Towards the Development of Effective Video Segmentation Based on Skew Gaussian Mixture Model
Pavan Kumar Tadiparthi1, Srinivas Yarramalle2
1Pavan Kumar Tadiparthi, Associate Professor, Department of Information Technology, MVGR College of Engineering, India.
2Srinivas Yarramalle, Professor, Department of Information Technology, GIT, GITAM University, India
3K. Nagasri,, M.Tech (Thermal Engineering) Student, Department of Mechanical Engineering, GRIET, Hyderabad, Telangana, India.
Manuscript received on May 06, 2020. | Revised Manuscript received on May 15, 2020. | Manuscript published on June 30, 2020. | PP: 1735-1745 | Volume-9 Issue-5, June 2020. | Retrieval Number: C5712029320/2020©BEIESP | DOI: 10.35940/ijeat.C5712.029320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: video analysis has gained a exponential demand with its usage in security cameras and in most of the real time applications for monitoring the law order. In order to have a precise analysis background subtraction and foreground detection processed are generally considered in the most of the approaches. However ,to have a more precise output from the dynamic motion images, this article proposes a methodology based on skew Gaussian mixture model. The results are analyzed against the existing methods using quality assessment measures.
Keywords: Performance analysis; image segmentation; skew Gaussian; Background subtraction; quality metrics.