Evaluation of optical properties of fluorescent nanofiber using image-processing technique

Purpose The purpose of this study is evaluate the optical properties of polyacrylonitrile (PAN) nanofibers containing fluorescent agents such as fluorescent dye and carbon quantum dots (CQDs) by using image-processing technique of Fluorescence microscope image. Design/methodology/approach The fluorescence microscope image of the pure PAN, PAN/CQDs and PAN/fluorescent dye nanofibers composite was analyzed using several image-processing techniques such as color histogram, lookup table (LUT), Fourier transform, RGB profile and surface plot analysis. Findings The fluorescence microscope image indicates that the fluorescence emission of nanocomposites depends on the type of fluorescent agent. The fluorescence intensity of nanofiber containing CQDs is more than nanofiber containing fluorescent dye. Various image-processing methods provide similar results for optical property of nanocomposites. Analyzing the LUT, the blue value of CQDs/PAN nanocomposite image was significantly higher than other nanocomposites. This was confirmed by other methods such as Fourier transform, color histogram and 3D topography of the electrospun nanofibers. According to analysis of colorimetric parameters, higher negative value of b* indicates bluer color for CQDs/PAN nanofibers than other nanocomposites. The obtained results indicate that the image-processing technique can be used to evaluate the optical property of fluorescent nanocomposite. Originality/value This study evaluates the optical properties of fluorescent nanocomposites by using image-processing techniques such as Fourier transform, color histogram, RGB profiles, LUT, surface plot and histogram analysis.

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A Novel Method Based on Digital Image Processing Technique and Finite Element Method for Rapidly Modeling Optical Properties of Actual Microstructured Optical Fibers

IEEE Photonics Journal ◽

10.1109/jphot.2016.2614780 ◽

2016 ◽

Vol 8 (6) ◽

pp. 1-14 ◽

Cited By ~ 3

Author(s):

Jianshe Li ◽

Shuguang Li ◽

Guanghua Gu ◽

Hui Li ◽

Qiang Liu ◽

...

Keyword(s):

Finite Element Method ◽

Image Processing ◽

Finite Element ◽

Optical Properties ◽

Optical Fibers ◽

Processing Technique ◽

Image Processing Technique ◽

Microstructured Optical Fibers ◽

Digital Image Processing Technique ◽

Novel Method

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Construction of garment pattern shape information system using image analysis and shape recognition techniques

International Journal of Clothing Science and Technology ◽

10.1108/ijcst-10-2015-0114 ◽

2016 ◽

Vol 28 (4) ◽

pp. 543-555

Author(s):

Jaewoong Lee ◽

InHwan Sul

Keyword(s):

Image Processing ◽

Shape Matching ◽

Shape Recognition ◽

Data Retrieval ◽

Processing Technique ◽

Image Processing Technique ◽

Shape Information ◽

Content Type ◽

Pattern Shape ◽

Shock Graph

Purpose – As an extended work of the previous paper (Sul, 2010), this paper provides a guideline information for an anonymous garment pattern in sewing process. The purpose of this paper is to first, provide garment pattern database. By simply taking pictures of garment patterns, the shape database is constructed. Once the shape database is prepared, data retrieval can be done by image indexing, i.e., simply inserting garment pattern boundary shape again to the database. Using shock graph methodology, the pattern sets used for database preparation can be exactly retrieved. Second, to find the nearest shape of a given input pattern shape in the database. If the input garment pattern shape does not exist in the database, the shape matching algorithm provides the next similar pattern data. The user, who is assumed to be non-expert in garment sewing process, can easily predict the position and combination information of various patterns. Design/methodology/approach – Image processing is used to construct the garment pattern shape database. The boundary shapes are extracted from the photographs of garment patterns and their shape recognition information, especially shock graph, is also recorded for later pattern data retrieval. Findings – Using the image processing technique, garment patterns can be converted to electronic format easily. Also the prepared pattern database can be used for finding the nearest shape of an additional given input garment pattern. Patterns with irregular shapes were retrieved easily, while those with a simple shape, such as rectangle, showed a little erroneous result. Originality/value – Shape recognition has been adopted in various industrial areas, except for garment sewing process. Using the provided methodology, garment pattern shapes can be easily saved and retrieved only by taking pictures of them.

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A New Image Processing Technique for STEM

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100052171 ◽

1974 ◽

Vol 32 ◽

pp. 432-433

Author(s):

Yasushi Kokubo ◽

Hirotami Koike ◽

Teruo Someya

Keyword(s):

Electron Microscopy ◽

Image Processing ◽

Scanning Electron Microscopy ◽

Elastic Scattering ◽

Field Emission ◽

Processing Technique ◽

Image Processing Technique ◽

Energy Analyzer ◽

Scanning Microscope ◽

Scanning Electron

One of the advantages of scanning electron microscopy is the capability for processing the image contrast, i.e., the image processing technique. Crewe et al were the first to apply this technique to a field emission scanning microscope and show images of individual atoms. They obtained a contrast which depended exclusively on the atomic numbers of specimen elements (Zcontrast), by displaying the images treated with the intensity ratio of elastically scattered to inelastically scattered electrons. The elastic scattering electrons were extracted by a solid detector and inelastic scattering electrons by an energy analyzer. We noted, however, that there is a possibility of the same contrast being obtained only by using an annular-type solid detector consisting of multiple concentric detector elements.

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A Comparative Study of Ant and Genetic Algorithms in Digital Mammography

International Journal of Scientific Research in Computer Science Engineering and Information Technology ◽

10.32628/cseit183863 ◽

2018 ◽

pp. 194-200

Author(s):

J. Magelin Mary ◽

Chitra K. ◽

Y. Arockia Suganthi

Keyword(s):

Genetic Algorithm ◽

Image Processing ◽

Medical Image ◽

Medical Image Processing ◽

Processing Technique ◽

Input Image ◽

Image Processing Technique ◽

Computational Time ◽

Image Mining ◽

The Individual

Image processing technique in general, involves the application of signal processing on the input image for isolating the individual color plane of an image. It plays an important role in the image analysis and computer version. This paper compares the efficiency of two approaches in the area of finding breast cancer in medical image processing. The fundamental target is to apply an image mining in the area of medical image handling utilizing grouping guideline created by genetic algorithm. The parameter using extracted border, the border pixels are considered as population strings to genetic algorithm and Ant Colony Optimization, to find out the optimum value from the border pixels. We likewise look at cost of ACO and GA also, endeavors to discover which one gives the better solution to identify an affected area in medical image based on computational time.

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An Enhanced Technique for Classification of Fruits using Shape Color and Texture Features

International Journal of Advanced Research in Computer Science and Software Engineering ◽

10.23956/ijarcsse/v7i7/0107 ◽

2017 ◽

Vol 7 (7) ◽

pp. 408

Author(s):

Yashpal Jitarwal ◽

Tabrej Ahamad Khan ◽

Pawan Mangal

Keyword(s):

Image Processing ◽

Texture Features ◽

Automatic Classification ◽

Processing Technique ◽

Image Processing Technique ◽

Advance Technique ◽

Time Required ◽

Fruit Sorting ◽

Human Inspection

In earlier times fruits were sorted manually and it was very time consuming and laborious task. Human sorted the fruits of the basis of shape, size and color. Time taken by human to sort the fruits is very large therefore to reduce the time and to increase the accuracy, an automatic classification of fruits comes into existence.To improve this human inspection and reduce time required for fruit sorting an advance technique is developed that accepts information about fruits from their images, and is called as Image Processing Technique.

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