IR camera system with an advanced image processing technologies

2016 ◽  
Author(s):  
Syuichi Ohkubo ◽  
Tetsuo Tamura
Keyword(s):  
Image Processing ◽  
Camera System ◽  
Ir Camera ◽  
Processing Technologies

An Infrared Microscope for Use on a Focused Ion Beam for Circuit Edit and Backside Edit Applications

2015 ◽  
Author(s):  
Alexander Richards ◽  
Matthew Weschler ◽  
Michael Durller
Keyword(s):  
Focused Ion Beam ◽  
Near Infrared ◽  
Ion Beam ◽  
Visible Spectrum ◽  
Camera System ◽  
Buried Structures ◽  
Ir Camera ◽  
Area Of Interest ◽  
Near Ultraviolet ◽  
Infrared Microscope

Abstract To help solve the navigational problem, i.e., being able to successfully locate a circuit for probing or editing without destroying chip functionality, a near-infrared (NIR), near-ultraviolet (NUV), and visible spectrum camera system was developed that attaches to most focused ion beam (FIB) or scanning electron microscope vacuum chambers. This paper reviews the details of the design and implementation of the NIR/NUV camera system, as instantiated upon the FEI FIB 200, with a particular focus on its use for the visualization of buried structures, and also for non-destructive real time area of interest location and end point detection. It specifically considers the use of the micro-optical camera system for its benefit in assisting with frontside and backside circuit edit, as well as other typical FIB milling activities. The quality of the image obtained by the IR camera rivals or exceeds traditional optical based imaging microscopy techniques.

A Hair Volume Analysis System Using Deep Learning and Image Processing Technologies

2021 ◽  
Author(s):  
Ming-Che Chen ◽  
Wan-Jung Chang ◽  
Yu-Xiang Xiao ◽  
Zi-Xuan Zhang ◽  
Yi-Chan Chiu ◽  
...  
Keyword(s):  
Image Processing ◽  
Deep Learning ◽  
Processing Technologies ◽  
Volume Analysis ◽  
Analysis System

Image Processing To Aid in Graphene Detection

2014 ◽  
Vol 1702 ◽  
Author(s):  
Ryan D. Gorby ◽  
Lihong (Heidi) Jiao
Keyword(s):  
Image Processing ◽  
Single Layer ◽  
Optical Microscope ◽  
Single Layer Graphene ◽  
Camera System ◽  
Layer Graphene ◽  
Sophisticated Equipment ◽  
Processing Software ◽  
Image Processing Software ◽  
Few Layer Graphene

ABSTRACTQualitative techniques for the detection of graphene on a Si/SiO2 substrate, without the use of sophisticated equipment, are presented. Once calibrated, this technique can be used to detect Single Layer Graphene (SLG) and Few Layer Graphene (FLG) with the use of an inexpensive optical microscope (OM), OM camera system, and image processing software. This technique could be transferred to graphene deposited on other substrates or other 2-D materials with minor updates to mathematical theory.

Study on Soil Particle Size Distribution by Digital Image Processing

2013 ◽  
Vol 788 ◽  
pp. 627-630
Author(s):  
Jian Shu Hou
Keyword(s):  
Mechanical Property ◽  
Image Processing ◽  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Digital Image ◽  
Traditional Method ◽  
Processing Method ◽  
Distribution Analysis ◽  
Processing Technologies

The particle size distribution of soil is very importantto its physical and mechanical property. The ordinary method of the particlesize distribution analysis is based on shaking the soil through a set of sieves.But it will be difficult to use the method while there have particles largerthan the biggest aperture of the size sieves. Then the digital image processingwas used to solve the problem here. The processing technologies, such as imageanalysis and enhancement, deblurring, edge detection were studied to analyzethe image of soil particles. Then the image processing method was used to getthe particle size distribution accurately. Though some promotions need to becarried out in the further study, it is can be found that the image processingmethod is more efficiently than the traditional method.

Rapid and non-invasive surface crack detection for pressed-panel products based on online image processing

2019 ◽  
Vol 18 (5-6) ◽  
pp. 1928-1942 ◽  
Author(s):  
Hwee Kwon Jung ◽  
Gyuhae Park
Keyword(s):  
Image Processing ◽  
Manufacturing Process ◽  
Crack Detection ◽  
Experimental Results ◽  
Inspection System ◽  
Camera System ◽  
Non Invasive ◽  
Panel Products ◽  
Traditional Approaches ◽  
Detection And Localization

Crack detection during the manufacturing process of pressed-panel products is an important aspect of quality management. Traditional approaches for crack detection of those products are subjective and expensive because they are usually performed by experienced human inspectors. Therefore, the development and implementation of an automated and accurate inspection system is required for the manufacturing process. In this article, a crack detection technique based on image processing is proposed that utilizes the images of panel products captured by a regular camera system. First, the binary panel object image is extracted from various backgrounds after considering the color factor. Edge lines are then generated from a binary image using a percolation process. Finally, crack detection and localization is performed with a unique edge-line evaluation. In order to demonstrate the capability of the proposed technique, lab-scale experiments were carried out with a thin aluminum plate. In addition, a test was performed with the panel images acquired at an actual press line. Experimental results show that the proposed technique could effectively detect panel cracks at an improved rate and speed. The experimental results also demonstrate that the proposed technique could be an extension of structural health monitoring frameworks into a new manufacturing application.

scholarly journals CCD instrumentation at Capilla Peak Observatory

1986 ◽  
Vol 118 ◽  
pp. 99-100
Author(s):  
B. E. Laubscher
Keyword(s):  
Image Processing ◽  
New Mexico ◽  
Ccd Camera ◽  
Camera System ◽  
Processing Capability ◽  
University Of New Mexico ◽  
Peak Observatory ◽  
The University

The astronomers at the University of New Mexico are applying the finishing touches to their CCD project. We addressed many issues during the course of this project, such as whether to build or buy the CCD camera system, what upgrades our telescope and observatory were in need of, and what kind of image processing capability the instrument demanded. Our decisions and solutions are presented as a guide to other institutions which may be considering CCD instrumentation for their small telescopes, especially since most face the same constraints that we do: limited money and manpower.

scholarly journals Development and Application of a Human–Machine Interface Using Head Control and Flexible Numeric Tables for the Severely Disabled

2020 ◽  
Vol 10 (19) ◽  
pp. 7005
Author(s):  
Che-Ming Chang ◽  
Chern-Sheng Lin ◽  
Wei-Cheng Chen ◽  
Chung-Ting Chen ◽  
Yu-Liang Hsu
Keyword(s):  
Image Processing ◽  
Skin Color ◽  
Digital Camera ◽  
Human Machine Interface ◽  
Head Motion ◽  
Processing Technologies ◽  
Color Recognition ◽  
Machine Interface ◽  
Head Control ◽  
Head Gestures

The human–machine interface with head control can be applied in many domains. This technology has the valuable application of helping people who cannot use their hands, enabling them to use a computer or speak. This study combines several image processing and computer vision technologies, a digital camera, and software to develop the following system: image processing technologies are adopted to capture the features of head motion; the recognized head gestures include forward, upward, downward, leftward, rightward, right-upper, right-lower, left-upper, and left-lower; corresponding sound modules are used so that patients can communicate with others through a phonetic system and numeric tables. Innovative skin color recognition technology can obtain head features in images. The barycenter of pixels in the feature area is then quickly calculated, and the offset of the barycenter is observed to judge the direction of head motion. This architecture can substantially reduce the distraction of non-targeted objects and enhance the accuracy of systematic judgment.

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