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Development of images segmentation using image thresholder and batch processing technique on the blood smears

Image segmentation is an important part of image processing, and one of the most common approaches is threshold segmentation. A new segmentation technique with each pixel in the image has its own threshold is developed in response to the fact that standard threshold-based segmentation algorithms onl...

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Main Authors: Al-Shoukry, Suhad, Zalili, Musa, Amer, Duha, Kareem, Safaa Muhsen
Format: Article
Language:English
Published: Semnan University 2022
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://umpir.ump.edu.my/id/eprint/39267/1/Development%20of%20images%20segmentation%20using%20image%20thresholder.pdf
http://umpir.ump.edu.my/id/eprint/39267/
http://dx.doi.org/10.22075/ijnaa.2022.28179.3825
http://dx.doi.org/10.22075/ijnaa.2022.28179.3825
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spelling my.ump.umpir.392672023-11-10T01:11:33Z http://umpir.ump.edu.my/id/eprint/39267/ Development of images segmentation using image thresholder and batch processing technique on the blood smears Al-Shoukry, Suhad Zalili, Musa Amer, Duha Kareem, Safaa Muhsen QA75 Electronic computers. Computer science Image segmentation is an important part of image processing, and one of the most common approaches is threshold segmentation. A new segmentation technique with each pixel in the image has its own threshold is developed in response to the fact that standard threshold-based segmentation algorithms only establish one or many thresholds, making it difficult to extract the complex information in an image. This work employs image segmentation tools to examine images of thin blood smears data set. The goal is to explore options for a noniterative-based and automated system for detecting parasites in blood smears. This can be achieved by detecting the presence of a parasite in thin blood smears and quantifying the portion of red blood cells in the sample that are infected. First, we try segmenting the individual red blood cells from the background using the color thresholder. Next, we clean up the obtained cell mask and examine cell properties using the image region analyzer function, which allows quickly filling in region holes and filtering out regions based on their properties such as area dimensions or eccentricity. Then quickly gauge and specify the expected diameter range of the cells in pixels and indicate that the circles are dark relative to the background. Finally, we've combined the code for finding circles matching image histograms and the parasite threshold detection logic into a single function to quickly examine the performance of this function on the other images using the image batch processing technique. The proposed detection function labels the detected cells with blue circles the parasites are marked in red and the infected cells are highlighted in green. The proposed algorithm has appropriately compensated for the variability in image quality. Semnan University 2022-07 Article PeerReviewed pdf en cc_by_4 http://umpir.ump.edu.my/id/eprint/39267/1/Development%20of%20images%20segmentation%20using%20image%20thresholder.pdf Al-Shoukry, Suhad and Zalili, Musa and Amer, Duha and Kareem, Safaa Muhsen (2022) Development of images segmentation using image thresholder and batch processing technique on the blood smears. International Journal of Nonlinear Analysis and Applications (IJNAA), 13 (2). pp. 3251-3259. ISSN 2008-6822. (Published) http://dx.doi.org/10.22075/ijnaa.2022.28179.3825 http://dx.doi.org/10.22075/ijnaa.2022.28179.3825
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Al-Shoukry, Suhad
Zalili, Musa
Amer, Duha
Kareem, Safaa Muhsen
Development of images segmentation using image thresholder and batch processing technique on the blood smears
description Image segmentation is an important part of image processing, and one of the most common approaches is threshold segmentation. A new segmentation technique with each pixel in the image has its own threshold is developed in response to the fact that standard threshold-based segmentation algorithms only establish one or many thresholds, making it difficult to extract the complex information in an image. This work employs image segmentation tools to examine images of thin blood smears data set. The goal is to explore options for a noniterative-based and automated system for detecting parasites in blood smears. This can be achieved by detecting the presence of a parasite in thin blood smears and quantifying the portion of red blood cells in the sample that are infected. First, we try segmenting the individual red blood cells from the background using the color thresholder. Next, we clean up the obtained cell mask and examine cell properties using the image region analyzer function, which allows quickly filling in region holes and filtering out regions based on their properties such as area dimensions or eccentricity. Then quickly gauge and specify the expected diameter range of the cells in pixels and indicate that the circles are dark relative to the background. Finally, we've combined the code for finding circles matching image histograms and the parasite threshold detection logic into a single function to quickly examine the performance of this function on the other images using the image batch processing technique. The proposed detection function labels the detected cells with blue circles the parasites are marked in red and the infected cells are highlighted in green. The proposed algorithm has appropriately compensated for the variability in image quality.
format Article
author Al-Shoukry, Suhad
Zalili, Musa
Amer, Duha
Kareem, Safaa Muhsen
author_facet Al-Shoukry, Suhad
Zalili, Musa
Amer, Duha
Kareem, Safaa Muhsen
author_sort Al-Shoukry, Suhad
title Development of images segmentation using image thresholder and batch processing technique on the blood smears
title_short Development of images segmentation using image thresholder and batch processing technique on the blood smears
title_full Development of images segmentation using image thresholder and batch processing technique on the blood smears
title_fullStr Development of images segmentation using image thresholder and batch processing technique on the blood smears
title_full_unstemmed Development of images segmentation using image thresholder and batch processing technique on the blood smears
title_sort development of images segmentation using image thresholder and batch processing technique on the blood smears
publisher Semnan University
publishDate 2022
url http://umpir.ump.edu.my/id/eprint/39267/1/Development%20of%20images%20segmentation%20using%20image%20thresholder.pdf
http://umpir.ump.edu.my/id/eprint/39267/
http://dx.doi.org/10.22075/ijnaa.2022.28179.3825
http://dx.doi.org/10.22075/ijnaa.2022.28179.3825
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score 13.244413

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