Comparison of Patterns Shapes and Patterns Texture for Identification of Malaria Parasites in Microscopic Image
Identification of malaria parasites in red blood cells has been done, with the aim of as tools to identify experts microscopic parasites more quickly. This study aimed to compare the level of accuracy in the results to identify and classify parasites based on the pattern shape and texture patterns....
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Jurusan Ilmu Komputer Universitas Negeri Semarang
2016-11-01
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Online Access: | http://journal.unnes.ac.id/sju/index.php/sji/article/view/7917 |
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doaj-f1a5ffdffcda4941b5d8c68203d346db2020-11-24T22:23:45ZengJurusan Ilmu Komputer Universitas Negeri SemarangScientific Journal of Informatics2407-76582460-00402016-11-0132109118Comparison of Patterns Shapes and Patterns Texture for Identification of Malaria Parasites in Microscopic ImageJani Kusanti0Universitas SurakartaIdentification of malaria parasites in red blood cells has been done, with the aim of as tools to identify experts microscopic parasites more quickly. This study aimed to compare the level of accuracy in the results to identify and classify parasites based on the pattern shape and texture patterns. The comparison is based on the characteristics of the pattern used, the steps being taken in this study is the image quality improvement process, the process of segmentation with Otsu method, feature extraction process on the image data to be tested. The process of pattern recognition and pattern shapes texture. The last step is to test the identification and classification of plasmodium falciparum parasite into 12 classes using methods Learning Vector Quantization (LVQ). The results of this study indicate that the pattern forms can provide a higher level of accuracy compared to LVQ texture pattern. LVQ with input shape pattern successfully identified 91% of image data correctly and input texture successfully identified 48% of image data properly.http://journal.unnes.ac.id/sju/index.php/sji/article/view/7917Malaria parasites, Classification, LVQ Method, Pattern recognition, Pattern shape texture |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jani Kusanti |
spellingShingle |
Jani Kusanti Comparison of Patterns Shapes and Patterns Texture for Identification of Malaria Parasites in Microscopic Image Scientific Journal of Informatics Malaria parasites, Classification, LVQ Method, Pattern recognition, Pattern shape texture |
author_facet |
Jani Kusanti |
author_sort |
Jani Kusanti |
title |
Comparison of Patterns Shapes and Patterns Texture for Identification of Malaria Parasites in Microscopic Image |
title_short |
Comparison of Patterns Shapes and Patterns Texture for Identification of Malaria Parasites in Microscopic Image |
title_full |
Comparison of Patterns Shapes and Patterns Texture for Identification of Malaria Parasites in Microscopic Image |
title_fullStr |
Comparison of Patterns Shapes and Patterns Texture for Identification of Malaria Parasites in Microscopic Image |
title_full_unstemmed |
Comparison of Patterns Shapes and Patterns Texture for Identification of Malaria Parasites in Microscopic Image |
title_sort |
comparison of patterns shapes and patterns texture for identification of malaria parasites in microscopic image |
publisher |
Jurusan Ilmu Komputer Universitas Negeri Semarang |
series |
Scientific Journal of Informatics |
issn |
2407-7658 2460-0040 |
publishDate |
2016-11-01 |
description |
Identification of malaria parasites in red blood cells has been done, with the aim of as tools to identify experts microscopic parasites more quickly. This study aimed to compare the level of accuracy in the results to identify and classify parasites based on the pattern shape and texture patterns. The comparison is based on the characteristics of the pattern used, the steps being taken in this study is the image quality improvement process, the process of segmentation with Otsu method, feature extraction process on the image data to be tested. The process of pattern recognition and pattern shapes texture. The last step is to test the identification and classification of plasmodium falciparum parasite into 12 classes using methods Learning Vector Quantization (LVQ). The results of this study indicate that the pattern forms can provide a higher level of accuracy compared to LVQ texture pattern. LVQ with input shape pattern successfully identified 91% of image data correctly and input texture successfully identified 48% of image data properly. |
topic |
Malaria parasites, Classification, LVQ Method, Pattern recognition, Pattern shape texture |
url |
http://journal.unnes.ac.id/sju/index.php/sji/article/view/7917 |
work_keys_str_mv |
AT janikusanti comparisonofpatternsshapesandpatternstextureforidentificationofmalariaparasitesinmicroscopicimage |
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1725764074514415616 |