International Journal of Advanced and Applied Sciences
Int. j. adv. appl. sci.
EISSN: 2313-3724
Print ISSN: 2313-626X
Volume 4, Issue 6 (June 2017), Pages: 28-34
Title: A comparative study on mixture of Gaussians for object segmentation
Author(s): Robina Khatoon 1, Syed Muhammad Saqlain Shah 1, *, Shafina Bibi 1, Imran Khan 1, Muhammad Usman Ashraf 1, 2
Affiliation(s):
1Department of CS & SE, International Islamic University, Islamabad, Pakistan
2Institute of Business Management Sciences, University of Agriculture, Faisalabad, Pakistan
https://doi.org/10.21833/ijaas.2017.06.004
Abstract:
Segmentation is the fundamental step in most of digital image processing and computer vision based applications for feature extraction. The purpose of segmentation is to partition an image into foreground and background. Numerous segmentation algorithms have been proposed for the last four decades ranging from degraded images; high and low contrast images, indoor video, outdoor videos, videos with static background and dynamic backgrounds. This paper presents evaluation and comparison of segmentation techniques used for real-time moving objects through static and adaptive number of Gaussians. The techniques are tested for both indoor and outdoor scenes. The comparison is presented on the basis of qualitative results and computational complexities.
© 2017 The Authors. Published by IASE.
This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords: Mixture of Gaussians, Segmentation, Foreground
Article History: Received 19 January 2017, Received in revised form 14 March 2017, Accepted 18 March 2017
Digital Object Identifier:
https://doi.org/10.21833/ijaas.2017.06.004
Citation:
Khatoon R, Shah SMS, Bibi S, Khan I, Ashraf MU (2017). A comparative study on mixture of Gaussians for object segmentation. International Journal of Advanced and Applied Sciences, 4(6): 28-34
http://www.science-gate.com/IJAAS/V4I6/Khatoon.html
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