Article Per Year (5 Year)
p-Index From 2020 - 2025
0
P-Index
This Author published in this journals
All Journal Proceeding of the Electrical Engineering Computer Science and Informatics
S. R. Sulistiyanti
University of Lampung
Computer Science & IT Electrical & Electronics Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
A Moving Objects Detection in Underwater Video Using Subtraction of the Background Model M. R. Prabowo; N. Hudayani; S. Purwiyanti; S. R. Sulistiyanti; F. X. A. Setyawan
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (932.244 KB) | DOI: 10.11591/eecsi.v4.1075

Abstract

This paper proposes a method for detecting moving objects on an underwater video. Video obtained using an underwater camera to capture the environmental conditions of the area. This research is the initial stage of the underwater surveillance system. Underwater surveillance system enables objects passing can be recognized shapes, types, and its behavior. The  detection method  used  in  this  research is  a subtraction between the current frames with the background modeling results. Underwater video retrieval has a high level of difficulty because the background is always changing either due  to  a  change the  intensity and  the  movement of  water currents. Therefore, it needs to be made an appropriate background model to address this problem. Modeling of the background on this research using adaptive modeling method, where the intensity of the background pixels is updated based on  inference  of  the  background  intensity  before.  If  the intensity of the pixels changed drastically beyond the allowed threshold value, the pixel is considered as the pixels of the object and the pixel values of the background model are updated based on this pixel value. The effectiveness of the proposed method is expressed with the value of recall and precision. The average recall value of the two videos is 83% and the value of its precision is 67.5%.
Co-Authors F. X. A. Setyawan M. R. Prabowo N. Hudayani S. Purwiyanti