JOIN (Jurnal Online Informatika) Volume 4 No. 2 | December 2019: 79-84 DOI: 10.15575/join.v4i2.314 Received: June 18, 2019; Revised: September 10, 2019; Received: December 22, 2019; Published: February 14, 2020 79 Implementation of Image Enhancement Algorithm for Image Forensics Using Matlab Fauzan Novaldi Suteja 1 , Eka Wahyu Hidayat 2 , Nur Widiyasono 3 1,2,3 Informatics Department, Universitas Siliwangi, Tasikmalaya, Indonesia 1 1147006101@studentunsil.ac.id, 2 ekawahyu@unsil.ac.id, 3 nur.widiyasono@unsil.ac.id Abstract- 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. Keywords- Image Enhancement Algorithms, Image Forensics, MSE, PSNR, Timing-Run I. INTRODUCTION Closed-circuit television (CCTV) is a device that serves to record surveillance and security purposes. CCTV is used to prevent crime and malfunction and is also used for other purposes such as monitoring industrial processes and traffic movements. CCTV is one of the most common digital devices in providing digital evidence for the purpose of forensic analysis [1][2]. CCTV has often been found in office buildings, banks, shopping centers and even used by small to medium scale stores and in the homes of upper- middle-class people. The use of surveillance cameras has mostly been used as evidence of a crime or as a reference for law enforcers to recognize the perpetrators so that they can explore further information to arrest the perpetrators [3]. The problem from CCTV for forensic analysis is the quality of recording from CCTV that is often bad due to several factors such as the type of camera, configuration, and camera position [2] lighting on the CCTV installation which results in too bright or too dark, noisy images when sending through a transmission line, the image is less sharp, blurred, etc. [4] can affect the results of analysis of identification and processing of information related to events recorded on CCTV. Enhancing image quality needs to be done so that CCTV results can provide complete information and identification accurately so that further analysis can be carried out. Some algorithms on image enhancement processing in this program are expected to be able to enhance the quality of each input image from CCTV according to image conditions and situations related to the right algorithm so that every possibility of CCTV image results can be solved with this program. CCTV is basically categorized into video forensics because it deals with evidence in the form of video recordings [5]. The pre-processing process needs to be done to get the CCTV image that comes from the CCTV video recording frame. Algorithm Image Enhancement applied to the application is Convolution (which consists of Low Pass Filters, High Pass Filters, Median Filters, Mean Filters and Gaussian Filters) [6], [7], [8], [1], [9] Histogram Equalization [10], [11], [12][12], [13], Wiener Filter [14], Stretching Contrast [15], [10], [16], [17], [18] and Linear Interpolation [19], [20] All algorithms are collected in a program to process image quality enhancements. This image quality enhancement application is created using MATLAB. This application was made aimed at enhancing the quality of CCTV images that are both visually so that they can obtain complete information and accurate identification. This application is expected to help related parties in carrying out the process of improving image quality. Related research to enhance image quality has been done before. some of them try to repair digital video [21], improve the screenshot results [20] and mammogram [22]. This study only compares the performance of Image Enhancement algorithms with other algorithms such as Histogram Equalization [10], [11], [12], Stretching Contrast [15], [10], [18], Convolution [6],[7], [12], , Wiener Filter [14] and Interpolation [19][20]. Research related to image quality enhancement has been done before. Some of them tried to repair digital video [21], improve the screenshots of images [20] and mammogram [22]. Some of them only compare the