Evaluation of Data Compression Techniques for Video Transmission over Wireless Sensor Networks
Mrunal Khedkar1, G.M. Asutkar2, R.Hariprakash3
1Mrunal Khedkar, Department of Electronics and Communication Engg., Priyadarshini Institute of Engineering and Technology, Nagpur, India.
2G.M.Asutkar, Department of Electronics and Communication Engg., Priyadarshini Institute of Engineering and Technology, Nagpur, India.
3R.Hariprakash, Department of Electronics & Communication., Bharat Institute of Higher Education and Research Chennai, India.
Manuscript received on July 20, 2019. | Revised Manuscript received on August 10, 2019. | Manuscript published on August 30, 2019. | PP: 5328-5335 | Volume-8 Issue-6, August 2019. | Retrieval Number: F7923088619/2019©BEIESP | DOI: 10.35940/ijeat.F7923.088619
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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 transmission over WSN is a challenging task because, video data is inherently huge in size and its transmission requires high bandwidth and processing requires more memory and more power. Presently majority of the research work in this area is focused on improving battery life, optimizing network parameters and increasing energy efficiency. The area of best suitable compression scheme for WSN is rarely being explored. This paper focuses on finding out a suitable compression technique for video transmission over WSN. Wireless sensor network (WSN) is an ad-hoc network of sensor nodes, where each node is able to communicate with every other node in the network in single hop or multi-hop manner. It is a low cost, low power and low bandwidth network with each node having limited battery life and limited memory. In order to overcome these challenges, initially image compression is applied on each frame extracted from given video. To find out most suitable compression technique for WSN, the various existing 2D image transforms like DCT, KLT, Slant, Hartley, Hadamard and DST are compared based upon their energy compaction property. The transform that gives more energy compaction is best suitable for WSN. Thus, after selecting a suitable transform for WSN domain, it is applied to obtain compressed video frames. Zigbee protocol based hardware setup is used for serial transmission of RGB video data frames between the nodes. Different parameters are evaluated for received image frames and transmitted image frames. Experimental evaluation shows that zigbee hardware set up improves the reliability and efficiency of video data transmission. This type of WSN set-up can be used for capturing video in any remote and hard-lying (border, mountains, forest) area, where any other types of networks are not available.
Keywords: Wireless Sensor Networks (WSN); Karhunen Loeve transform (KLT), Discrete Cosine Transform (DCT), Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Structural Similarity Index (SSI)