Article Per Year (5 Year)
p-Index From 2021 - 2026
0
P-Index
This Author published in this journals
All Journal International Journal of Intelligent Systems and Applications in Engineering
Gerek, Ömer Nezih
Prof. Dr. Ismail SARITAS
Computer Science & IT

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
A Note on Background Subtraction by Utilizing a New Tensor Approach Işık, Şahin; Özkan, Kemal; Doğan, Muzaffer; Gerek, Ömer Nezih
International Journal of Intelligent Systems and Applications in Engineering 2016: Special Issue
Publisher : Prof. Dr. Ismail SARITAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.267154

Abstract

This study deals with determining the foreground region by background subtraction based on a new tensor decomposition method. With this aim, the concept of Common Matrix Approach (CMA) is utilized with a purpose of background modelling. The performance of proposed method is validated by making experiments on real videos provided by Wallflower dataset. The obtained results are compared with well-known methods based on subjective on objective evaluation measures. The obtained good results indicate that using the CMA algorithm for background modelling is a simple and effective technique in terms computational cost and implementation. As an eventual result, we have observed that the superior results are determined on complex backgrounds including dynamic objects and illumination variation in image sets.
A new subspace based solution to background modelling and change detection Işık, Şahin; Özkan, Kemal; Gerek, Ömer Nezih; Doğan, Muzaffer
International Journal of Intelligent Systems and Applications in Engineering 2016: Special Issue
Publisher : Prof. Dr. Ismail SARITAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.267148

Abstract

For surveillance system, the background subtraction plays an important role for moving object detection with an algorithm embedded in the camera. Since the existence algorithms cannot satisfy the good accuracy on complex backgrounds including illumination change and dynamic objects, we have put forward the concept of Common Vector Approach (CVA) as a new idea for background modelling. Effectiveness of proposed method is presented through the experiments on popular Wallflower dataset. The obtained visual outputs are compared with well-known methods based on the subjective and objective criteria. From the overall evaluation, we can note the proposed method is not only exhibit successful foreground detection results, but also promises an effective and efficient system for background modelling.
Co-Authors Özkan, Kemal Doğan, Muzaffer Işık, Şahin