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Color constancy analysis approach for color standardization on malaria thick and thin blood smear images

cris.author.scopus-author-id 57202507356
cris.author.scopus-author-id 57219027157
cris.author.scopus-author-id 55357649900
cris.author.scopus-author-id 57201525827
cris.author.scopus-author-id 24345693200
cris.virtual.department Universiti Malaysia Perlis
cris.virtual.department Universiti Malaysia Perlis
cris.virtual.department Universiti Malaysia Perlis
cris.virtualsource.department da75dbd1-11a6-49dd-ae82-ac7efb3405da
cris.virtualsource.department 4ba2fcc7-660a-4777-ba44-c43d17389e5d
cris.virtualsource.department 9099bfe1-c1c2-4a04-8dab-f52234d1f87a
dc.contributor.author Thaqifah Ahmad Aris
dc.contributor.author Aimi Salihah Abdul Nasir
dc.contributor.author Haryati Jaafar
dc.contributor.author Lim Chee Chin
dc.contributor.author Mohamed Z.
dc.date.accessioned 2024-09-27T07:22:47Z
dc.date.available 2024-09-27T07:22:47Z
dc.date.issued 2021-01-01
dc.description.abstract Malaria is an extensively prevalent blood infection, the most severe and widespread parasitic disease that stirring millions of people in the world. Currently, microscopy diagnosis still the most widely used method for malaria diagnosis. However, this procedure contains the probability of miscalculation of parasites due to human error. Computerized system by using image processing is recognized as a quick and easy ways to analyze a lot of blood samples. However, because of the non-standard preparation of the blood slides which producing color varieties in different slides will result on low quality images. Hence, it is difficult to identify the existence of malaria parasites as well as observing its morphological characteristics to recognize malaria parasites. Therefore, this paper aims to analyze the standardization performance between six types of color constancy algorithms namely, gray world (GW), white patch (WP), modified white patch (MWP), progressive hybrid (PH), shades of gray (SoG) and gray edge (GE) on both thick and thin blood smear malaria images of P. falciparum and P. vivax species. Six types of color constancy algorithms standardization performance are analysed by using quantitative measure namely, peak signal to noise ratio (PSNR), normalized absolute error (NAE), mean square error (MSE) and root mean square error (RMSE). Based on the qualitative and quantitative findings, the results show that SoG algorithm is the best color constancy as compared to others proposed color constancy. SoG algorithm has achieved the highest PSNR and lowest NAE, MSE and RMSE values, thus proved that the quality of malaria images have been improved.
dc.identifier.doi 10.1007/978-981-15-5281-6_57
dc.identifier.isbn [9789811552809]
dc.identifier.scopus 2-s2.0-85088536638
dc.identifier.uri https://hdl.handle.net/20.500.14170/4749
dc.relation.funding Hospital Universiti Sains Malaysia
dc.relation.grantno undefined
dc.relation.ispartof Lecture Notes in Electrical Engineering
dc.relation.ispartofseries Lecture Notes in Electrical Engineering
dc.relation.issn 18761100
dc.subject Color constancy | Color standardization | Malaria thick and thin blood smear | Quantitative measure
dc.title Color constancy analysis approach for color standardization on malaria thick and thin blood smear images
dc.type Book Series
dspace.entity.type Publication
oaire.citation.endPage 804
oaire.citation.startPage 785
oaire.citation.volume 666
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit School of Medical Sciences, Universiti Sains Malaysia
oairecerif.author.affiliation Universiti Malaysia Perlis
oairecerif.author.affiliation Universiti Malaysia Perlis
oairecerif.author.affiliation Universiti Malaysia Perlis
oairecerif.author.affiliation Universiti Malaysia Perlis
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person.identifier.scopus-author-id 57202507356
person.identifier.scopus-author-id 57219027157
person.identifier.scopus-author-id 55357649900
person.identifier.scopus-author-id 57201525827
person.identifier.scopus-author-id 24345693200
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