A One-Megapixel Image Acquisition And Processing System For Solar Oscillation Studies

1986 ◽  
Author(s):  
Edward J. Rhodes, Jr. ◽  
Thomas K. Bursch ◽  
Roger K. Ulrich ◽  
Steven Tomczyk
Keyword(s):  
Image Acquisition ◽  
Processing System ◽  
Solar Oscillation

High-Speed Visible Image Acquisition and Processing System for Plasma Shape and Position Control of EAST Tokamak

2018 ◽  
Vol 46 (5) ◽  
pp. 1312-1317 ◽  
Author(s):  
Heng Zhang ◽  
Bingjia Xiao ◽  
Zhengping Luo ◽  
Qin Hang ◽  
Jianhua Yang
Keyword(s):  
High Speed ◽  
Position Control ◽  
Image Acquisition ◽  
Processing System ◽  
Visible Image

The Research and Design of Portable Leaf Disease Spots Image Acquisition System

2011 ◽  
Vol 128-129 ◽  
pp. 1480-1483
Author(s):  
Kai Song ◽  
Zhe Wang ◽  
Feng Ju Shen
Keyword(s):  
High Performance ◽  
Low Cost ◽  
Image Acquisition ◽  
Processing System ◽  
Image Features ◽  
Acquisition System ◽  
Ultra Low Power ◽  
Real Time Processing ◽  
Leaf Disease ◽  
Image Acquisition System

The crop leaf disease spots image recognition technology has a great significance in identifying diseases and in effective spraying of pesticides to liminate diseases. We researched and designed the portable leaf disease spots image acquisition system since current PC-based processing system is high cost and lack of flexibility and real-timing, This system uses a high-performance 32-bit DSP chip based DM642 as its main processor, and also uses ultra-low power consumption and ultra-small size video decoder chips, large-capacity memories and high-performance communicator interfaces. As a result of the reasonable design of hardware architecture, this system realized leaf disease spots image features collecting and processing ，video transmitting, and achieved strong real-time processing capability, easy operation, low cost, anti-interference ability and other characteristics. The system prototype works well, and meets the design requirements.

High-performance image acquisition and processing system with MTCA.4

2014 ◽  
Author(s):  
D. Makowski ◽  
A. Mielczarek ◽  
P. Perek ◽  
G. Jablonski ◽  
M. Orlikowski ◽  
...  
Keyword(s):  
High Performance ◽  
Image Acquisition ◽  
Processing System

scholarly journals A VERSATILE MULTI-CAMERA SYSTEM FOR 3D ACQUISITION AND MODELING

2020 ◽  
Vol XLIII-B2-2020 ◽  
pp. 785-790
Author(s):  
O. Lanz ◽  
F. Sottsas ◽  
M. Conni ◽  
M. Boschetti ◽  
E. Nocerino ◽  
...  
Keyword(s):  
Low Cost ◽  
Image Acquisition ◽  
Processing System ◽  
3D Models ◽  
Surface Generation ◽  
Joint Work ◽  
Camera System ◽  
Reconstruction Process ◽  
Reconstruction Methods ◽  
3D Digitization

Abstract. Image-based 3D models generation typically involves three stages, namely: 2D image acquisition, data processing, and 3D surface generation and editing. The availability of different easy-to-use and low-cost image acquisition solutions, combined with open-source or commercial processing tools, has democratized the 3D reconstruction and digital twin generation. But high geometric and texture fidelity on small- to medium-scale objects as well as integrated commercial system for mass 3D digitization are not available. The paper presents our effort to build such a system, i.e. a market-ready multi-camera solution and a customized reconstruction process for mass 3D digitization of small to medium objects. The system is realized as a joint work between industrial and academic partners, in order to employ the latest technologies for the needs of the market. The proposed versatile image acquisition and processing system pushes to the limits the 3D digitization pipeline combining a rigid capturing system with photogrammetric reconstruction methods.

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).

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