PENGGUNAAN WAVELET IMAGE ENHANCEMENT DAN TEKSTUR ENERGI CITRA UNTUK MENDETEKSI MASSA MENCURIGAKAN PADA MAMOGRAM
Abstract: The Use of Wavelet Image Enhancement and Image Energy Texture for Detecting Suspected Mass in Mammogram. Breast cancer is one of the most dangerous cancer for female. The risk of the cancer can be lessened by early detection using mammography. This research sets out to detect and sign the...
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Universitas Negeri Malang
2012-09-01
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Online Access: | http://journal.um.ac.id/index.php/teknologi-kejuruan/article/view/3187 |
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doaj-3b03577e626f4d38831da3fdb2466c322020-11-24T22:51:24ZindUniversitas Negeri MalangTeknologi dan Kejuruan0852-00622477-04422012-09-0131110.17977/tk.v31i1.31872859PENGGUNAAN WAVELET IMAGE ENHANCEMENT DAN TEKSTUR ENERGI CITRA UNTUK MENDETEKSI MASSA MENCURIGAKAN PADA MAMOGRAMHeru Wahyu HerwantoAbstract: The Use of Wavelet Image Enhancement and Image Energy Texture for Detecting Suspected Mass in Mammogram. Breast cancer is one of the most dangerous cancer for female. The risk of the cancer can be lessened by early detection using mammography. This research sets out to detect and sign the edge of suspected mass in mammogram. The method used is an image enhancement and segmentation. The process of image enhancement uses the method of adaptive wavelet enhancement, meanwhile the segmentation uses the calculation of image energy texture with laws filter, smoothing, tressholding, morphology, and boudary extraction. The final result of this method will be compared with those of same method with corrected images abd adaptive histogram equalization. The result of the research shows that there is an improvement of enthropy, deviation standard, and contrast values. The overall execution program takes 1.82869 seconds longer than the adaptive histogram equalization.http://journal.um.ac.id/index.php/teknologi-kejuruan/article/view/3187adaptif wavelet enhancementkanker payudaramassestexture energy |
collection |
DOAJ |
language |
Indonesian |
format |
Article |
sources |
DOAJ |
author |
Heru Wahyu Herwanto |
spellingShingle |
Heru Wahyu Herwanto PENGGUNAAN WAVELET IMAGE ENHANCEMENT DAN TEKSTUR ENERGI CITRA UNTUK MENDETEKSI MASSA MENCURIGAKAN PADA MAMOGRAM Teknologi dan Kejuruan adaptif wavelet enhancement kanker payudara masses texture energy |
author_facet |
Heru Wahyu Herwanto |
author_sort |
Heru Wahyu Herwanto |
title |
PENGGUNAAN WAVELET IMAGE ENHANCEMENT DAN TEKSTUR ENERGI CITRA UNTUK MENDETEKSI MASSA MENCURIGAKAN PADA MAMOGRAM |
title_short |
PENGGUNAAN WAVELET IMAGE ENHANCEMENT DAN TEKSTUR ENERGI CITRA UNTUK MENDETEKSI MASSA MENCURIGAKAN PADA MAMOGRAM |
title_full |
PENGGUNAAN WAVELET IMAGE ENHANCEMENT DAN TEKSTUR ENERGI CITRA UNTUK MENDETEKSI MASSA MENCURIGAKAN PADA MAMOGRAM |
title_fullStr |
PENGGUNAAN WAVELET IMAGE ENHANCEMENT DAN TEKSTUR ENERGI CITRA UNTUK MENDETEKSI MASSA MENCURIGAKAN PADA MAMOGRAM |
title_full_unstemmed |
PENGGUNAAN WAVELET IMAGE ENHANCEMENT DAN TEKSTUR ENERGI CITRA UNTUK MENDETEKSI MASSA MENCURIGAKAN PADA MAMOGRAM |
title_sort |
penggunaan wavelet image enhancement dan tekstur energi citra untuk mendeteksi massa mencurigakan pada mamogram |
publisher |
Universitas Negeri Malang |
series |
Teknologi dan Kejuruan |
issn |
0852-0062 2477-0442 |
publishDate |
2012-09-01 |
description |
Abstract: The Use of Wavelet Image Enhancement and Image Energy Texture for Detecting Suspected Mass in Mammogram. Breast cancer is one of the most dangerous cancer for female. The risk of the cancer can be lessened by early detection using mammography. This research sets out to detect and sign the edge of suspected mass in mammogram. The method used is an image enhancement and segmentation. The process of image enhancement uses the method of adaptive wavelet enhancement, meanwhile the segmentation uses the calculation of image energy texture with laws filter, smoothing, tressholding, morphology, and boudary extraction. The final result of this method will be compared with those of same method with corrected images abd adaptive histogram equalization. The result of the research shows that there is an improvement of enthropy, deviation standard, and contrast values. The overall execution program takes 1.82869 seconds longer than the adaptive histogram equalization. |
topic |
adaptif wavelet enhancement kanker payudara masses texture energy |
url |
http://journal.um.ac.id/index.php/teknologi-kejuruan/article/view/3187 |
work_keys_str_mv |
AT heruwahyuherwanto penggunaanwaveletimageenhancementdanteksturenergicitrauntukmendeteksimassamencurigakanpadamamogram |
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