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Dara Incam Ramadhan
Department of Electrical Engineering, Faculty of Engineering, Universitas Riau
Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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COMPARISON OF BACKGROUND SUBTRACTION, SOBEL, ADAPTIVE MOTION DETECTION, FRAME DIFFERENCES, AND ACCUMULATIVE DIFFERENCES IMAGES ON MOTION DETECTION Dara Incam Ramadhan; Indah Permata Sari; Linna Oktaviana Sari
SINERGI Vol 22, No 1 (2018)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (634.376 KB) | DOI: 10.22441/sinergi.2018.1.009

Abstract

Nowadays, digital image processing is not only used to recognize motionless objects, but also used to recognize motions objects on video. One use of moving object recognition on video is to detect motion, which implementation can be used on security cameras. Various methods used to detect motion have been developed so that in this research compared some motion detection methods, namely Background Substraction, Adaptive Motion Detection, Sobel, Frame Differences and Accumulative Differences Images (ADI). Each method has a different level of accuracy. In the background substraction method, the result obtained 86.1% accuracy in the room and 88.3% outdoors. In the sobel method the result of motion detection depends on the lighting conditions of the room being supervised. When the room is in bright condition, the accuracy of the system decreases and when the room is dark, the accuracy of the system increases with an accuracy of 80%. In the adaptive motion detection method, motion can be detected with a condition in camera visibility there is no object that is easy to move. In the frame difference method, testing on RBG image using average computation with threshold of 35 gives the best value. In the ADI method, the result of accuracy in motion detection reached 95.12%.
Co-Authors Indah Permata Sari Sari, Linna Oktaviana