scholarly journals Shape Classification for Micro and Nanostructures by Image Analysis

10.5772/50226 ◽  
2013 ◽  
Author(s):  
F. Robert-Inacio ◽  
G. Delafosse ◽  
L. Patrone
Keyword(s):  
Image Analysis ◽  
Shape Classification

scholarly journals From Individual Graphite Assignment to an Improved Digital Image Analysis of Ductile Iron

2020 ◽  
Vol 14 (4) ◽  
pp. 1090-1104
Author(s):  
J. Friess ◽  
U. Sonntag ◽  
I. Steller ◽  
A. Bührig-Polaczek
Keyword(s):  
Image Analysis ◽  
Digital Image ◽  
Ductile Iron ◽  
Digital Image Analysis ◽  
Visual Analysis ◽  
Digital Data ◽  
Shape Classification ◽  
Data Set ◽  
Classification Approach ◽  
Graphite Particles

Abstract Since graphite classification by visual analysis exhibits large variations, a more integrative concept of graphite shape classification is required to evaluate the correlations of process, microstructure and properties, and to fulfill customers’ requirements. The automatic digital image analysis is partly based on visual analysis, but it is not thoroughly defined for graphite shape classification. For example, nodules and thereby nodularity are only defined by the shape parameter roundness, although several studies suggest more sophisticated approaches. Within the first of three successive round robin tests, visual assignment for a variety of graphite particles was performed to obtain a universal digital data set of classified graphite particles. For this, the classification approach from standard EN ISO 945-1 was used and extended with degenerated graphite. The assigned particles were evaluated concerning different shape parameters showing that roundness and the assigned minimum limit value of 0.6 are not sufficient to distinguish nodules from less ideal graphite particle shapes. Furthermore, the current classification approach does not represent the full spectrum of graphite morphologies and needs to be extended. The development of a universal hierarchical classification method for nodules and other graphite shapes has been initiated, and the results will contribute to an improved image analysis standard for ductile iron, particularly ISO 945-4.

Intelligent System of Brain Tumor Automation Diagnosis Based on Image Analysis and Mining

2013 ◽  
Vol 325-326 ◽  
pp. 1619-1622
Author(s):  
Peng Wu ◽  
Ning Jun Ruan ◽  
Kai Xie
Keyword(s):  
Image Analysis ◽  
Brain Tumor ◽  
Medical Image ◽  
Intelligent System ◽  
Image Features ◽  
Shape Classification ◽  
System Use ◽  
Brain Tumor Diagnosis ◽  
The Brain ◽  
Fuzzy Region

This paper covers brain tumor diagnosis system based on image analysis and mining and its application. The system use the algorithm of fuzzy region competition, extracts shape feature factors to classify tumor shape, maps shape classification extracted automatically and other medical image features to numbers and then feed to bayesian network to sort the brain tumor automatically.

The Use of Skeletonization for the Shape Classification of Carbon-Black Aggregates

1993 ◽  
Vol 66 (4) ◽  
pp. 491-509 ◽  
Author(s):  
Charles R. Herd ◽  
Gerard C. McDonald ◽  
Randolph E. Smith ◽  
William M. Hess
Keyword(s):  
Image Analysis ◽  
Carbon Black ◽  
Automated Image Analysis ◽  
Shape Classification ◽  
Linear Type ◽  
Carbon Blacks ◽  
Aggregate Breakdown ◽  
Aggregate Shape ◽  
Type 3

Abstract A specialized image analysis erosion technique, termed skeletonization, has been used for the first quantitative and direct measurement of branching in carbon-black aggregates. Twenty different carbon-black grades were analyzed using transmission-electron-microscopy/automated-image analysis (TEM/AIA). The skeletonization data were used in a discrimination analysis program for detailed shape classification of carbon-black aggregates into four different shape categories that included spheroidal (Type 1), ellipsoidal (Type 2), linear (Type 3) and branched (Type 4). These data were used to examine differences in the aggregate shape distributions between and within grades. Skeletonization and conventional TEM/AIA analyses were also conducted to examine aggregate breakdown as a result of high-shear mixing in rubber (SBR) and cellulose acetate butyrate (CAB) paint chip compounds. It was found that the number of aggregate branches decreased by as much as 50% in rubber and 70% in CAB compounds, and the distributions became narrower. Aggregate breakdown increases in the direction of the larger particle size carbon blacks which contain more linear (Type 3) aggregates. In rubber, an N650 (131 DBPA) and N330 (102 DBPA) carbon blacks were found to be similar in overall aggregate shape properties. Therefore, the significantly higher vulcanizate modulus for N650 appears to be related to a higher level of carbon-black—polymer interaction, as opposed to high amounts of polymer occluded and immobilized within the aggregate structure.

scholarly journals Significant Geometry Features in Tongue Image Analysis

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Bob Zhang ◽  
Han Zhang
Keyword(s):  
Image Analysis ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Decision Tree ◽  
Shape Classification ◽  
Large Dataset ◽  
Medical Practices ◽  
Human Tongue ◽  
Average Accuracy

The shape of a human tongue and its relation to a patients’ state, either healthy or diseased (and if diseased which disease), is quantitatively analyzed using geometry features by means of computerized methods in this paper. Thirteen geometry features based on measurements, distances, areas, and their ratios are extracted from tongue images captured by a specially designed device with color correction. Using the features, 5 tongue shapes (rectangle, acute and obtuse triangles, square, and circle) are defined based on traditional Chinese medicine (TCM). Classification of the shapes is subsequently carried out with a decision tree. A large dataset consisting of 672 images comprising of 130 healthy and 542 disease examples (labeled according to Western medical practices) are tested. Experimental results show that the extracted geometry features are effective at tongue shape classification (coarse level). Even if more than one disease class belongs to the same shape, the disease classes can still be discriminated via fine level classification using a combination of the geometry features, with an average accuracy of 76.24% for all shapes.

Automated Image Analysis Of Nuclear And Cytoplasmic Changes In Exfoliated Cells From Tracheas Treated With Carcinogen

1977 ◽  
Vol 35 ◽  
pp. 220-221
Author(s):  
S.F. Stinson ◽  
J.C. Lilga ◽  
M.B. Sporn
Keyword(s):  
Image Analysis ◽  
Pattern Analysis ◽  
Relative Proportion ◽  
Automated Image Analysis ◽  
Image Analyzer ◽  
Cross Sectional ◽  
Exfoliated Cells ◽  
Neoplastic Lesions ◽  
Analysis System ◽  
Morphologic Criterion

Increased nuclear size, resulting in an increase in the relative proportion of nuclear to cytoplasmic sizes, is an important morphologic criterion for the evaluation of neoplastic and pre-neoplastic cells. This paper describes investigations into the suitability of automated image analysis for quantitating changes in nuclear and cytoplasmic cross-sectional areas in exfoliated cells from tracheas treated with carcinogen.Neoplastic and pre-neoplastic lesions were induced in the tracheas of Syrian hamsters with the carcinogen N-methyl-N-nitrosourea. Cytology samples were collected intra-tracheally with a specially designed catheter (1) and stained by a modified Papanicolaou technique. Three cytology specimens were selected from animals with normal tracheas, 3 from animals with dysplastic changes, and 3 from animals with epidermoid carcinoma. One hundred randomly selected cells on each slide were analyzed with a Bausch and Lomb Pattern Analysis System automated image analyzer.

Progress In The Practical Application Of Automated Image Analysis To Tem Negatives

1977 ◽  
Vol 35 ◽  
pp. 214-217
Author(s):  
F. A. Heckman ◽  
E. Redman ◽  
J.E. Connolly
Keyword(s):  
Image Analysis ◽  
Image Quality ◽  
Exposure Time ◽  
Image Contrast ◽  
Automated Image Analysis ◽  
Practical Application ◽  
Factors Affecting ◽  
High Image Quality ◽  
Qualitative Evidence ◽  
Comprehensive Study

In our initial publication on this subject1) we reported results demonstrating that contrast is the most important factor in producing the high image quality required for reliable image analysis. We also listed the factors which enhance contrast in order of the experimentally determined magnitude of their effect. The two most powerful factors affecting image contrast attainable with sheet film are beam intensity and KV. At that time we had only qualitative evidence for the ranking of enhancing factors. Later we carried out the densitometric measurements which led to the results outlined below.Meaningful evaluations of the cause-effect relationships among the considerable number of variables in preparing EM negatives depend on doing things in a systematic way, varying only one parameter at a time. Unless otherwise noted, we adhered to the following procedure evolved during our comprehensive study:Philips EM-300; 30μ objective aperature; magnification 7000- 12000X, exposure time 1 second, anti-contamination device operating.

A New System For Optomanual Semiautomatic Quantitative Image Analysis

1977 ◽  
Vol 35 ◽  
pp. 210-211
Author(s):  
H.P. Rohr
Keyword(s):  
Image Analysis ◽  
Volume Density ◽  
List Type ◽  
Distribution Analysis ◽  
Type Number ◽  
Point Counting ◽  
Human Eye ◽  
Quantitative Image ◽  
Point Density ◽  
Electronic Counting

Today, in image analysis the broadest possible rationalization and economization have become desirable. Basically, there are two approaches for image analysis: The image analysis through the so-called scanning methods which are usually performed without the human eye and the systems of optical semiautomatic analysis completely relying on the human eye.The new MOP AM 01 opto-manual system (fig.) represents one of the very promising approaches in this field. The instrument consists of an electronic counting and storing unit, which incorporates a microprocessor and a keyboard for choice of measuring parameters, well designed for easy use.Using the MOP AM 01 there are three possibilities of image analysis:the manual point counting,the opto-manual point counting andthe measurement of absolute areas and/or length (size distribution analysis included).To determine a point density for the calculation of the corresponding volume density the intercepts lying within the structure are scanned with the light pen.

Application of Modified Bloch Waves to Image Analysis of Extended Linear Defects

1974 ◽  
Vol 32 ◽  
pp. 402-403
Author(s):  
S. Nakahara ◽  
D. M. Maher
Keyword(s):  
Image Analysis ◽  
Computational Approach ◽  
Dislocation Loops ◽  
Plane Wave Expansion ◽  
Dynamical Equations ◽  
Bloch Waves ◽  
Linear Defects ◽  
Imperfect Crystal ◽  
Localized Defects ◽  
Defective Crystals

Since Head first demonstrated the advantages of computer displayed theoretical intensities from defective crystals, computer display techniques have become important in image analysis. However the computational methods employed resort largely to numerical integration of the dynamical equations of electron diffraction. As a consequence, the interpretation of the results in terms of the defect displacement field and diffracting variables is difficult to follow in detail. In contrast to this type of computational approach which is based on a plane-wave expansion of the excited waves within the crystal (i.e. Darwin representation ), Wilkens assumed scattering of modified Bloch waves by an imperfect crystal. For localized defects, the wave amplitudes can be described analytically and this formulation has been used successfully to predict the black-white symmetry of images arising from small dislocation loops.

Interfacing of a TEM/STEM System to a Computer

1981 ◽  
Vol 39 ◽  
pp. 250-251
Author(s):  
P. Hagemann
Keyword(s):  
Image Analysis ◽  
Transmission Rate ◽  
Analytical Electron Microscopy ◽  
Signal Beam ◽  
Automated Image Analysis ◽  
Beam Deflection ◽  
External Control ◽  
Computer Input ◽  
Instrument Control ◽  
Data Acquisition And Processing

The use of computers in the analytical electron microscopy today shows three different trends (1) automated image analysis with dedicated computer systems, (2) instrument control by microprocessors and (3) data acquisition and processing e.g. X-ray or EEL Spectroscopy.While image analysis in the T.E.M. usually needs a television chain to get a sequential transmission suitable as computer input, the STEM system already has this necessary facility. For the EM400T-STEM system therefore an interface was developed, that allows external control of the beam deflection in TEM as well as the control of the STEM probe and video signal/beam brightness on the STEM screen.The interface sends and receives analogue signals so that the transmission rate is determined by the convertors in the actual computer periphery.

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