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Yusuf Zain Santosa, Yusuf Zain
Universitas Gadjah Mada
Computer Science & IT

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Comparison of Patterns Shapes and Patterns Texture for Identification of Malaria Parasites in Microscopic Image Kusanti, Jani; Santosa, Yusuf Zain
Scientific Journal of Informatics Vol 3, No 2 (2016): November 2016
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v3i2.7917

Abstract

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.
COMPARISON OF PATTERNS SHAPES AND PATTERNS TEXTURE FOR IDENTIFICATION OF MALARIA PARASITES IN MICROSCOPIC IMAGE Kusanti, Jani; Santosa, Yusuf Zain
Scientific Journal of Informatics Vol 3, No 2 (2016): November 2016
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v3i2.7917

Abstract

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.
Comparison of Patterns Shapes and Patterns Texture for Identification of Malaria Parasites in Microscopic Image Kusanti, Jani; Santosa, Yusuf Zain
Scientific Journal of Informatics Vol 3, No 2 (2016): November 2016
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v3i2.7917

Abstract

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.
Co-Authors Desyandri Desyandri Purwoko, Agus Salsabila, Unik Hanifah