Abstract

In this paper we present a semi-automatic technique for moving objects segmentation and tracking. Clustering as a segmentation method has been used for many applications. The problem of clustering in many segmentation methods is a need of high performance and low computational cost. We proposed the Fuzzy C-Means method for clustering moving objects. To evaluate the performance, we compare FCM against K-Means and SOM algorithm. Semi-automatic used by human for create image ground truth for measure performance by MSE and PSNR. Based on experiment the MSE of Fuzzy C-Means is lower than K-Means and SOM. Also PSNR of FCM is higher than K-Means and SOM. The result proved that Fuzzy C-Means is promising to cluster pixels in moving objects segmentation.

Original languageEnglish
Publication statusPublished - 2015
Event2015 5th International Workshop on Computer Science and Engineering: Information Processing and Control Engineering, WCSE 2015-IPCE - Moscow, Russian Federation
Duration: 15 Apr 201517 Apr 2015

Conference

Conference2015 5th International Workshop on Computer Science and Engineering: Information Processing and Control Engineering, WCSE 2015-IPCE
Country/TerritoryRussian Federation
CityMoscow
Period15/04/1517/04/15

Keywords

  • Fuzzy c-means
  • Moving object segmentation
  • Semi-automatic

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