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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Main Author: Jani Kusanti
Format: Article
Language:English
Published: Jurusan Ilmu Komputer Universitas Negeri Semarang 2016-11-01
Series:Scientific Journal of Informatics
Subjects:
Online Access:http://journal.unnes.ac.id/sju/index.php/sji/article/view/7917
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spelling 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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