Implementation of Image Enhancement Algorithm for Image Forensics using Mathlab

The purpose of this journal is to explain the implementation of the image enhancement algorithm for image forensics. Image Forensic deals with the types of digital evidence in the form of digital image files. One of the most commonly used digital devices in providing digital evidence for forensic an...

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Main Authors: Fauzan Novaldi Suteja, Eka Wahyu Hidayat, Nur Widiyasono
Format: Article
Language:English
Published: Universitas Islam Negeri (UIN) Sunan Gunung Djati Bandung 2020-02-01
Series:JOIN: Jurnal Online Informatika
Subjects:
Online Access:https://join.if.uinsgd.ac.id/index.php/join/article/view/314
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spelling doaj-bc6cf2e0ad124329a8acfed92285ae9f2020-11-25T03:46:37ZengUniversitas Islam Negeri (UIN) Sunan Gunung Djati BandungJOIN: Jurnal Online Informatika2528-16822527-91652020-02-0142798410.15575/join.v4i2.31495Implementation of Image Enhancement Algorithm for Image Forensics using MathlabFauzan Novaldi Suteja0Eka Wahyu Hidayat1Nur Widiyasono2Universitas SiliwangiUniversitas SiliwangiUniversitas SiliwangiThe purpose of this journal is to explain the implementation of the image enhancement algorithm for image forensics. Image Forensic deals with the types of digital evidence in the form of digital image files. One of the most commonly used digital devices in providing digital evidence for forensic analysis is CCTV (Closed-Circuit Television). CCTV images have a low quality such as noise, blur, lack of light intensity, etc., so that the image must be enhanced so that forensic analysis can be done. To enhance image quality, an application is needed by applying the image enhancement algorithm. The algorithm applied to the application is a Low Pass Filter to increase low pixel intensity, High Pass Filter to increase high pixel intensity, Median Filter to replaces the original pixel value with the pixel center value of the image, Mean Filter to replaces the original pixel value with a value the average pixel of the image, the Gaussian Filter for reducing noise in the image, the Wiener Filter to reduce blur in the image, the Histogram Equalization spreads the image histogram value, Contrast Stretching to stretch the contrast intensity in the image and Bicubic Interpolation to increase the image size and resize the image. In this study, the application was built using MATLAB and the testing process for each algorithm was based on Timing-Run, MSE and PSNR parameters. From the test, the average MSE value is 1058.512083 and the PSNR value is 541.61875 dB, which means that the resulting image has a fairly high level of similarity and the average time needed to process the algorithm for the image is 0.114627915 seconds.https://join.if.uinsgd.ac.id/index.php/join/article/view/314image enhancement algorithms, image forensics, mse, psnr, timing-run.
collection DOAJ
language English
format Article
sources DOAJ
author Fauzan Novaldi Suteja
Eka Wahyu Hidayat
Nur Widiyasono
spellingShingle Fauzan Novaldi Suteja
Eka Wahyu Hidayat
Nur Widiyasono
Implementation of Image Enhancement Algorithm for Image Forensics using Mathlab
JOIN: Jurnal Online Informatika
image enhancement algorithms, image forensics, mse, psnr, timing-run.
author_facet Fauzan Novaldi Suteja
Eka Wahyu Hidayat
Nur Widiyasono
author_sort Fauzan Novaldi Suteja
title Implementation of Image Enhancement Algorithm for Image Forensics using Mathlab
title_short Implementation of Image Enhancement Algorithm for Image Forensics using Mathlab
title_full Implementation of Image Enhancement Algorithm for Image Forensics using Mathlab
title_fullStr Implementation of Image Enhancement Algorithm for Image Forensics using Mathlab
title_full_unstemmed Implementation of Image Enhancement Algorithm for Image Forensics using Mathlab
title_sort implementation of image enhancement algorithm for image forensics using mathlab
publisher Universitas Islam Negeri (UIN) Sunan Gunung Djati Bandung
series JOIN: Jurnal Online Informatika
issn 2528-1682
2527-9165
publishDate 2020-02-01
description The purpose of this journal is to explain the implementation of the image enhancement algorithm for image forensics. Image Forensic deals with the types of digital evidence in the form of digital image files. One of the most commonly used digital devices in providing digital evidence for forensic analysis is CCTV (Closed-Circuit Television). CCTV images have a low quality such as noise, blur, lack of light intensity, etc., so that the image must be enhanced so that forensic analysis can be done. To enhance image quality, an application is needed by applying the image enhancement algorithm. The algorithm applied to the application is a Low Pass Filter to increase low pixel intensity, High Pass Filter to increase high pixel intensity, Median Filter to replaces the original pixel value with the pixel center value of the image, Mean Filter to replaces the original pixel value with a value the average pixel of the image, the Gaussian Filter for reducing noise in the image, the Wiener Filter to reduce blur in the image, the Histogram Equalization spreads the image histogram value, Contrast Stretching to stretch the contrast intensity in the image and Bicubic Interpolation to increase the image size and resize the image. In this study, the application was built using MATLAB and the testing process for each algorithm was based on Timing-Run, MSE and PSNR parameters. From the test, the average MSE value is 1058.512083 and the PSNR value is 541.61875 dB, which means that the resulting image has a fairly high level of similarity and the average time needed to process the algorithm for the image is 0.114627915 seconds.
topic image enhancement algorithms, image forensics, mse, psnr, timing-run.
url https://join.if.uinsgd.ac.id/index.php/join/article/view/314
work_keys_str_mv AT fauzannovaldisuteja implementationofimageenhancementalgorithmforimageforensicsusingmathlab
AT ekawahyuhidayat implementationofimageenhancementalgorithmforimageforensicsusingmathlab
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