scholarly journals Design of Image Processing System on Pressure Varied Using Interferometer Mach-Zehnder

2019 ◽  
Vol 2 ◽  
pp. 241-244
Author(s):  
Mujib Abdullah ◽  
Frida Agung Rakhmadi
Keyword(s):  
Image Processing ◽  
Processing System ◽  
Light Sources ◽  
Interference Phenomenon ◽  
Image Processing System ◽  
Light Interference ◽  
Measurement Results ◽  
Interference Ring ◽  
Light Darkness ◽  
The Difference

Quantitative analysis and visualization of light becomes very important when we understand the nature of light, namely interference. This also applies to light-darkness conditions (such as the nature of light when an interference phenomenon occurs) and the application of light-propagating light (such as the wavelength traveled by light in the airspace or pressurized space). Because in the nature of light requires experimental observations and program algorithms that utilize the process of analyzing the nature of the light that occurs (interferometer). This study aims to design an image processing system design to obtain qualitative from the nature of light interference. Large quantitative interference ring measurement trials were carried out using the width measurement results on the observation board which varied at pressures of 0, -100, -200, -300, -400, and -500 which were given light sources from the red laser. From the measurement results obtained the difference between rings on the board in the form of area. The area can be compared manually to get the uncertainty of the sidewall fabrication that gives an error in the measurement.

An image processing technique for the observation of the viability of Steinernema carpocapsae in spray application research

Nematology ◽  
2010 ◽  
Vol 12 (1) ◽  
pp. 105-113 ◽  
Author(s):  
Nicole Viaene ◽  
Winy Messens ◽  
David Nuyttens ◽  
Maurice Moens ◽  
Nancyde Sutter ◽  
...  
Keyword(s):  
Image Processing ◽  
Sodium Chloride ◽  
Entomopathogenic Nematodes ◽  
Processing System ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Spray Application ◽  
Application Research ◽  
Image Processing System ◽  
The Difference

AbstractDamage caused to entomopathogenic nematodes by spray application is generally assessed by observing the viability of the infective juveniles under the microscope. To improve the quality and speed of this observation we developed an image processing technique and tested the efficacy of acetic acid and sodium chloride as chemical stimulants. Because of the lower standard error on the results obtained (0.7 vs 1.7), sodium chloride was eventually selected for all subsequent observations. The viability as observed with the image processing technique rose significantly with the time after the nematodes were suspended in water; however, viability as observed under the microscope was not influenced by the time. These differences can be attributed to the difference in type of stimulant (mechanical vs chemical) used. After nematodes had been in suspension for 3.5 h, the viability as measured using the image processing system was still significantly lower than the viability as measured under the microscope. This difference did not disappear after 24 h at 4, 15 or 24°C. Maintaining nematodes for 24 h at 35°C significantly decreased the viability to 5.9% (microscope) or 11.0% (image processing technique). The decrease in viability as observed with the image processing system corresponded better with the decrease in infectivity (i.e., 13.8%). Our results support further use of the image processing technique, not only to observe the viability of entomopathogenic nematodes but also to count the mobile or total number of nematodes of any species.

Software pattern recognition applied to nanodiffraction patterns from a STEM instrument

1986 ◽  
Vol 44 ◽  
pp. 694-695
Author(s):  
G.Y. Fan ◽  
J.M. Cowley
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Computer Software ◽  
Processing System ◽  
Light Level ◽  
Host Computer ◽  
Low Light ◽  
Image Processing System ◽  
Recent Developments ◽  
On Line

In recent developments, the ASU HB5 has been modified so that the timing, positioning, and scanning of the finely focused electron probe can be entirely controlled by a host computer. This made the asynchronized handshake possible between the HB5 STEM and the image processing system which consists of host computer (PDP 11/34), DeAnza image processor (IP 5000) which is interfaced with a low-light level TV camera, array processor (AP 400) and various peripheral devices. This greatly facilitates the pattern recognition technique initiated by Monosmith and Cowley. Software called NANHB5 is under development which, instead of employing a set of photo-diodes to detect strong spots on a TV screen, uses various software techniques including on-line fast Fourier transform (FFT) to recognize patterns of greater complexity, taking advantage of the sophistication of our image processing system and the flexibility of computer software.

Massive Image Treatment System Based on Cloud Computing Platform

2014 ◽  
Vol 687-691 ◽  
pp. 3733-3737
Author(s):  
Dan Wu ◽  
Ming Quan Zhou ◽  
Rong Fang Bie
Keyword(s):  
Image Processing ◽  
Cloud Computing ◽  
High Performance ◽  
Large Scale ◽  
Processing System ◽  
Virtual Space ◽  
Image Processing System ◽  
Computing Platform ◽  
Simulation Calculation ◽  
Computer Resources

Massive image processing technology requires high requirements of processor and memory, and it needs to adopt high performance of processor and the large capacity memory. While the single or single core processing and traditional memory can’t satisfy the need of image processing. This paper introduces the cloud computing function into the massive image processing system. Through the cloud computing function it expands the virtual space of the system, saves computer resources and improves the efficiency of image processing. The system processor uses multi-core DSP parallel processor, and develops visualization parameter setting window and output results using VC software settings. Through simulation calculation we get the image processing speed curve and the system image adaptive curve. It provides the technical reference for the design of large-scale image processing system.

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