Improving compression ratio using lossy technique for video sequences

Poonam Modi , Debalina Nandy

Compression, lossy, keyframe, fuzzy

To store an uncompressed colour video, even the DVDs of 5 Gbytes are not capable of handling more than few minutes of video. Hence video compression has become very essential. There are two types of compression: lossy and lossless. Generally the video compression is lossy as it checks for areas of redundancy between the successive frames and saves only the differences between the frames. Although the modern video compression techniques are well advanced, video compression still uses the basic steps in image compression and principles such as motion estimation and compensation are implemented to achieve compression in the video. Color is the most dominant feature used by the human brain to perceive an image region to be salient. Since size, shape, location and colors of salient objects vary widely, a fuzzy rule based system is proposed in this research which uses color proximity, color spread, connected components and presence of a face as linguistic variables. These rules are learned using a genetic algorithm. The color space used is the CIELab color space which closely conforms to human perception of colors. With the help of fuzzy rules and clustering we will compress video.

Published Paper   E-Certificate

"Improving compression ratio using lossy technique for video sequences", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.6, Issue 6, page no.00, August-2021, Available :https://ijnrd.org/papers/JETIR2005166.pdf

Volume 6 Issue 6, August-2021

Pages : 00

Paper Reg. ID: IJNRD_170051

Published Paper Id: JETIR2005166

Downloads: 000118835

Research Area: Engineering

Country: rajkot-360007, gujarat, India

Published Paper PDF: https://ijnrd.org/papers/JETIR2005166

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=JETIR2005166

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

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