A Novel Framework for Fast Video Inpainting
Md. Salman Bombaywala1, Chirag Paunwala2

1Md.Salman R. Bombaywala, Uka Tarsadia University, Bardoli, (Gujarat), India. 2Chirag N. Paunwala, Department of Electronics and Communication Engineering, Sarvajanik College of Enggineering and Technology, Surat, (Gujarat), India.
Manuscript received on 24 January 2019 | Revised Manuscript received on 30 March 2019 | Manuscript published on 30 January 2019 | PP: 216-223 | Volume-7 Issue-6, March 2019 | Retrieval Number: E2052017519©BEIESP
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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 inpainting is considered as a complex problem in the current literature. This paper proposes a fast, efficient and automatic method of video inpainting to inpaint moving objects in the video. The presented algorithm employs the spatiotemporal coherency present in the video frames for inpainting while considering the fact that the background either has periodic motion or it remains stationary. The algorithm does not require any manual generation of the mask. Batch frame based inpainting is proposed to maintain motion information in case of background having periodic motion. A new dissimilarity measure; 3D N-SSD is introduced to find similar frames for frame-based video inpainting algorithms. The proposed algorithm is tested for different background and illumination conditions. We have done speed and quality test analysis by inpainting videos of different backgrounds. Quick execution times and high PSNR values for inpainted videos show effectiveness of our algorithm.
Keywords: 3D N-SSD, Inpainting mask, Periodic background, Reference frame, Temporal data, Video inpainting
Scope of the Article: Patterns and Frameworks