An Online Video Segmentation using Improved Particle Swarm Optimization Technique
R.Durga1, G.Yamuna2
1R.Durga*, Assistant Professor, Department of Electronics and Communication Engineering, Government college of Engineering, Srirangam, Trichy, India.
2G.Yamuna, Professor, Department of Electronics and Communication Engineering, Annamalai University, Annamalainagar ,India.

Manuscript received on November 12, 2019. | Revised Manuscript received on November 25, 2019. | Manuscript published on 30 November, 2019. | PP: 5256-5260 | Volume-8 Issue-4, November 2019. | Retrieval Number: D7427118419/2019©BEIESP | DOI: 10.35940/ijrte.D7427.118419

Open Access | Ethics and Policies | Cite  | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (

Abstract: Video segmentation is the original needed stage in the video method wherever the whole video is splits into volumetric sections, each segment consists of spatial substantive with temporal domain information. We proposed a video segmentation algorithm using Short Term Hierarchical Fast Watershed Algorithm (STHFWA )and Fractional Order Darwinian Particle Swarm Optimization(FODPSO) technique. In STHFWA ,the k-means clustering is used to find out the initial segments based on the color intensity present in the frames and Fast watershed algorithm is applied to construct the rigid lines based on the catchment basin coordinates to avoid over segmentation. Finally, FODPSO optimization is used to reduce the computational complexity. Also, the experimental results are analyzed on a VSB100 dataset, shows that the proposed algorithm outperforms modern online video segmentation techniques significantly.
Keywords: Video Segmentation, Dual Complex Tree Wavelet Transform, Fast Watershed Algorithm, Fractional Order Darwinian Particle Swarm Optimization (FODPSO).
Scope of the Article: Design Optimization of Structures.