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检索条件"任意字段=Conference on Real-Time Image and Video Processing 2010"

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Multi scene infrared image processing based on fusion algorithm 6

Multi scene infrared image processing based on fusion algori...

引用

6th conference on Frontiers in Optical Imaging and Technology: Imaging Detection and Target Recognition

作者： Wang, Shuwei Xi, Youyou Yang, Jinbao Tong, Xiaojie Yang, Chen Beijing Institute of Environmental Characteristics Beijing China 93114troops Beijing China

ISBN: (数字)9781510679733

ISBN: (纸本)9781510679726

Infrared imaging technology is widely used in military and civilian fields, but in practical applications, accurate and effective detection and tracking of infrared small targets is a bottleneck problem that needs to be solved urgently. In response to the problem that traditional algorithms are difficult to handle complex scenes with low signal-to-noise ratio and deep learning algorithms rely heavily on data, the proposed algorithm combines traditional algorithms with deep learning algorithms and is applied to detect and track infrared moving targets in various complex scenes, with resolutions ranging from 640 * 512 to 320 * 256 video sequences. At the same time, traditional algorithms include both single frame and multi frame detection methods. In order to avoid the problem of poor real-time performance, we selected the TMS320C6678 hardware platform and implemented simulation applications using a DSP+FPGA architecture. Experimental results have shown that this algorithm has excellent performance in object detection and tracking. © 2024 SPIE.

关键词： Learning algorithms

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Embedded-Based Non-contact Heart Rate Detection System 8th

Embedded-Based Non-contact Heart Rate Detection System

引用

8th International conference on Computing, Control and Industrial Engineering, CCIE 2024

作者： Ding, Ning Zhang, Qi Liu, Zhirong Liang, Meiling Liu, Henghui Li, Linzhi School of Electronic Engineering and Automation Guilin University of Electronic Science and Technology Guilin China

ISBN: (纸本)9789819769360

The non-contact heart rate detection system avoids direct contact between the sensor and the skin, improving portability, comfort and real-time heart rate monitoring. This paper presents an embedded-based non-contact heart rate detection system, embedding the camera behind the mirror, so that the user can realize to look at the mirror and get their heart rate information at the same time. First, the face color video is acquired by the USB camera mounted on the Raspberry Pi, the face in the video is detected as well as the feature points are detected, and the region of interest of the face is obtained and intercepted based on the detected feature points. Then, using OpenCV-based image processing, the feature area is separated by RGB three-channel, and one group of components is used as a one-dimensional signal for data processing, and then the heart rate value with periodic changes is extracted by Fourier transform and band-pass filtering. The system finally realizes the measurement of heart rate value and the display of heart rate waveform. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： image segmentation

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Research on the processing algorithm of drilling image 8

Research on the processing algorithm of drilling image

引用

8th International conference on Electronic Technology and Information Science, ICETIS 2023

作者： Yuan, Haoqi Xu, Fuxin Fu, Penglei School of Physics and Electronics CSU Lushan South Road Yuelu Changsha China

ISBN: (纸本)9781510666535

In geological exploration, the texture and context information generated by different rocks on the inner wall of the drilling hole is of great significance to understand the geological condition. Drilling camera technology can obtain digital drilling video and hole wall images. For a long time, the method of manual interpretation is the main method of studying hole wall images. This method has problems such as poor real-time performance and low work efficiency .In this paper, the processing algorithm is designed based on the imaging characteristics of hole wall image and the method of digital image processing, including image preprocessing, image expansion and image stitching. First, the radius of the area is determined according to the image features, and then the concentric circle expansion method is used to obtain the rectangular expansion image. Finally, the SIFT feature point is used to complete the accurate matching with the Ransac algorithm, and use weighted average method to complete image fusion. The entire algorithm can obtain a panoramic expansion image of the hole wall area, laying the foundation for the quantitative analysis of drilling data. © 2023 SPIE.

关键词： image fusion

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Performance Test of Holographic video Communication System

Performance Test of Holographic Video Communication System

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International conference on Multimedia Computing, Networking and Applications (MCNA)

作者： Kara, Kubra Lloret, Jaime Romero, Oscar Sendra, Sandra Univ Politecn Valencia Inst Invest Gest Integrada Zonas Costeras C Paranimf 1 Valencia 46730 Spain

ISBN: (纸本)9798350354744;9798350354737

Holography creates three-dimensional (3D) images with depth and relief, and can be applied to medicine, engineering, and entertainment, enabling holographic communication, live streaming, and virtual gatherings. Digital holography involves using digital displays, cameras, and beams. This paper discusses various holographic systems, including computational holography, which uses computers to produce 3D images, Deep Holography (DH), which utilizes deep neural networks (DNN), and tensor holography, which combines DNN and machine learning (ML) to produce 3D images in mid-air. This paper also addresses network challenges, such as the high data transmission, bandwidth limitations that can hinder the quality of the holographic image, and the low latency crucial for maintaining real-time interaction in holographic communication. While some scholars introduce the capacities of 6G networks, other authors propose a compression and differentiated prioritization technique. Holography can create striking images using convolutional neural networks (CNN) and an anti-aliasing double-phase (AA-DPM) method. Based on the communication performance test that has been carried out, it can be concluded that ensuring access to powerful and optimized hardware and software is crucial for both text and holographic image generation. As the complexity and length of the text increase, processing time augments as well. There are significant differences between using powerful servers and weaker hardware. Finally, it can be concluded that it is imperative to prioritize hardware and software for image generation to facilitate a smooth conversation.

关键词： Digital holography Network infrastructure image quality Technical resource Performance test

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MobileNetV2-Transformer Hybrid Architecture for Effective video Frame Embeddings Prediction 2

MobileNetV2-Transformer Hybrid Architecture for Effective Vi...

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2nd IEEE International conference on Electrical, Automation and Computer Engineering, ICEACE 2024

作者： Zhang, Xiangyue Georgia Institute of Technology School of Computer Science AtlantaGA United States

ISBN: (纸本)9798350368208

In the realm of video processing and analysis, accurate prediction of future frames is crucial in applications like video compression, anomaly detection and augmented reality. This paper introduces a novel approach that leverages the powerful feature extraction capabilities of MobileNetV2 combined with the temporal sequence modeling strengths of Transformer models to predict the embeddings of following video frames. More specifically, the paper first employs the MobileNetV2 architecture to extract high-dimensional embeddings from individual frames, capitalizing on its efficiency and robustness in handling image data. These embeddings serve as a compact representation of the visual content of each frame. Then, a Transformer model is utilized to analyze the sequential nature of those embeddings, aiming to predict the embeddings of following frames. The Transformer's multi-head self-attention mechanism allows for an enhanced understanding of the temporal dynamics of the video, facilitating more accurate predictions compared with traditional methods. The paper later evaluates the method on test video datasets. The results indicate that the model needs further development such as incorporating a greater variety and quantity of experimental data. The method involved in the paper opens new avenues for real-time video analysis applications with the combination of Convolutional Neural Networks (CNNs) and Transformer models. The implications of this research extend to improve the performance of video-based systems across various domains, possibly indicating the potential of integrated architectures in advancing video analytic techniques. © 2024 IEEE.

关键词： video analysis

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ACCURATE MULTISCALE SELECTIVE FUSION OF CT AND video imageS FOR real-time ENDOSCOPIC CAMERA 3D TRACKING IN ROBOTIC SURGERY 47

ACCURATE MULTISCALE SELECTIVE FUSION OF CT AND VIDEO IMAGES ...

引用

47th IEEE International conference on Acoustics, Speech and Signal processing (ICASSP)

作者： Luo, Xiongbiao Xiamen Univ Dept Comp Sci Xiamen 36105 Peoples R China

ISBN: (纸本)9781665405409

Robotic surgery requires endoscope 3D tracking to navigate the endoscope in the body. This paper proposes an accurate multiscale selective fusion framework to register 2D endoscopic video images to 3D pre-operative CT data for endoscope 3D tracking. Current video-based 3D tracking depends on the performance of the 2D-3D fusion procedure that suffers from inaccurate similarity and image uncertainties. To boost video-based 3D tracking, we develop multiscale selective similarity characterization to enhance the 2D-3D fusion procedure. Such fusion not only uses image pyramids in multiple scales to represent endoscopic images but also selects specific structure information from these multiscale images to compute the similarity. We validated our method on clinical data. Our method can reduce the current tracking error from 8.9 to 5.4 mm without using any external trackers, while it provides surgeons with robust real-time surgical 3D tracking.

关键词： Endoscope Tracking Surgical Navigation 2D-3D Registration image Similarity Robotic Surgery

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video detection method of pointer instrument based on improved FCOS

Video detection method of pointer instrument based on improv...

引用

2022 International conference on Computer Graphics, Artificial Intelligence, and Data processing, ICCAID 2022

作者： Chen, Xi Zhang, Pengfei Xu, Wei Chang, Yongjuan Liu, Mingshuo Zhao, Zhenyuan State Grid Hebei Information &telecommunication Branch Shijiazhuang050000 China North China Electric Power University Hebei Baoding071003 China

ISBN: (纸本)9781510663350

Aiming at the problem that pointer instrument detection algorithm has slow locating speed and low real time performance in edge equipment, this paper proposes a pointer instrument video detection method based on improved FCOS. The algorithm is based on FCOS model and uses lightweight network ShuffleNetV2 to extract image features. Using PAN structure to strengthen the original feature fusion network, a bidirectional feature fusion network is formed. The attention module with global context information is introduced to reduce the information attenuation in the process of feature fusion. The two parameters of pixel utilization PUR and relative time increase RIT are introduced to test the influence of images with different image pixels on the detection effect in a more intuitive form. Through experiments, when the resolution of the input image is 1 280×1 280, compared with the baseline model, the detection time of the pointer instrument video detection method based on improved FCOS is reduced by 91.60% when the detection accuracy is similar. © 2023 SPIE.

关键词： Pixels

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Proceedings - 2024 IEEE 7th International conference on Multimedia Information processing and Retrieval, MIPR 2024

Proceedings - 2024 IEEE 7th International Conference on Mult...

引用

7th IEEE International conference on Multimedia Information processing and Retrieval, MIPR 2024

ISBN: (纸本)9798350351422

The proceedings contain 106 papers. The topics discussed include: macro-AUC-driven active learning strategy for multi-label classification enhancement;mitigating privacy threats without degrading visual quality of VR applications: using re-identification attack as a case study;attenuation-aware weighted optical flow with medium transmission map for learning-based visual odometry in underwater terrain;GeoVQA: a comprehensive multimodal geometry dataset for secondary education;pulse of the crowd: quantifying crowd energy through audio and video analysis;automated recognition of optic disc and blood vessels in diabetic fundoscopy images using real-time image analysis;GeoSecure-B: a method for secure bearing calculation;and exploiting correlation between facial action units for detecting deepfake videos.

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real time traffic classification and volume count using automated image processing

Real time traffic classification and volume count using auto...

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2025 International conference on Medical Imaging, Electronic Imaging, Information Technologies, and Sensors, MIEITS 2025

作者： Kamaruddin, A.S. Bahri, I. Ibrahim, A. Tey, L.S. Kuan, W.K. Yahaya, N.N. Ismail, A.P. BSA LAB Engineering No. 78 B LKNP Songsang Jl. Sri Semantan 4 Kg Padang Kerbau Pahang Temerloh 28000 Malaysia School of Civil Engineering UNITEC Institute of Technology 139 Carrington Rd Mt. Albert Campus Auckland 1025 New Zealand School of Civil Engineering College of Engineering Universiti Teknologi MARA Cawangan Pulau Pinang Kampus Permatang Pauh Permatang Pauh Pulau Pinang 13500 Malaysia School of Civil Engineering College of Engineering Universiti Teknologi MARA Selangor Shah Alam 40450 Malaysia School of Electrical Engineering College of Engineering Universiti Teknologi MARA Cawangan Pulau Pinang Kampus Permatang Pauh Permatang Pauh Pulau Pinang 13500 Malaysia

ISBN: (纸本)9781510691704

Conventional vehicle counting using various techniques such as manual counts are no longer efficient in the era of industrial revolution 4.0. The algorithm within the intelligence system using a real time video and image processing technique is proposed due to its reliability, efficiency, cost effectiveness and safety for gathering data. Surveillance cameras commonly installed in large cities could be used to obtain traffic data recording, allowing for an automated system to be easily adopted at minimal cost. This study provides an alternative and economical means to estimate traffic density via video-image processing which adopts OpenCV in the Python code. This method only requires a fixed video camera be positioned at an elevated position such as on a pedestrian bridge or a light pole. The images are processed automatically through OpenCV code bindings in Python. The system requires frames from the video to be captured so background subtraction can be performed to detect and count the vehicles using Gaussian Mixture Model. The classification of vehicles by size is done by comparing the contour areas to the assumed values. The proposed algorithm can be adapted to meet the requirements of the user and the camera’s position. The algorithm allows traffic data to be obtained, which may assist local authorities make decisions regarding urban planning and the design of transportation systems. Sample videos of traffic scenes were used to compare the detection and classification of vehicles. Results from the proposed algorithm were compared with manual count results from the field. Analysis of the classification and volume count of vehicles using the proposed algorithm is shown to have an error rate of 1.3% compared to an error rate of 6.4% using the manual tally counter method. The results confirmed that the proposed automatic counting system performed better when compared to the manual tally counter method with the additional benefits of increase cost efficiency and impr

关键词： Contour comparison Foreground extraction Gaussian Mixture Model image processing OpenCV real-time traffic classification Traffic data collection Vehicle counting

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2024 13th Mediterranean conference on Embedded Computing, MECO 2024

2024 13th Mediterranean Conference on Embedded Computing, ME...

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13th Mediterranean conference on Embedded Computing, MECO 2024

ISBN: (纸本)9798350387568

The proceedings contain 114 papers. The topics discussed include: application of artificial neural networks for processing some biomedical data;distinguishing between AI images and real images with hybrid image classification methods;securing Durres Port's digital transformation: cybersecurity strategy for maritime industry;linguistic encryption for underwater communication;a toolset for blood pressure visualization and measurement in time, frequency and time-frequency domains;using a shape from polarization to determine the 3D surface of objects with thermal radiation;on the influence of cell libraries and other parameters to SCA resistance of crypto IP cores;integration of PXROS-HR with micro-ROS in robotic systems;and traffic-aware video streaming topology reconfiguration for smart city applications.

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