Automatic phytoplankton image smoothing through integrated dual image histogram specification and enhanced background removal method
Diatom is a dominant phytoplankton and commonly found in oceans or waterways. The captured phytoplankton microscopic images suffer from low contrast and surrounding debris. These images are not appropriated for identification. Integrated dual image contrast adaptive histogram specification with enha...
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Taylor and Francis
2022
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my.iium.irep.1015062022-12-01T08:40:32Z http://irep.iium.edu.my/101506/ Automatic phytoplankton image smoothing through integrated dual image histogram specification and enhanced background removal method Kamarul Baharin, Mohd Aiman Syahmi Abdul Ghani, Ahmad Shahrizan Mohammad Noor, Normawaty Ismail, Hasnun Nita Syamsul Amri, Syafiq Qhushairy Q Science (General) Diatom is a dominant phytoplankton and commonly found in oceans or waterways. The captured phytoplankton microscopic images suffer from low contrast and surrounding debris. These images are not appropriated for identification. Integrated dual image contrast adaptive histogram specification with enhanced background removal (DIHS-BR) is proposed to address these issues by automatically removes the background of the phytoplankton image and improves the image quality while cropping phytoplankton cell. DIHS-BR will automatically remove the background and noises. DIHS-BR consists of two major steps, namely, contrast adaptive histogram specification and background removal by means of edge mask cropping. Results demonstrated that DIHS-BR filtered out the image background and left only the required phytoplankton cell image. Noises are minimized, while the contrast and colour of phytoplankton cells are improved. The average edge-based contrast measure (EBCM) of 83.065 demonstrates the best contrast improvement of the proposed methods compared with the other state-of-the-art methods Taylor and Francis 2022-11-14 Article PeerReviewed application/pdf en http://irep.iium.edu.my/101506/7/101506_Automatic%20phytoplankton%20image%20smoothing.pdf Kamarul Baharin, Mohd Aiman Syahmi and Abdul Ghani, Ahmad Shahrizan and Mohammad Noor, Normawaty and Ismail, Hasnun Nita and Syamsul Amri, Syafiq Qhushairy (2022) Automatic phytoplankton image smoothing through integrated dual image histogram specification and enhanced background removal method. The Imaging Science Journal. pp. 1-27. ISSN 1368-2199 E-ISSN 1743-131X https://www.tandfonline.com/loi/yims20 10.1080/13682199.2022.2149067 |
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Q Science (General) Kamarul Baharin, Mohd Aiman Syahmi Abdul Ghani, Ahmad Shahrizan Mohammad Noor, Normawaty Ismail, Hasnun Nita Syamsul Amri, Syafiq Qhushairy Automatic phytoplankton image smoothing through integrated dual image histogram specification and enhanced background removal method |
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Diatom is a dominant phytoplankton and commonly found in oceans or waterways. The captured phytoplankton microscopic images suffer from low contrast and surrounding debris. These images are not appropriated for identification. Integrated dual image contrast adaptive histogram specification with enhanced background removal (DIHS-BR) is proposed to address these issues by automatically removes the background of the phytoplankton image and improves the image quality while cropping phytoplankton cell. DIHS-BR will automatically remove the background and noises. DIHS-BR consists of two major steps, namely, contrast adaptive histogram specification and background removal by means of edge mask cropping. Results demonstrated that DIHS-BR filtered out the image background and left only the required phytoplankton cell image. Noises are minimized, while the contrast and colour of phytoplankton cells are improved. The average edge-based contrast measure (EBCM) of 83.065 demonstrates the best contrast improvement of the proposed methods compared with the other state-of-the-art methods |
format |
Article |
author |
Kamarul Baharin, Mohd Aiman Syahmi Abdul Ghani, Ahmad Shahrizan Mohammad Noor, Normawaty Ismail, Hasnun Nita Syamsul Amri, Syafiq Qhushairy |
author_facet |
Kamarul Baharin, Mohd Aiman Syahmi Abdul Ghani, Ahmad Shahrizan Mohammad Noor, Normawaty Ismail, Hasnun Nita Syamsul Amri, Syafiq Qhushairy |
author_sort |
Kamarul Baharin, Mohd Aiman Syahmi |
title |
Automatic phytoplankton image smoothing through integrated dual image histogram specification and enhanced background removal method |
title_short |
Automatic phytoplankton image smoothing through integrated dual image histogram specification and enhanced background removal method |
title_full |
Automatic phytoplankton image smoothing through integrated dual image histogram specification and enhanced background removal method |
title_fullStr |
Automatic phytoplankton image smoothing through integrated dual image histogram specification and enhanced background removal method |
title_full_unstemmed |
Automatic phytoplankton image smoothing through integrated dual image histogram specification and enhanced background removal method |
title_sort |
automatic phytoplankton image smoothing through integrated dual image histogram specification and enhanced background removal method |
publisher |
Taylor and Francis |
publishDate |
2022 |
url |
http://irep.iium.edu.my/101506/7/101506_Automatic%20phytoplankton%20image%20smoothing.pdf http://irep.iium.edu.my/101506/ https://www.tandfonline.com/loi/yims20 |
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