Identifikasi Karakteristik Citra Berdasarkan pada Nilai Entropi dan Kontras

Abstract Determining the object boundaries in an image is a necessary process, to identify the boundaries of an object with other objects as well as to define an object in the image. The acquired image is not always in good condition, on the other hand there is a lot of noise and blur. Various ed...

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Main Authors: Bheta Agus Wardijono, Lussiana ETP, Rozi
Format: Article
Language:Indonesian
Published: Indonesian Society of Applied Science (ISAS) 2021-06-01
Series:Journal of Applied Computer Science and Technology
Subjects:
Online Access:https://journal.isas.or.id/index.php/JACOST/article/view/136
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spelling doaj-0df04203932f43dd801463095987b6ef2021-07-22T05:58:18ZindIndonesian Society of Applied Science (ISAS)Journal of Applied Computer Science and Technology2723-14532021-06-0121182310.52158/jacost.v2i1.136136Identifikasi Karakteristik Citra Berdasarkan pada Nilai Entropi dan KontrasBheta Agus Wardijono0Lussiana ETP1Rozi2STMIK Jakarta STI&KSTMIK Jakarta STI&KSTMIK Jakarta STI&KAbstract Determining the object boundaries in an image is a necessary process, to identify the boundaries of an object with other objects as well as to define an object in the image. The acquired image is not always in good condition, on the other hand there is a lot of noise and blur. Various edge detection methods have been developed by providing noise parameters to reduce noise, and adding a blur parameter but because these parameters apply to the entire image, but lossing some edges due to these parameters. This study aims to identify the characteristics of the image region, whether the region condition is noise, blurry or otherwise sharp (clear). The step is done by dividing the four regions from the image size, then calculating the entropy value and contrast value of each formed region. The test results show that changes in region size can produce different characteristics, this is indicated by entropy and contrast values ​​of each formed region. Thus it can be concluded that entropy and contrast can be used as a way to identify image characteristics, and dividing the image into regions provides more detailed image characteristics.https://journal.isas.or.id/index.php/JACOST/article/view/136image edge detection, image characteristics, regionization, entropy, contrast.
collection DOAJ
language Indonesian
format Article
sources DOAJ
author Bheta Agus Wardijono
Lussiana ETP
Rozi
spellingShingle Bheta Agus Wardijono
Lussiana ETP
Rozi
Identifikasi Karakteristik Citra Berdasarkan pada Nilai Entropi dan Kontras
Journal of Applied Computer Science and Technology
image edge detection, image characteristics, regionization, entropy, contrast.
author_facet Bheta Agus Wardijono
Lussiana ETP
Rozi
author_sort Bheta Agus Wardijono
title Identifikasi Karakteristik Citra Berdasarkan pada Nilai Entropi dan Kontras
title_short Identifikasi Karakteristik Citra Berdasarkan pada Nilai Entropi dan Kontras
title_full Identifikasi Karakteristik Citra Berdasarkan pada Nilai Entropi dan Kontras
title_fullStr Identifikasi Karakteristik Citra Berdasarkan pada Nilai Entropi dan Kontras
title_full_unstemmed Identifikasi Karakteristik Citra Berdasarkan pada Nilai Entropi dan Kontras
title_sort identifikasi karakteristik citra berdasarkan pada nilai entropi dan kontras
publisher Indonesian Society of Applied Science (ISAS)
series Journal of Applied Computer Science and Technology
issn 2723-1453
publishDate 2021-06-01
description Abstract Determining the object boundaries in an image is a necessary process, to identify the boundaries of an object with other objects as well as to define an object in the image. The acquired image is not always in good condition, on the other hand there is a lot of noise and blur. Various edge detection methods have been developed by providing noise parameters to reduce noise, and adding a blur parameter but because these parameters apply to the entire image, but lossing some edges due to these parameters. This study aims to identify the characteristics of the image region, whether the region condition is noise, blurry or otherwise sharp (clear). The step is done by dividing the four regions from the image size, then calculating the entropy value and contrast value of each formed region. The test results show that changes in region size can produce different characteristics, this is indicated by entropy and contrast values ​​of each formed region. Thus it can be concluded that entropy and contrast can be used as a way to identify image characteristics, and dividing the image into regions provides more detailed image characteristics.
topic image edge detection, image characteristics, regionization, entropy, contrast.
url https://journal.isas.or.id/index.php/JACOST/article/view/136
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AT lussianaetp identifikasikarakteristikcitraberdasarkanpadanilaientropidankontras
AT rozi identifikasikarakteristikcitraberdasarkanpadanilaientropidankontras
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