scholarly journals Fast Frame Synchronization Design and FPGA Implementation in SF-BOTDA

Photonics ◽  
2020 ◽  
Vol 7 (1) ◽  
pp. 17
Author(s):  
Qiuyi Pan ◽  
Xincheng Huang ◽  
Rui Min ◽  
Weiping Liu
Keyword(s):  
Real Time ◽  
Time Domain Analysis ◽  
Frame Synchronization ◽  
System A ◽  
Synchronization Algorithm ◽  
Field Programmable ◽  
Time Requirements ◽  
Optical Time ◽  
Time Required ◽  
Standard Frame

To address the issues of high time consumption of frame synchronization involved in a scanning-free Brillouin optical time-domain analysis (SF-BOTDA) system, a fast frame synchronization algorithm based on incremental updating was proposed. In comparison to the standard frame synchronization algorithm, the proposed one significantly reduced the processing time required for the BOTDA system frame synchronization by about 98%. In addition, to further accelerate the real-time performance of frame synchronization, a field programmable gate array (FPGA) hardware implementation architecture based on parallel processing and pipelining mechanisms was also proposed. Compared with the software implementation, it further raised the processing speed by 13.41 times. The proposed approach could lay a foundation for the BOTDA system in the field with the associated high real-time requirements.

The Mathematical Morphology Image Edge Detection Based on FPGA

2013 ◽  
Vol 467 ◽  
pp. 599-603 ◽  
Author(s):  
Hui De Li ◽  
Lian Yu Zhao
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Real Time ◽  
Mathematical Morphology ◽  
Detection Algorithm ◽  
Image Edge Detection ◽  
Result Show ◽  
Field Programmable ◽  
Time Requirements ◽  
Image Edge

The image edge detection algorithm is one of the most important steps in the image processing, however, while the large amount of data is need to be dealt with in the detection process, it is difficult to meet real-time requirements by using the software method. In order to improve the speed of digital image processing, An embedded processing systems based on FPGA (field-programmable gate array) detection algorithm is proposed, which takes corrosion expansion algorithm of mathematical morphology as its theoretical basis to achieve the task of image edge detection, experiments result show the method is effective and feasible, and meets the real-time requirement of the image processing.

scholarly journals Visual-Feedback-Based Frame-by-Frame Synchronization for 3000 fps Projector–Camera Visual Light Communication

Electronics ◽  
2021 ◽  
Vol 10 (14) ◽  
pp. 1631
Author(s):  
Atul Sharma ◽  
Sushil Raut ◽  
Kohei Shimasaki ◽  
Taku Senoo ◽  
Idaku Ishii
Keyword(s):  
Real Time ◽  
Visual Feedback ◽  
Video Sequence ◽  
Clock Cycle ◽  
Frame Rate ◽  
Video Sequences ◽  
Frame Synchronization ◽  
Bandwidth Utilization ◽  
Long Distance ◽  
Synchronization Algorithm

This paper proposes a novel method for synchronizing a high frame-rate (HFR) camera with an HFR projector, using a visual feedback-based synchronization algorithm for streaming video sequences in real time on a visible-light communication (VLC)-based system. The frame rates of the camera and projector are equal, and their phases are synchronized. A visual feedback-based synchronization algorithm is used to mitigate the complexities and stabilization issues of wire-based triggering for long-distance systems. The HFR projector projects a binary pattern modulated at 3000 fps. The HFR camera system operates at 3000 fps, which can capture and generate a delay signal to be given to the next camera clock cycle so that it matches the phase of the HFR projector. To test the synchronization performance, we used an HFR projector–camera-based VLC system in which the proposed synchronization algorithm provides maximum bandwidth utilization for the high-throughput transmission ability of the system and reduces data redundancy efficiently. The transmitter of the VLC system encodes the input video sequence into gray code, which is projected via high-definition multimedia interface streaming in the form of binary images 590 × 1060. At the receiver, a monochrome HFR camera can simultaneously capture and decode 12-bit 512 × 512 images in real time and reconstruct a color video sequence at 60 fps. The efficiency of the visual feedback-based synchronization algorithm is evaluated by streaming offline and live video sequences, using a VLC system with single and dual projectors, providing a multiple-projector-based system. The results show that the 3000 fps camera was successfully synchronized with a 3000 fps single-projector and a 1500 fps dual-projector system. It was confirmed that the synchronization algorithm can also be applied to VLC systems, autonomous vehicles, and surveillance applications.

EFFICIENT ARCHITECTURES FOR SEGMENTATION OF ENDOSCOPIC IMAGES IN MICRO-ROBOTIC AUTO NAVIGATION SYSTEMS

2006 ◽  
Vol 03 (04) ◽  
pp. 523-545 ◽  
Author(s):  
C. S. LIM ◽  
S. K. LAM ◽  
H. TIAN ◽  
T. SRIKANTHAN
Keyword(s):  
Real Time ◽  
High Performance ◽  
Region Of Interest ◽  
Navigation Systems ◽  
Endoscopic Images ◽  
Field Programmable ◽  
Filter Operation ◽  
Otsu’S Method ◽  
Hardware Resource ◽  
Time Requirements

This paper presents novel techniques and their architectural translations for real-time image segmentation of endoscopic images, which are required for micro-robotic auto navigation systems. The proposed technique is based on a two-step process to segment the lumen regions from endoscopic images. In the first step, an adaptive progressive thresholding technique based on Otsu's method is employed to obtain a preliminary region of interest of the lumen region. A novel architecture for the between-class variance computation of Otsu's method is presented to meet the real-time requirements of the system. The proposed implementation employs binary logarithmic computations to eliminate the complex divisions and multiplications in Otsu's procedure. In the second step, an Iris filter is employed to enhance the boundary of the region of interest to facilitate an accurate detection of the lumen region. An architecture based on the coordinate rotation digital computer is proposed to simplify the complex computations of trigonometric functions required by the Iris filter operation. Software simulations demonstrate that the proposed technique requires a significantly smaller number of iterations to obtain an accurate segmentation result as compared to a previously reported method. In addition, synthesis results on the field-programmable gate array show that the proposed architectures can achieve high performance with low hardware resource utilization.

Real-time signal processing in field programmable gate array based digital gamma-ray spectrometer

2020 ◽  
Vol 91 (10) ◽  
pp. 104707
Author(s):  
Yinyu Liu ◽  
Hao Xiong ◽  
Chunhui Dong ◽  
Chaoyang Zhao ◽  
Quanfeng Zhou ◽  
...  
Keyword(s):  
Signal Processing ◽  
Real Time ◽  
Field Programmable Gate Array ◽  
Gamma Ray ◽  
Time Signal ◽  
Gamma Ray Spectrometer ◽  
Field Programmable ◽  
Gate Array ◽  
Real Time Signal Processing

scholarly journals Intelligent IoT systems for civil infrastructure health monitoring: a research roadmap

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
E. Bertino ◽  
M. R. Jahanshahi ◽  
A. Singla ◽  
R.-T. Wu
Keyword(s):  
Data Acquisition ◽  
Real Time ◽  
Original Data ◽  
Local Analysis ◽  
Civil Infrastructure ◽  
Time Requirements ◽  
Iot Devices ◽  
Learning Reinforcement ◽  
The Times ◽  
Acquisition Processes

AbstractThis paper addresses the problem of efficient and effective data collection and analytics for applications such as civil infrastructure monitoring and emergency management. Such problem requires the development of techniques by which data acquisition devices, such as IoT devices, can: (a) perform local analysis of collected data; and (b) based on the results of such analysis, autonomously decide further data acquisition. The ability to perform local analysis is critical in order to reduce the transmission costs and latency as the results of an analysis are usually smaller in size than the original data. As an example, in case of strict real-time requirements, the analysis results can be transmitted in real-time, whereas the actual collected data can be uploaded later on. The ability to autonomously decide about further data acquisition enhances scalability and reduces the need of real-time human involvement in data acquisition processes, especially in contexts with critical real-time requirements. The paper focuses on deep neural networks and discusses techniques for supporting transfer learning and pruning, so to reduce the times for training the networks and the size of the networks for deployment at IoT devices. We also discuss approaches based on machine learning reinforcement techniques enhancing the autonomy of IoT devices.

scholarly journals Influence of Features on Accuracy of Anomaly Detection for an Energy Trading System

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4237
Author(s):  
Hoon Ko ◽  
Kwangcheol Rim ◽  
Isabel Praça
Keyword(s):  
Anomaly Detection ◽  
Real Time ◽  
Feature Detection ◽  
Trading System ◽  
Judgment Accuracy ◽  
Energy Trading ◽  
Real Time Processing ◽  
Detection Model ◽  
Time Required ◽  
The Relationship

The biggest problem with conventional anomaly signal detection using features was that it was difficult to use it in real time and it requires processing of network signals. Furthermore, analyzing network signals in real-time required vast amounts of processing for each signal, as each protocol contained various pieces of information. This paper suggests anomaly detection by analyzing the relationship among each feature to the anomaly detection model. The model analyzes the anomaly of network signals based on anomaly feature detection. The selected feature for anomaly detection does not require constant network signal updates and real-time processing of these signals. When the selected features are found in the received signal, the signal is registered as a potential anomaly signal and is then steadily monitored until it is determined as either an anomaly or normal signal. In terms of the results, it determined the anomaly with 99.7% (0.997) accuracy in f(4)(S0) and in case f(4)(REJ) received 11,233 signals with a normal or 171anomaly judgment accuracy of 98.7% (0.987).

Accelerating laser processes with a smart two-dimensional polygon mirror scanner for ultra-fast beam deflection

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Florian Roessler ◽  
André Streek
Keyword(s):  
Energy Distribution ◽  
Real Time ◽  
Laser Processing ◽  
High Speed ◽  
Beam Deflection ◽  
Two Dimensional ◽  
Heat Accumulation ◽  
Field Programmable ◽  
Drill Holes ◽  
Average Laser

Abstract In laser processing, the possible throughput is directly scaling with the available average laser power. To avoid unwanted thermal damage due to high pulse energy or heat accumulation during MHz-repetition rates, energy distribution over the workpiece is required. Polygon mirror scanners enable high deflection speeds and thus, a proper energy distribution within a short processing time. The requirements of laser micro processing with up to 10 kW average laser powers and high scan speeds up to 1000 m/s result in a 30 mm aperture two-dimensional polygon mirror scanner with a patented low-distortion mirror configuration. In combination with a field programmable gate array-based real-time logic, position-true high-accuracy laser switching is enabled for 2D, 2.5D, or 3D laser processing capable to drill holes in multi-pass ablation or engraving. A special developed real-time shifter module within the high-speed logic allows, in combination with external axis, the material processing on the fly and hence, processing of workpieces much larger than the scan field.

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