Optimisation of a gold nanoparticle-based aptasensor integrated with image processing for the colorimetric detection of acephate using response surface methodology

We successfully optimized AuNPs, modified DNA aptamer and magnesium sulphate salt to enhance the selectivity and sensitivity for detection of Ac. The accuracy of the detection was also improved by image processing technique.

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Image Digitization of Colorimetric Detection of Acephate Based on Its Complexation with Citrate-Capped Gold Nanoparticles

Journal of Chemistry ◽

10.1155/2020/8872048 ◽

2020 ◽

Vol 2020 ◽

pp. 1-10

Author(s):

Mohd Junaedy Osman ◽

Wan Md Zin Wan Yunus ◽

Keat Khim Ong ◽

Buong Woei Chieng ◽

Noor Azilah Mohd Kassim ◽

...

Keyword(s):

Image Processing ◽

Gold Nanoparticles ◽

Limit Of Detection ◽

Colorimetric Detection ◽

Linear Regression Analysis ◽

Processing Technique ◽

Detection Sensitivity ◽

Image Processing Technique ◽

Detection Accuracy ◽

Colour Image

Acephate (Ac), an organophosphate (OP) insecticide, is very harmful to human and the environment. Conventional techniques of detection are sensitive and selective but relatively time-consuming, expensive, and require trained personnel. This paper describes the use of an image processing technique to digitize the red values (RVs) of the colour image of Ac-capped gold nanoparticles (Ac-Cit-AuNPs) complex captured using a digital microscope to improve the detection accuracy and precision. The formation of the suspension was characterised using laser test, ultraviolet-visible spectrophotometer (UV-Vis), high-resolution transmission electron microscope (HRTEM), and Fourier Transform infrared spectroscope (FTIR). The linear regression analysis revealed that the detection sensitivity improved as the smaller gold nanoparticles were used. For quantitative measurement using image processing, a good linear relationship (R2 = 0.9905 and 0.9924) for Cit-HAuNPs and Cit-MAuNPs, respectively, between the concentration of Ac and average red values was obtained in the range of 0–8 mM. The limit of detection (LOD) for Ac was found to be 0.3 mM and 0.4 mM for Cit-MAuNPs and Cit-HAuNPs, respectively.

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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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