Infrared (NIR) superficial vascular imaging device. The device uses NIR Light-Emitting Diode (LED) light at 850 nm along with other electronic and optical components. It operates as a non-contact and safe infrared (IR) imaging method in real-time. image and video analysis are carried out using OpenCV (Open-Source Computer Vision), a library of programming functions mainly used in computer vision. Various tests were carried out to optimize the imaging system and set up a suitable external environment. To test the performance of the device, the images taken from three diabetic volunteers, who are expected to have abnormalities in the vascular structure due to the possibility of deformation caused by high glucose levels in the blood, were compared with the images taken from two non-diabetic volunteers. As a result, tortuosity was observed successfully in the superficial vascular structures, where the results need to be interpreted by the medical experts in the field to understand the underlying reasons. Although this study is an engineering study and does not have an intention to diagnose any diseases, the developed system here might assist healthcare personnel in early diagnosis and treatment follow-up for vascular structures and may enable further opportunities.

关键词： Medical imaging system Superficial vein imaging Computer vision real-time video processing Microcomputer

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A Spatio-Temporal video Denoising Co-Processor With Adaptive Codec

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS 2023年第11期70卷 4223-4234页

作者： Shi, Gang Wang, Xianglong Ouyang, Yichen Yao, Ruoheng Chen, Zhuoyu Zhang, Wei Chen, Lei An, Fengwei Southern Univ Sci & Technol Sch Microelect Shenzhen 518055 Peoples R China Southern Univ Sci & Technol Sch Microelect Minist Educ Shenzhen 518055 Peoples R China Southern Univ Sci & Technol Engn Res Ctr Integrated Circuits Next Generat Comm Minist Educ Shenzhen 518055 Peoples R China

With the increasing demand for high-resolution video and real-time processing, the limited efficiency of video-denoising algorithms has become a critical factor. This paper proposes a spatio-temporal video denoising co-processor to suppress an image sequence's spatial and temporal noise. Temporal denoising is achieved by merging the current and previous frames at the pixel level in which the current frame is processed by a spatial filter. After exploiting noise estimation and motion detection, the Wiener filter calculates the merge ratio. Rather than buffering the entire previous frame, the JPEG-like codec can dynamically adjust the compression ratio through a predefined quantization table to satisfy the designed on-chip storage. The experimental results demonstrate that the spatio-temporal denoising co-processor can effectively eliminate the fluctuation of the grayscale value of the noise in videos. Simultaneously, the adaptive codec can reduce the storage space consumption for the frame buffer by at least 80% of the original size. To the best of our knowledge, this is the first fully integrated spatio-temporal denoising co-processor without any external memory. Additionally, the grayscale, RGB, and RAW versions of the co-processor are also implemented on the Stratix V FPGA platform and synthesized in 28nm CMOS technology.

关键词： Streaming media Wiener filters image coding Hardware Estimation real-time systems Low-pass filters Noise reduction FPGA image compression motion estimation

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A High-Efficiency and Low-Complexity SKIP Type for Base Mesh Coding in V-DMC

A High-Efficiency and Low-Complexity SKIP Type for Base Mesh...

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2024 conference on Visual Communications and image processing

作者： Xu, Jianfeng Kato, Haruhisa Kawamura, Kei KDDI Res Inc Adv Visual Commun Lab 2-1-15 Ohara Fujimino Saitama 3568502 Japan

ISBN: (纸本)9798331529543;9798331529550

video-based Dynamic Mesh Coding (V-DMC) is an emerging standard for dynamic mesh compression, where the original meshes are decimated into simplified meshes called base meshes. This paper introduces a novel SKIP type for base mesh coding in V-DMC, complementing the existing INTRA and INTER types. When the SKIP type is used in base mesh coding, it directly copies the reconstructed base mesh from the reference frame, eliminating the need for additional data coding. Thus, the reconstructed base mesh in the current frame is identical to that in the reference frame. This significantly reduces the bit rate and decoding time for base meshes. Additionally, this paper employs a Lagrangian cost function using a linear model for bit estimation of INTRA type and L1 norms for distortion approximation of SKIP type to enable the encoder to select the best type for base meshes. Experimental results demonstrate superior BD-rate performance and significantly reduced decoding time for base meshes using the SKIP type, particularly in sequences with minimal object movements.

关键词： V-DMC video-based Dynamic Mesh Coding Base Mesh Coding Skip Type Lagrangian Cost Function

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A real-time Network for Fast Breast Lesion Detection in Ultrasound videos 6th

A Real-Time Network for Fast Breast Lesion Detection in Ultr...

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6th Chinese conference on Pattern Recognition and Computer Vision (PRCV)

作者： Dai, Qian Lin, Junhao Li, Weibin Wang, Liansheng Xiamen Univ Sch Informat Xiamen Peoples R China Xiamen Univ Sch Med Xiamen Peoples R China

ISBN: (纸本)9789819985579;9789819985586

Breast cancer stands as the foremost cause of cancer-related deaths among women worldwide. The prompt and accurate detection of breast lesions through ultrasound videos plays a crucial role in early diagnosis. However, existing ultrasound video lesion detectors often rely on multiple adjacent frames or non-local temporal fusion strategies to enhance performance, consequently compromising their detection speed. This study presents a simple yet effective network called the Space time Feature Aggregation Network (STA-Net). Its main purpose is to efficiently identify lesions in ultrasound videos. By leveraging a temporally shift-based space-time aggregation module, STA-Net achieves impressive real-time processing speeds of 54 frames per second on a single GeForce RTX 3090 GPU. Furthermore, it maintains a remarkable accuracy level of 38.7 mean average precision (mAP). Through extensive experimentation on the BUV dataset, our network surpasses existing state-of-the-art methods both quantitatively and qualitatively. These promising results solidify the effectiveness and superiority of our proposed STA-Net in ultrasound video lesion detection.

关键词： Ultrasound video Breast Lesion Detection

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Methods of increasing the contrast of images in video information systems 3

Methods of increasing the contrast of images in video inform...

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3rd International conference on Optics, Computer Applications, and Materials Science, CMSD 2023

作者： Beknazarova, S.S. Abdullayev, S.X. Abdullayeva, O.S. Abdullayev, Z.S. Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi 105 A. Temur Tashkent100142 Uzbekistan Namangan State University Namangan Uzbekistan Namangan Engeneering-Construction Institute Namangan Uzbekistan

ISBN: (纸本)9781510674486

In the article describe the methods of increasing the contrast of images in video information systems, the main compression of the video stream is provided by eliminating inter-frame redundancy using motion compensation methods for image fragments of adjacent frames. However, the use of motion compensation methods requires the formation of additional data (metadata) containing information about the types of image blocks used, the coordinates of their movement, etc. At the same time, in order to increase the compression of the video stream without compromising its quality, a higher accuracy of motion compensation is required, which leads to an increase in the number of blocks and, accordingly, to an increase in the volume of metadata that reduces the effectiveness of motion compensation. This is the main problem of compressing streaming video without degrading the quality of images. In addition, the higher accuracy of positioning blocks with motion compensation dramatically reduces the speed of image processing, which is not always feasible in real-time systems. © 2024 SPIE. All rights reserved.

关键词： Information systems

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Smart Monitoring and Guidance System for Parking Spaces 5

Smart Monitoring and Guidance System for Parking Spaces

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5th IEEE International conference on Computing, Power, and Communication Technologies, IC2PCT 2024

作者： Manvanth, G.S. Pavan Kumar, A. Priyanka, Valipe Devi Goduguluri, Varshitha Ravish, Roopa Pes University Department of Computer Science and Engineering Karnataka Bengaluru India

ISBN: (纸本)9798350383522

A parking system refers to the infrastructure and technology used to manage and facilitate the parking of vehicles in a specific area. These systems are designed to streamline the process of finding parking spaces, enhance efficiency, and improve overall traffic management. The proposed system is designed to address the challenges faced by open space parking spaces in major metropolitan cities. The prevailing issue of locating parking spaces in busy urban settings is tackled using Machine Learning (ML) model. Smart Monitoring and Guidance system is a ML based technology which allows the users to find vacant parking slots in a given area. The system uses ML model over Internet of Things (IoT) based solutions as scaling and maintenance is easier using ML models. The system provides real time information to the users about the total number of parking slots available at a parking space using image processing. The users can select a parking space of their choice. Upon selecting a suitable parking space, users are provided with real-time navigation assistance to the parking space of their choice. ML model improves the overall efficiency, reliability, and robustness of the system. The system obtains parking information of multiple parking spaces by processing their video footages concurrently. The system provides users with real-time navigation to the parking space thus providing the users and hassle free experience. © 2024 IEEE.

关键词： Directions assistance image processing Machine Learning Parking issues Parking Monitoring Parking slot availability real-time navigation real-time processing Smart city solutions Support Vector Classifier time-saving Traffic reduction

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Generalized self-cueing real-time attention scheduling with intermittent inspection and image resizing

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real-time SYSTEMS 2023年第2期59卷 302-343页

作者： Liu, Shengzhong Fu, Xinzhe Hu, Yigong Wigness, Maggie David, Philip Yao, Shuochao Sha, Lui Abdelzaher, Tarek Univ Illinois Champaign IL 61820 USA MIT Cambridge MA USA US DEVCOM Army Res Lab Adelphi NY USA George Mason Univ Fairfax VA USA

This paper proposes a generalized self-cueing real-time attention scheduling framework for DNN-based visual machine perception pipelines on resource-limited embedded platforms. Self-cueing means we identify subframe-level regions of interest in a scene internally by exploiting temporal correlations among successive video frames as opposed to externally via a cueing sensor. One limitation of our original self-cueing-and-inspection strategy (Liu et al. in Proceedings of the 28th IEEE real-time and embedded technology and applications symposium (RTAS), 2022b) lies in its lack of computational efficiency under high workloads, like busy traffic scenarios where a large number of objects are identified and separately inspected. We extend the conference publication by integrating image resizing with intermittent inspection and task batching in attention scheduling. The extension enhances the original algorithm by accelerating the processing of large objects by reducing their resolution at the cost of only a negligible degradation in accuracy, thereby achieving a higher overall object inspection throughput. After extracting partial regions around objects of interest, using an optical flow-based tracking algorithm, we allocate computation resources (i.e. DNN inspection) to them in a criticality-aware manner using a generalized batched proportional balancing algorithm (GBPB), to minimize a concept of generalized system uncertainty. It saves computational resources by inspecting low-priority regions intermittently at low frequencies and inspecting large objects at low resolutions. We implement the system on an NVIDIA Jetson Xavier platform and extensively evaluate its performance using a real-world driving dataset from Waymo. The proposed GBPB algorithm consistently outperforms the previous BPB algorithm that only uses intermittent inspection and a set of baselines. The performance gain of GBPB is larger in facing more significant resource constraints (i.e., lower sampling inte

关键词： real-time scheduling Object detection Temporal correlations Cyber-physical systems

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real-time Streaming Media processing and Optimization Technology in Intelligent video Surveillance

Real-time Streaming Media Processing and Optimization Techno...

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2024 International conference on Intelligent Algorithms for Computational Intelligence Systems, IACIS 2024

作者： Jiang, Hua Wang, Junjie Chuxiong Normal University School of Mathematics and Computer Science Chuxiong China

ISBN: (纸本)9798350360660

With the public Internet becoming more unstable due to issues like network congestion and line outages, ensuring the quality of large-scale real-time communications is becoming a significant concern. The real-time streaming processing and optimization methods for intelligent video surveillance systems are the main topics of this study. It offers a dynamic routing and distribution network technology developed to address transmission issues brought on by unstable public Internet links. Transmission quality is significantly increased by the system's optimisation of data transfer between servers through the use of dynamic path design and real-time quality detection. The study shows increased transmission stability and efficiency by contrasting static direct connections with dynamic routing. The dynamic obstacle avoidance capabilities of the system is validated by experimental simulations of network breakdowns. Furthermore, the effectiveness of different video encoders and streaming transport methods is assessed. According to the findings, content-aware coding beats rate-control and resolution-adjustment approaches in terms of video transmission quality, achieving an average Peak Signal-to-Noise Ratio (PSNR) of 38.2 dB. The present study offers significant perspectives on enhancing real-time streaming services and contributes to the advancement of intelligent video surveillance systems in the future. © 2024 IEEE.

关键词： video streaming

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