Data Monitoring of Athlete Physical Training Based on FPGA Processing System and Machine Vision

2021 ◽  
pp. 103875
Author(s):  
Li Xiao
Keyword(s):  
Machine Vision ◽  
Physical Training ◽  
Processing System ◽  
Data Monitoring

Developing an orientation and cutting point determination algorithm for a trout fish processing system using machine vision

2019 ◽  
Vol 162 ◽  
pp. 613-629 ◽  
Author(s):  
Hossein Azarmdel ◽  
Seyed Saeid Mohtasebi ◽  
Ali Jafari ◽  
Alfredo Rosado Muñoz
Keyword(s):  
Machine Vision ◽  
Processing System ◽  
Fish Processing ◽  
Point Determination ◽  
Cutting Point

scholarly journals An Automatic Machine Vision-Guided System for the Propagation of Potato Test-Tube Plantlets

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Xu Shengyong ◽  
Peng Biye ◽  
Wu Haiyang ◽  
Li Fushuai ◽  
Cai Xingkui ◽  
...  
Keyword(s):  
Image Processing ◽  
Machine Vision ◽  
Vision System ◽  
Image Acquisition ◽  
Processing System ◽  
Test Tube ◽  
Automatic Machine ◽  
Node Point ◽  
Acquisition Device ◽  
Image Acquisition Device

In manually propagating potato test-tube plantlets (PTTPs), the plantlet is usually grasped and cut at the node point between the cotyledon and stem, which is hardly located and is easily damaged by the gripper. Using an agricultural intelligent robot to replace manual operation will greatly improve the efficiency and quality of the propagation of PTTPs. An automatic machine vision-guided system for the propagation of PTTPs was developed and tested. In this paper, the workflow of the visual system was designed and the image acquisition device was made. Furthermore, the image processing algorithm was then integrated with the image acquisition device in order to construct an automatic PTTP propagation vision system. An image processing system for locating a node point was employed to determine a suitable operation point on the stem. A binocular stereo vision algorithm was applied to compute the 3D coordinates of node points. Finally, the kinematics equation of the three-axis parallel manipulator was established, and the three-dimensional coordinates of the nodes were transformed into the corresponding parameters X, Y, and Z of the three driving sliders of the manipulator. The experimental results indicated that the automatic vision system had a success rate of 98.4%, 0.68 s time consumed per 3 plants, and approximate 1 mm location error in locating the plantlets in an appropriate position for the medial expansion period (22 days).

Surface Defect Inspection and Classification of Segment Magnet by Using Machine Vision Technique

2011 ◽  
Vol 339 ◽  
pp. 32-35 ◽  
Author(s):  
Hong Hai Jiang ◽  
Guo Fu Yin
Keyword(s):  
Image Processing ◽  
Machine Vision ◽  
Surface Defects ◽  
Processing System ◽  
Support Vector ◽  
Inspection System ◽  
Low Contrast ◽  
Constituent Material ◽  
Canny Edge

In this paper, we propose a machine vision based approach for detecting and classifying irregular low-contrast surface defects of segment magnet. The constituent material of it is ferrite which varies from silver gray to black in color .For this reason, the defects embedded in a low-contrast surface show no big different from its surrounding region, and even worse, all the surfaces and chamfers of segment magnet must be inspected. Our system is able to analyze all surfaces under inspection, to discover and classify its defects by means of image processing algorithms and support vector machine (SVM). A working prototype of the system has been built and tested to validate the proposed approach and to reproduce the difficult issues of the inspection system. The developed prototype includes three subsystems: an array of several CCD area cameras (Fig.1); a controllable roller LED light source(Fig.1); and a PC-based image processing system. The detection of the defects is performed by means of Canny edge detection, morphology and other feature extraction operations. The image processing and classification results demonstrate that the proposed method can identify surface defects effectively.

scholarly journals CADDMAS: A Real-Time Parallel System for Dynamic Data Analysis

1994 ◽  
Author(s):  
Thomas F. Tibbals ◽  
Theodore A. Bapty ◽  
Ben A. Abbott
Keyword(s):  
Real Time ◽  
Message Passing ◽  
High Speed ◽  
Low Frequency ◽  
Processing System ◽  
Data Monitoring ◽  
Critical Parameters ◽  
Computer Assisted ◽  
Dynamic Data ◽  
Parallel Network

Arnold Engineering Development Center (AEDC) has designed and built a high-speed data acquisition and processing system for real-time online dynamic data monitoring and analysis. The Computer Assisted Dynamic Data Monitoring and Analysis System (CADDMAS) provides 24 channels at high frequency and another 24 channels at low frequency for online real-time aeromechanical, vibration, and performance analysis of advanced turbo-engines and other systems. The system is primarily built around two different parallel processors and several PCs to demonstrate hardware independence and architecture scalability. These processors provide the computational power to display online and in real-time what can take from days to weeks using existing offline techniques. The CADDMAS provides online test direction and immediate hardcopy plots for critical parameters, all the while providing continuous health monitoring through parameter limit checking. Special in-house developed Front End Processors (FEP) sample the dynamic signals, perform anti-aliasing, signal transfer function correction, and bandlimit filtering to improve the accuracy of the time domain signal. A second in-house developed Numeric Processing Element (NPE) performs the FFT, threshold monitoring, and packetizes the data for rapid asynchronous access by the parallel network. Finally, the data are then formatted for display, hardcopy plotting, and cross-channel processing within the parallel network utilizing off-the-shelf hardware. The parallel network is a heterogeneous message-passing parallel pipeline configuration which permits easy scaling of the system. Advanced parallel processing scheduler/controller software has been adapted specifically for CADDMAS to allow quasi-dynamic instantiation of a variety of simultaneous data processing tasks concurrent with display and alarm monitoring functions without gapping the data. Although many applications of CADDMAS exist, this paper describes the features of CADDMAS, the development approach, and the application of CADDMAS for turbine engine aeromechanical testing.

scholarly journals A New Approach to Spindle Radial Error Evaluation Using a Machine Vision System

2017 ◽  
Vol 24 (1) ◽  
pp. 201-219 ◽  
Author(s):  
C. Kavitha ◽  
S. Denis Ashok
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Processing System ◽  
Dimensional Accuracy ◽  
New Approach ◽  
Master Cylinder ◽  
Radial Error ◽  
Spindle Rotation ◽  
Least Squares Curve Fitting ◽  
Fourier Series Analysis

AbstractThe spindle rotational accuracy is one of the important issues in a machine tool which affects the surface topography and dimensional accuracy of a workpiece. This paper presents a machine-vision-based approach to radial error measurement of a lathe spindle using a CMOS camera and a PC-based image processing system. In the present work, a precisely machined cylindrical master is mounted on the spindle as a datum surface and variations of its position are captured using the camera for evaluating runout of the spindle. TheCircular Hough Transform(CHT) is used to detect variations of the centre position of the master cylinder during spindle rotation at subpixel level from a sequence of images. Radial error values of the spindle are evaluated using the Fourier series analysis of the centre position of the master cylinder calculated with the least squares curve fitting technique. The experiments have been carried out on a lathe at different operating speeds and the spindle radial error estimation results are presented. The proposed method provides a simpler approach to on-machine estimation of the spindle radial error in machine tools.

Embedded Machine Vision System Design Based on Davinci DM355

2013 ◽  
Vol 300-301 ◽  
pp. 729-734
Author(s):  
Hong Rui Ma ◽  
Jian Xian Cai ◽  
Rui Hong Yu
Keyword(s):  
Machine Vision ◽  
Low Power ◽  
Vision System ◽  
Processing System ◽  
Machine Vision System ◽  
Processor Core ◽  
Digital Multimedia ◽  
Development Platform ◽  
Vision Processing ◽  
Risc Processor

Most existing machine vision processing system is 8-bit or 16-bit processor control system, complex algorithms and multi-tasking of the vision system have been severely constrained. DaVinci DM355 integrated ARM926 RISC processor core and specialized image processor is a programmable DMSoC development platform with digital multimedia codecs, high integration, low-power consumption. The machine vision system based on DaVinci DM355 development goal is to establish a low-power hardware development board based on the DaVinci DM355, transplant Linux operating system based on the hardware board and develop corresponding driver.This will provide the basis for the realization of complex algorithm and multitasking system for machine vision system.

Development and Design of Smart-Robot Image Transmission and Processing System Based on On-Line Control

2014 ◽  
Vol 602-605 ◽  
pp. 813-816
Author(s):  
Lin Cai
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Rapid Development ◽  
Processing System ◽  
Image Transmission ◽  
Network Control ◽  
Research Network ◽  
Network Technology ◽  
Motion Feature ◽  
Robot Technology

With the rapid development of network technology, communication technology and multimedia technology, and robot technology is getting mature, network control robot system has gradually become a main direction of current robot research. Network based robot refers to the public through the network and the control operation of the robot Shi Yuancheng. Study on the idea of network robot is the network technology and robot technology integration together, through the network to control the robot. In the network of the robot, machine vision plays a more and more important role. To a strange environment of robot control, observed the function of an image. Machine vision can not only according to the characteristics of image recognition, robot path, but also can provide visual understanding of the observation space to strange environment and to control the robot. It is also belongs to the field of robot visual category for image transmission and processing technology on the essence of robot network control. The vision system of robot is a machine vision system, refers to the use of computer to realize the vision function of the people, is to use computer to achieve the objective of 3D world understanding.[5] The so-called three-dimensional understanding refers to the observed object shape, size, texture and motion feature distance, leaving on the understanding of the concept of robot design.

Automated Raw-Fish Processing System Using Machine Vision

2013 ◽  
Vol 19 (11) ◽  
pp. 3196-3200
Author(s):  
Yu-Teng Liang ◽  
Yih-Chih Chiou
Keyword(s):  
Machine Vision ◽  
Processing System ◽  
Fish Processing ◽  
Raw Fish

Edible Bird Nest Processing using Machine Vision and Robotic Arm

2015 ◽  
Vol 72 (2) ◽  
Author(s):  
Yuvarajoo Subramaniam ◽  
Yeong Che Fai ◽  
Eileen Su Lee Ming
Keyword(s):  
Machine Vision ◽  
Large Scale ◽  
Vision System ◽  
Industrial Robot ◽  
Processing System ◽  
Food Product ◽  
Cost Effective ◽  
Automated System ◽  
Scale Production ◽  
Bird Nest

Edible Bird nest food product is one of the demanding food product in food production industry. Government looking into ways to improve this industry to boost the economy. Many large scale production are being operated around Malaysia. One of the major difficulties faced in processing the bird nest is to remove its impurities or more formerly known as dirt. Current conventional cleaning method which is manual cleaning is not cost effective and time consuming. Furthermore, it also requires large number of workforce to be used for processing small quantities of bird nest. This paper presents an automated system which utilizes machine vision system and an industrial robot to accomplish a better processing system for edible bird nest. This system offers great advantage compared to conventional process by reducing the time consumed for processing and increase the efficiency.

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