ctrlnum 779
fullrecord <?xml version="1.0"?> <dc schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><relation>http://repository.unsri.ac.id/779/</relation><title>PERBAIKAN KUALITAS CITRA IRIS MATA MENGGUNAKAN METODE HISTOGRAM EQUALIZATION, ADAPTIVE HISTOGRAM EQUALIZATION DAN OPERASI MORFOLOGI</title><creator>RICADONNA, RAHMA</creator><creator>Erwin, Erwin</creator><subject>T57.6-57.97 Operations research. Systems analysis</subject><subject>T58.5-58.64 Information technology</subject><description>The iris pattern is unique to each eye subject and remains stable throughout life. Iris is known as the most accurate and reliable part of one's identification. During the data acquisition process, the iris image dataset that the author uses is unbalanced contrast and noise in the form of light reflection. To overcome this problem, it is necessary to improve the quality of the image so that the image is easier to analyze by the image-based automation process. The method used in the image enhancement process in this study is histogram equalization (HE) and Adaptive Histogram Equalization (AHE). Histogram equalization serves to balance contrast and minimize noise found in the iris image that I use. Contrast enhancement HE can change the brightness thoroughly which results in low saturation or excessive saturation in certain parts. AHE improves the shortcomings of HE by increasing contrast locally or in certain parts in more detail. In addition to improving image quality, morphological image processing techniques are also used. Methods Morphological operations function as a method that will eliminate noise found in the iris image. The results of the histogram equalization method, adaptive histogram equalization and morphological operations will be measured the image quality value using the Peak Signal Noise Ratio (PSNR) measurement method.</description><date>2019-05-24</date><type>Thesis:Thesis</type><type>PeerReview:NonPeerReviewed</type><type>Book:Book</type><language>ind</language><rights>cc_public_domain</rights><identifier>http://repository.unsri.ac.id/779/3/RAMA_56201_09011281320013_0029017101_01_front_ref.pdf</identifier><type>Book:Book</type><language>ind</language><rights>cc_public_domain</rights><identifier>http://repository.unsri.ac.id/779/4/RAMA_56201_09011281320013_0029017101_02.pdf</identifier><type>Book:Book</type><language>ind</language><rights>cc_public_domain</rights><identifier>http://repository.unsri.ac.id/779/5/RAMA_56201_09011281320013_0029017101_03.pdf</identifier><type>Book:Book</type><language>ind</language><rights>cc_public_domain</rights><identifier>http://repository.unsri.ac.id/779/8/RAMA_56201_09011281320013_0029017101_04.pdf</identifier><type>Book:Book</type><language>ind</language><rights>cc_public_domain</rights><identifier>http://repository.unsri.ac.id/779/6/RAMA_56201_09011281320013_0029017101_05.pdf</identifier><type>Book:Book</type><language>ind</language><rights>cc_public_domain</rights><identifier>http://repository.unsri.ac.id/779/7/RAMA_56201_09011281320013_0029017101_06_REF.pdf</identifier><type>Book:Book</type><language>ind</language><rights>cc_public_domain</rights><identifier>http://repository.unsri.ac.id/779/9/RAMA_56201_09011281320013_0029017101_07_LAMP.pdf</identifier><identifier> RICADONNA, RAHMA and Erwin, Erwin (2019) PERBAIKAN KUALITAS CITRA IRIS MATA MENGGUNAKAN METODE HISTOGRAM EQUALIZATION, ADAPTIVE HISTOGRAM EQUALIZATION DAN OPERASI MORFOLOGI. Undergraduate thesis, Sriwijaya University. </identifier><recordID>779</recordID></dc>
language ind
format Thesis:Thesis
Thesis
PeerReview:NonPeerReviewed
PeerReview
Book:Book
Book
author RICADONNA, RAHMA
Erwin, Erwin
title PERBAIKAN KUALITAS CITRA IRIS MATA MENGGUNAKAN METODE HISTOGRAM EQUALIZATION, ADAPTIVE HISTOGRAM EQUALIZATION DAN OPERASI MORFOLOGI
publishDate 2019
isbn 0901128132001
topic T57.6-57.97 Operations research. Systems analysis
T58.5-58.64 Information technology
url http://repository.unsri.ac.id/779/3/RAMA_56201_09011281320013_0029017101_01_front_ref.pdf
http://repository.unsri.ac.id/779/4/RAMA_56201_09011281320013_0029017101_02.pdf
http://repository.unsri.ac.id/779/5/RAMA_56201_09011281320013_0029017101_03.pdf
http://repository.unsri.ac.id/779/8/RAMA_56201_09011281320013_0029017101_04.pdf
http://repository.unsri.ac.id/779/6/RAMA_56201_09011281320013_0029017101_05.pdf
http://repository.unsri.ac.id/779/7/RAMA_56201_09011281320013_0029017101_06_REF.pdf
http://repository.unsri.ac.id/779/9/RAMA_56201_09011281320013_0029017101_07_LAMP.pdf
http://repository.unsri.ac.id/779/
contents The iris pattern is unique to each eye subject and remains stable throughout life. Iris is known as the most accurate and reliable part of one's identification. During the data acquisition process, the iris image dataset that the author uses is unbalanced contrast and noise in the form of light reflection. To overcome this problem, it is necessary to improve the quality of the image so that the image is easier to analyze by the image-based automation process. The method used in the image enhancement process in this study is histogram equalization (HE) and Adaptive Histogram Equalization (AHE). Histogram equalization serves to balance contrast and minimize noise found in the iris image that I use. Contrast enhancement HE can change the brightness thoroughly which results in low saturation or excessive saturation in certain parts. AHE improves the shortcomings of HE by increasing contrast locally or in certain parts in more detail. In addition to improving image quality, morphological image processing techniques are also used. Methods Morphological operations function as a method that will eliminate noise found in the iris image. The results of the histogram equalization method, adaptive histogram equalization and morphological operations will be measured the image quality value using the Peak Signal Noise Ratio (PSNR) measurement method.
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