Three-Dimensional Particle Tracking Velocimetry Based on Automated Digital Image Processing

1989 ◽  
Vol 111 (4) ◽  
pp. 384-391 ◽  
Author(s):  
Koichi Nishino ◽  
Nobuhide Kasagi ◽  
Masaru Hirata
Keyword(s):  
Image Processing ◽  
Turbulent Flows ◽  
Digital Image Processing ◽  
Digital Image ◽  
Particle Tracking ◽  
Three Dimensional ◽  
Image Processing Technique ◽  
Water Tank ◽  
Decaying Turbulence ◽  
Laser Disk

A three-dimensional particle tracking velocimeter for measuring an instantaneous distribution of all the three velocity components in a liquid flow is developed using an automated digital image processing technique. The measurement system consists of three TV cameras, a digital image processor, a laser disk recorder and a 16-bit microcomputer. Motions of neutrally buoyant tracer particles introduced into the flow field are observed by the cameras, and the three-dimensional displacement of each particle is calculated from consecutive TV frames recorded on the laser disk. Instantaneous velocity profiles in an unsteady laminar Couette flow between two concentric cylinders are measured. The results are in good agreement with predictions within the measurement uncertainties evaluated systematically. Furthermore, the measurement of a decaying turbulence in a stirred water tank demonstrates that the present technique is applicable to turbulent flows.

Diagnosis of the state of N in wheat via digital image processing technique

2012 ◽  
Vol 19 (5) ◽  
pp. 1168-1174
Author(s):  
Li-Zhou ZHANG ◽  
Xiao-Yu HOU ◽  
Yu-Ming ZHANG ◽  
Hong-Jun LI ◽  
Yi-Song CHENG ◽  
...  
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Processing Technique ◽  
The State ◽  
Image Processing Technique ◽  
Digital Image Processing Technique

Diagnosis of N nutrient status of corn using digital image processing technique

2010 ◽  
Vol 18 (6) ◽  
pp. 1340-1344
Author(s):  
Li-Zhou ZHANG ◽  
Dian-Wu WANG ◽  
Yu-Ming ZHANG ◽  
Yi-Song CHENG ◽  
Hong-Jun LI ◽  
...  
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Nutrient Status ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Digital Image Processing Technique

Micro-Flow-Cytometer Integrated witch Optical Tweezer and DIP Technique for Cell/Particle Sorting and Manipulation

2007 ◽  
Vol 121-123 ◽  
pp. 1351-1354
Author(s):  
Yu Sheng Chien ◽  
Che Hsin Lin ◽  
Fu Jen Kao ◽  
Cheng Wen Ko
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
High Performance ◽  
Optical Tweezer ◽  
Processing Technique ◽  
Microfluidic System ◽  
Image Processing Technique ◽  
Target Cells ◽  
Digital Image Processing Technique

This paper proposes a novel microfluidic system for cell/microparticle recognition and manipulation utilizing digital image processing technique (DIP) and optical tweezer under microfluidic configuration. Digital image processing technique is used to count and recognize the cell/particle samples and then sends a control signal to generate a laser pulse to manipulate the target cell/particle optically. The optical tweezer system is capable of catching, moving and switching the target cells at the downstream of the microchannel. The trapping force of the optical tweezer is also demonstrated utilizing Stocks-drag method and electroosmotic flow. The proposed system provides a simple but high-performance solution for microparticle manipulation in a microfluidic device.

scholarly journals Predict Growth Stages of Wheat Crop using Digital Image Processing

2020 ◽  
Vol 8 (5) ◽  
pp. 3026-3035
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Processing Technique ◽  
Mean Value ◽  
Image Processing Technique ◽  
Wheat Crop ◽  
Growth Stages ◽  
Increase Productivity ◽  
Crop Growth Stages

Manual examination is not as accurate to examine crop growing stages because of the possibility of the human mistake and errors. While machine examination or automatic examination can easily examine crop growing stages and increase productivity because it provides fast and accurate examine result. This study provide a solution to finding the wheat crop growth stages, Once the growing stages are established, farmers can take suitable and measured steps to improve the production of wheat or other agricultural crops. For finding the growth stages of wheat digital image processing technique is used. RGB model, HSI model, mean value of green colour, hue and saturation images use for examining wheat crop.

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