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Armansyah
Department of Computer Science, Faculty of Science and Technology State Islamic University of North Sumatera Medan
Computer Science & IT

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IDENTIFICATION OF AUTHENTICITY BASED ON DIGITAL IMAGES USING LOCAL BINARY PATTERN AND SUPPORT VECTOR MACHINE METHODS DIAN NIKITA SARI; Muhammad Ikhsan; Armansyah
INFOKUM Vol. 10 No. 4 (2022): October, computer, information and engineering
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (276.262 KB)

Abstract

Technological progress has an influence on development. Where the influence that arises can be in the form of positive or negative influences related to community behavior in utilizing and applying existing information technology. Paper money is a basic need in society where its use is as a means of payment, either cash or electronically. Counterfeit money is currency whose production is carried out without any legal approval from the state or government on the official website of Bank Indonesia. Counterfeit money in Indonesia from 2014 to 2018 has decreased and increased on a national scale. In this study the authors want to make a study to be able to distinguish counterfeit money or real money with the concept of Computer Science in the field of image processing using extraction and classification techniques. In this study, the extraction technique used is texture extraction with LBP and Classification using SVM to be able to recognize the authenticity of banknotes using the MATLAB application as a means to complete the analysis process
APPLICATION OF CONTRAST LIMITED ADAPTIVE HISTOGRAM EQUALIZATION (CLAHE) AND GAUSSIAN FILTER METHODS FOR IMPROVEMENT OF IMAGE QUALITY ON CLOSED CIRCUIT TELEVISION (CCTV) Nurul Hadi Muliani Hariadi Saputra; Armansyah; Mhd Furqan
INFOKUM Vol. 10 No. 4 (2022): October, computer, information and engineering
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (327.801 KB)

Abstract

The results of video recordings from CCTV cameras depend on the quality of the CCTV facilities themselves, some can capture results from dark rooms or vice versa. If the room has a lot of light, then the CCTV footage looks good, if the room lacks light, the CCTV camera results only see objects that have light, so there are some sides of the object that look dark and the results of the objects recorded are not optimal. So to minimize dark CCTV catches, It is essential to have a system that can boost the performance of CCTV, especially on CCTV screenshots. Methods that can be used to improve the quality of CCTV images are CLAHE and Gaussian Filter methods. CCTV pictures captured in low light may have their contrast stabilized using the CLAHE technique, and noise can be removed using the Gaussian Filter method. Based on the CLAHE test, it was able to increase the contrast of CCTV with clip limit histogram, and the Gaussian Filter succeeded in eliminating CCTV image noise while maintaining the quality of CCTV images from CLAHE, this is based on the MSE value which is close to 0 (zero). Keywords: Enhancement, CCTV, Imagery, CLAHE, Gaussian Filter.
Co-Authors DIAN NIKITA SARI Mhd Furqan Muhammad Ikhsan Nurul Hadi Muliani Hariadi Saputra