THE CHALLENGES OF USING A GIGAPAN IN FIELD BASED MICRO- AND MACRO-SIZED DATA COLLECTION AND IMAGE PROCESSING

2019 ◽  
Author(s):  
Preston Liles ◽  
◽  
Logan Pearson ◽  
Samantha Barnett ◽  
Dakota G. Simpson ◽  
...  
Keyword(s):  
Image Processing ◽  
Data Collection

Automated electron tomography: from data collection to image processing

1995 ◽  
Vol 53 ◽  
pp. 26-27
Author(s):  
Weiping Liu ◽  
Jennifer Fung ◽  
W.J. de Ruijter ◽  
Hans Chen ◽  
John W. Sedat ◽  
...  
Keyword(s):  
Image Processing ◽  
Data Collection ◽  
Structural Information ◽  
Imaging Technique ◽  
Electron Tomography ◽  
Ccd Camera ◽  
Automated Data Collection ◽  
Full Control ◽  
Transmission Electron ◽  
Amorphous Structures

Electron tomography is a technique where many projections of an object are collected from the transmission electron microscope (TEM), and are then used to reconstruct the object in its entirety, allowing internal structure to be viewed. As vital as is the 3-D structural information and with no other 3-D imaging technique to compete in its resolution range, electron tomography of amorphous structures has been exercised only sporadically over the last ten years. Its general lack of popularity can be attributed to the tediousness of the entire process starting from the data collection, image processing for reconstruction, and extending to the 3-D image analysis. We have been investing effort to automate all aspects of electron tomography. Our systems of data collection and tomographic image processing will be briefly described.To date, we have developed a second generation automated data collection system based on an SGI workstation (Fig. 1) (The previous version used a micro VAX). The computer takes full control of the microscope operations with its graphical menu driven environment. This is made possible by the direct digital recording of images using the CCD camera.

Implementation of Backpropagation for Ulap-ulap Pattern Recognition

2021 ◽  
Vol 9 (3) ◽  
pp. 405
Author(s):  
Ni Luh Yulia Alami Dewi ◽  
I Wayan Santiyasa
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Data Collection ◽  
Test Data ◽  
Training Data ◽  
Image Pattern

Ulap-ulap is one of the symbols used to indicate that a building has been carried out Mlaspas ceremony. Mlaspas is one of the ceremonies performed to purify and clean a building. Ulap-ulap itself consists of various types depending on the building where it is placed, for example the ulap-ulap placed on the Pelinggih building will be different from the ulap-ulap placed on the Bale building. So that the pattern contained in each type of Ulap-ulap is different. The purpose of this research is to be able to do pattern recognition on Ulap-ulap images. The method used in this study is Backpropagation, and for its implementation, the MATLAB 7.5.0 (R2007b) application is used. This study used 18 images of Ulap-ulap, including 15 training data and 6 test data. The stages of the process carried out are for Ulap-ulap pattern recognition, the first is data collection, then image processing, and finally the pattern recognition. Recognition of the Ulap-ulap image pattern with Backpropagation, resulted in an accuracy of 83.333%.

Data Collection and Image Processing Tool for Face Recognition

2019 ◽  
pp. 386-392
Author(s):  
Francimar Rodrigues Maciel ◽  
Sergio Cleger Tamayo ◽  
Aasim Khurshid ◽  
Pauliana Caetano Caetano Martins
Keyword(s):  
Image Processing ◽  
Face Recognition ◽  
Data Collection

Phase-shifting methodologies in photoelastic analysis—the application of Jones calculus

1996 ◽  
Vol 31 (6) ◽  
pp. 423-432 ◽  
Author(s):  
K Ramesh ◽  
V Ganapathy
Keyword(s):  
Image Processing ◽  
Stress Concentration ◽  
Data Collection ◽  
Comparative Study ◽  
Digital Image Processing ◽  
Digital Image ◽  
Phase Shifting ◽  
Intensity Data ◽  
New Approach ◽  
Photoelastic Analysis

The potential of digital image processing hardware to record intensity data at video rates has resulted in a new approach for data collection. Efforts were aimed at evaluating isochromatic and isoclinic fringe orders quantitatively by processing the intensity data recorded. These methodologies have come to be known as phase-shifting techniques. The various phase-shifting algorithms in photoelasticity are surveyed and a comparative study is done. The use of Jones calculus to understand these methodologies is brought out. An attempt has been made to identify the reason for loss of accuracy in evaluating the field parameters in stress concentration zones.

scholarly journals Ground penetrating radar for buried utilities detection and mapping: a review

2021 ◽  
Vol 2107 (1) ◽  
pp. 012056
Author(s):  
Hasimah Ali ◽  
Nurul Syahirah Mohd Ideris ◽  
A F Ahmad Zaidi ◽  
M S Zanar Azalan ◽  
T S Tengku Amran ◽  
...  
Keyword(s):  
Machine Learning ◽  
Image Processing ◽  
Experimental Design ◽  
Data Collection ◽  
Ground Penetrating Radar ◽  
Machine Learning Techniques ◽  
Learning Techniques ◽  
Underground Utilities ◽  
Ground Penetrating ◽  
Non Destructive

Abstract This paper presents a review on Ground Penetrating Radar (GPR) detection and mapping of buried utilities which have been widely used as non-destructive investigation and efficiently in terms of usage. The reviews cover on experimental design in GPR data collection and survey, pre-processing, extracting hyperbolic feature using image processing and machine learning techniques. Some of the issues and challenges facing by the GPR interpretation particularly in extracting the hyperbolas pattern of underground utilities have also been highlighted.

scholarly journals Focus: The interface between data collection and data processing in cryo-EM

2017 ◽  
Author(s):  
Nikhil Biyani ◽  
Ricardo D. Righetto ◽  
Robert McLeod ◽  
Daniel Caujolle-Bert ◽  
Daniel Castano-Diez ◽  
...  
Keyword(s):  
Image Processing ◽  
Data Collection ◽  
Data Processing ◽  
Electron Tomography ◽  
Single Particles ◽  
Transmission Electron ◽  
Computer Image Processing ◽  
Elemental Image ◽  
User Friendly ◽  
High Throughput Manner

We present a new software package called Focus that interfaces cryo-transmission electron microscopy (cryo-EM) data collection with computer image processing. Focus creates a user-friendly environment to import and manage data recorded by direct electron detectors and perform elemental image processing tasks in a high-throughput manner while new data is being acquired at the microscope. It provides the functionality required to remotely monitor the progress of data collection and data processing, which is essential now that automation in cryo-EM allows a steady flow of images of single particles, two-dimensional crystals, or electron tomography data to be recorded in overnight sessions. The rapid detection of any errors that may occur greatly increases the productivity of recording sessions at the electron microscope.

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