Digital Image Analysis Of Single Rectangular Slit Fraunhofer Diffraction Patterns

Study of the single rectangular slit Fraunhofer diffraction pattern has been carried out through experiments. Data acquisition was done by manually measuring the distance of the bright and dark diffraction patterns using millimeter block paper and by means of digital images analysis of the diffraction patterns. The digital images were used to obtain the bright and dark intensity data of the pattern as the function of the distance from the center of the pattern. The process of obtaining the data was carried out as follows: image acquisition, image digitization, image quality enhancement, graphics plotting and chart normalization. The data processing is done analytically and computationally using ImageJ software. The results of the digital image analysis of diffraction patterns produce an intensity graph of the distance of the diffraction pattern (I-y chart). The results from the digital image analysis approach provide an alternative method that is more accurate in the process of calculating the physical magnitude of diffraction parameters such as the wavelength of the source. One of the advantages of this method is that intensity of the diffraction pattern can be visualized as a function of the distance from the center of the screen. Although accuracy of the calculation result is not very high, the magnitude of the intensity can be observed to decrease with increasing distance of the diffraction pattern to the center of the screen. The results of the calculation of the source wavelength by means of digital image analysis provides good results compared to the manual method using the millimeter block paper. The smallest mean error of the wavelength by means of digital image analysis is 1,72% and the manual method using the millimeter block paper is 3,84%. This method of measurement using digital image analysis can be used as an alternative for various position or distance-based measurement, such as the calculation of linear expansion coefficient with a single slit diffraction method.

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Critical Remarks on Some Applications of Digital Image Analysis with Emphasis on Statistical Methodology

Jurnal Teknologi ◽

10.11113/jt.v35.606 ◽

2012 ◽

Author(s):

Omar Mohd. Rijal ◽

Norliza Mohd. Noor ◽

Yun Fah Chang

Keyword(s):

Image Analysis ◽

Key Words ◽

Statistical Methods ◽

Digital Image ◽

Digital Image Analysis ◽

Digital Images ◽

Statistical Methodology ◽

Sources Of Uncertainty

Hasil penyelidikan dari Rijal dan Noor dan mengenai kegunaan kaedah statistik dan punca ketidakpastian yang berhubungkait dengan membuat pentadbiran ketika menggunakan imej digit memberi motivasi kepada kajian ini. Dalam kertas kerja ini tiga contoh lagi dikemukakan dengan tujuan memberi pandangan keseluruhan mengenai applikasi (termasuk secara statistik) analisis imej digit, dan isu–isu am diberi penekanan. Satu kesimpulan dari kajian ini adalah kaedah statistik/matematik harus diberi peranan penting dalam analisis imej digit. Kata kunci: Analisis imej digit; kaedah statistik; perbandingan secara kritikal contoh-contoh terpilih The results of Rijal and Noor and regarding the use of statistical methods and sources of uncertainty associated with making inferences when using digital images provide the motivation for this study. In this paper three other examples are presented with the purpose of providing an overview of applications (possibly statistical) of image analysis, and general issues highlighted. One conclusion from this study is that statistical/mathematical methodology should be emphasized in digital image analysis. Key words: Digital image analysis

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Evaluation of Components of Partial Resistance to Oat Crown Rust Using Digital Image Analysis

Plant Disease ◽

10.1094/pdis.2003.87.6.667 ◽

2003 ◽

Vol 87 (6) ◽

pp. 667-674 ◽

Cited By ~ 40

Author(s):

J. E. Díaz-Lago ◽

D. D. Stuthman ◽

K. J. Leonard

Keyword(s):

Image Analysis ◽

Latent Period ◽

Digital Image ◽

Partial Resistance ◽

Digital Image Analysis ◽

Digital Images ◽

Crown Rust ◽

Infection Frequency ◽

Sources Of Resistance ◽

Resistance Components

Digital image analysis is an objective and nondestructive method potentially capable of providing accurate and precise estimates of disease resistance components. This study was conducted to quantify components of partial resistance to crown rust through the analysis of sequential digital images of inoculated leaves of adult oat plants, and to compare components found in two sources of resistance unrelated genetically. Uredinium density, relative infection frequency, latent period, days to first pustule appearance, uredinium size, and disease progress rates were assessed on three oat lines (RS-line 3W-C2R-9-3b, MN-841801, Starter) in two greenhouse experiments. Resistant lines had fewer and smaller uredinia, and these appeared later than in the susceptible check. Relative infection frequency, latent period, and uredinium size were equally important components in the expression of the partial resistance to crown rust, and the two sources of resistance could not be differentiated by any of the variables studied. The analysis of sequential digital images of diseased leaves produced precise estimates of partial resistance components and disease progress rates.

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Possibilities of automatic assessment of the vitreous nature of wheat and linear characteristics of grain (seeds) by digital image analysis

Agrarian science ◽

10.32634/0869-8155-2020-338-5-87-90 ◽

2020 ◽

pp. 87-90

Author(s):

T. S. Rutkovskaya ◽

R. Yu. Antonov ◽

G. P. Petrov

Keyword(s):

Image Analysis ◽

Data Processing ◽

Digital Image ◽

Digital Image Analysis ◽

Digital Images ◽

Comparative Characteristic ◽

Automatic Assessment ◽

Wheat Grains ◽

Linear Dimensions ◽

The Stability

Relevance and methods. The article considers the possibility of using the analysis of digital images for a comprehensive assessment of the physical characteristics of grain: vitreous and linear dimensions.Results. A comparative characteristic of instrumental and organoleptic methods for determining these indicators by the following criteria is given: stability of results, speed of measurements and data processing. An algorithm has been developed that combines the ability to programmatically determine glassiness and linear dimensions of wheat grains based on their digital images. A relationship was found between an increase in the vitreous nature of the sample and an increase in the stability of the results.

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The Possibility of Digital Imaging in the Diagnosis of Occlusal Caries

International Journal of Dentistry ◽

10.1155/2010/860515 ◽

2010 ◽

Vol 2010 ◽

pp. 1-4 ◽

Cited By ~ 9

Author(s):

Sachi Umemori ◽

Ken-ichi Tonami ◽

Hiroshi Nitta ◽

Shiro Mataki ◽

Kouji Araki

Keyword(s):

Image Analysis ◽

Fractal Dimension ◽

Sensitivity And Specificity ◽

Digital Image ◽

Diagnostic Tool ◽

Digital Imaging ◽

Digital Image Analysis ◽

Digital Images ◽

Occlusal Surface ◽

Occlusal Caries

The aim of this study was to assess the possibility of digital image analysis of pit-and-fissure discoloration in order to diagnose caries. Digital images showing pit-and-fissure discoloration in 100 teeth of 19 patients were analyzed to obtain the fractal dimension (FD) and the proportion of the area of pit-and-fissure discoloration to the area of occlusal surface (PA). DIAGNOdent values were measured (DD), and dentists' diagnoses were also obtained. The sensitivity and specificity of FD, PA, DD, and the combination of FD and PA compared to the dentists' diagnoses were calculated. The sensitivities of FD, PA, DD, and the combination of FD and PA were 0.89, 0.47, 0.69, and 0.86, respectively, and the specificities were 0.84, 0.95, 0.91, and 0.86, respectively. Although further research is needed for the practical use, it is possible to use the analysis of digital images of pit-and-fissure molar discoloration as a diagnostic tool.

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A comparison of Ki67 index in carcinoma breast by digital image analysis with manual method

Indian Journal of Pathology and Oncology ◽

10.18231/j.ijpo.2019.107 ◽

2019 ◽

Vol 6 (4) ◽

pp. 548-551

Author(s):

Sandhya I ◽

◽

Parineetha V Shetty ◽

Keerthana Prasad ◽

Purnima S Rao ◽

...

Keyword(s):

Image Analysis ◽

Digital Image ◽

Digital Image Analysis ◽

Ki67 Index ◽

Carcinoma Breast ◽

Manual Method

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Algorithm for detecting rounding measures for digital image analysis

System technologies ◽

10.34185/1562-9945-3-122-2019-04 ◽

2019 ◽

Vol 3 (122) ◽

pp. 25-31

Author(s):

Tetiana Vitaliivna Selivorstova ◽

Vadym Yuriiovych Selivorstov

Keyword(s):

Image Analysis ◽

Digital Image ◽

Digital Image Analysis ◽

Digital Images ◽

Application Software ◽

Metallic Inclusion ◽

New Approach ◽

Quantitative Estimates ◽

Metallic Inclusions ◽

Inclusions In Steel

The urgency of the paper is to develop a new approach for quantifying the shape of non-metallic inclusions in steel, in particular sulfides. The aim of the article is to develop an algorithm for detecting a rounding measure for analyzing digital images of the macrostructure of metal templates, namely sulfuric prints. Method. According to the proposed algorithm, the object in the image - a non-metallic inclusion is considered to be close to a circular shape, if the ratio of the circumference of a circle equal in area to a non-metallic inclusion to the length of its contour approaches unity. Results. Testing of the developed algorithm for detecting rounding measures for digital image analysis was carried out using the developed application software. To study the image it must first be converted to binary. Next, the image is processed, as a result of which the user receives information about the number of inclusions and their degree of rounding. The application of the developed algorithm to the array of test images showed the adequacy of the proposed algorithm. The developed algorithm is included in the form of a processor in the ASImprints software for analyzing sulfuric prints. Conclusions. The developed algorithm for detecting the rounding measure for analyzing digital images is based on an intuitive approach. Its application to digital images of the macrostructure of metal templates will allow researchers to obtain microstructural and macrostructural phenomena in the melt to obtain their quantitative estimates.

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