Enhancement of Low-Quality Diatom Images using Integrated Automatic Background Removal (IABR) Method from Digital Microscopic Image
Most diatom images scanned from digital microscopes suffer from low contrast, noise, and contain unwanted floating particles and debris in a single image. Moreover, the active movement of diatom along with poor lens focusing produces a blurred image. Thus, in this paper, we introduce a new integrate...
Published in: | 13th IEEE Symposium on Computer Applications and Industrial Electronics, ISCAIE 2023 |
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2-s2.0-85165176128 Baharin M.A.S.K.; Ghani A.S.A.; Amri S.Q.S.; Mohammad-Noor N.; Ismail H.N. Enhancement of Low-Quality Diatom Images using Integrated Automatic Background Removal (IABR) Method from Digital Microscopic Image 2023 13th IEEE Symposium on Computer Applications and Industrial Electronics, ISCAIE 2023 10.1109/ISCAIE57739.2023.10165175 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85165176128&doi=10.1109%2fISCAIE57739.2023.10165175&partnerID=40&md5=80ca96577bb0d618063aaf31284a27b5 Most diatom images scanned from digital microscopes suffer from low contrast, noise, and contain unwanted floating particles and debris in a single image. Moreover, the active movement of diatom along with poor lens focusing produces a blurred image. Thus, in this paper, we introduce a new integrated automatic background removal technique (IABR) to enhance low-quality microscopic diatom images. This paper describes a two-step process of microscopic diatom image for image smoothing. First, haze removal technique is applied to the low light image to enhance and removes the image from haze and noise. Second, the background removal technique extracts the diatom cell from the background image and improves the image contrast. The output results show that the proposed IABR method has successfully enhanced and smooths low-quality diatom images by removing the image background and improving image contrast. © 2023 IEEE. Institute of Electrical and Electronics Engineers Inc. English Conference paper |
author |
Baharin M.A.S.K.; Ghani A.S.A.; Amri S.Q.S.; Mohammad-Noor N.; Ismail H.N. |
spellingShingle |
Baharin M.A.S.K.; Ghani A.S.A.; Amri S.Q.S.; Mohammad-Noor N.; Ismail H.N. Enhancement of Low-Quality Diatom Images using Integrated Automatic Background Removal (IABR) Method from Digital Microscopic Image |
author_facet |
Baharin M.A.S.K.; Ghani A.S.A.; Amri S.Q.S.; Mohammad-Noor N.; Ismail H.N. |
author_sort |
Baharin M.A.S.K.; Ghani A.S.A.; Amri S.Q.S.; Mohammad-Noor N.; Ismail H.N. |
title |
Enhancement of Low-Quality Diatom Images using Integrated Automatic Background Removal (IABR) Method from Digital Microscopic Image |
title_short |
Enhancement of Low-Quality Diatom Images using Integrated Automatic Background Removal (IABR) Method from Digital Microscopic Image |
title_full |
Enhancement of Low-Quality Diatom Images using Integrated Automatic Background Removal (IABR) Method from Digital Microscopic Image |
title_fullStr |
Enhancement of Low-Quality Diatom Images using Integrated Automatic Background Removal (IABR) Method from Digital Microscopic Image |
title_full_unstemmed |
Enhancement of Low-Quality Diatom Images using Integrated Automatic Background Removal (IABR) Method from Digital Microscopic Image |
title_sort |
Enhancement of Low-Quality Diatom Images using Integrated Automatic Background Removal (IABR) Method from Digital Microscopic Image |
publishDate |
2023 |
container_title |
13th IEEE Symposium on Computer Applications and Industrial Electronics, ISCAIE 2023 |
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doi_str_mv |
10.1109/ISCAIE57739.2023.10165175 |
url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85165176128&doi=10.1109%2fISCAIE57739.2023.10165175&partnerID=40&md5=80ca96577bb0d618063aaf31284a27b5 |
description |
Most diatom images scanned from digital microscopes suffer from low contrast, noise, and contain unwanted floating particles and debris in a single image. Moreover, the active movement of diatom along with poor lens focusing produces a blurred image. Thus, in this paper, we introduce a new integrated automatic background removal technique (IABR) to enhance low-quality microscopic diatom images. This paper describes a two-step process of microscopic diatom image for image smoothing. First, haze removal technique is applied to the low light image to enhance and removes the image from haze and noise. Second, the background removal technique extracts the diatom cell from the background image and improves the image contrast. The output results show that the proposed IABR method has successfully enhanced and smooths low-quality diatom images by removing the image background and improving image contrast. © 2023 IEEE. |
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Institute of Electrical and Electronics Engineers Inc. |
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language |
English |
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Conference paper |
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scopus |
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Scopus |
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1809678021268865024 |