Map Reduce Based Endoscopic Video Compression and Artificial Intelligent Video Splitter Approach for Lossless Video

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Heena Kouser Gogi, Suvarna Nandyal, Asma Anjum, Deepa puranik, Lubna Taranum M P, Aaesha Sultana R

Abstract

Endoscopic video storage is a major issue today in cloud-based health centre.  The Electronics Health Record must include full-length endoscopic surgeries for diagnosis and research.  Hence this is paper presents compression of endoscopic using Map Reduce technique. Artificial Intelligent based solution is employed as an intelligent video splitter to form the key value as "Map" stages to filter the endoscopic video into a group of frames based on redundancy. These outputs are passed to "reduce" to merge them into a single output. After mapping and reducing endoscopic video frames, lossless compression is applied and the experimental results for PSNR 30-40 dB, SSI 0.7-0.8, Bitrate 32.17 and MSE 2.1 is obtained.

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