By Topic

Adaptive threshold for background subtraction in moving object detection using Fuzzy C-Means clustering

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Moch Arief Soeleman ; Dept. of Comput. Sci., Dian Nuswantoro Univ., Semarang, Indonesia ; Mochamad Hariadi ; Mauridhi Hery Purnomo

Background subtraction is the important part of moving object detection. The problem of background subtraction is threshold selection strategy. This paper proposed a Fuzzy C-Means (FCM) algorithm to produce an adaptive threshold for background subtraction in moving object detection. To evaluate the performance, FCM were compared against standard Otsu algorithm as threshold selection strategy. Mean Square Error (MSE) and Peak Signal Noise Ratio (PSNR) was used to measure the performance. Based on the experiment, the MSE of FCM is lower than MSE of Otsu and PSNR of FCM is higher than PSNR of Otsu. The result proved that FCM is promising to classify the pixels as foreground or background in moving object detection.

Published in:

TENCON 2012 - 2012 IEEE Region 10 Conference

Date of Conference:

19-22 Nov. 2012