Efficient Data Reduction Techniques for Remote Applications of a Wireless Visual Sensor Network. (9th May 2013)

• Record Type: Journal Article
• Authors: Khursheed, Khursheed; Imran, Muhammad; Ahmad, Naeem; O'Nils, Mattias
• Is Part Of: International journal of advanced robotic systems. Volume 10:Number 5(2013)
• Publication Date: 2013-05-09
• Subjects: Image Coding -- Change Coding -- ROI Coding -- Energy Consumption -- Visual Sensor Node -- Image Header -- Wireless Visual Sensor Network; Robotics -- Periodicals; Robotics; Periodicals; 629.892
• DOI: 10.5772/55996
• Languages: English
• ISSNs: 1729-8806

Abstract

Abstract A Wireless Visual Sensor Network (WVSN) is formed by deploying many Visual Sensor Nodes (VSNs) in the field. After acquiring an image of the area of interest, the VSN performs local processing on it and transmits the result using an embedded wireless transceiver. Wireless data transmission consumes a great deal of energy, where energy consumption is mainly dependent on the amount of information being transmitted. The image captured by the VSN contains a huge amount of data. For certain applications, segmentation can be performed on the captured images. The amount of information in the segmented images can be reduced by applying efficient bi-level image compression methods. In this way, the communication energy consumption of each of the VSNs can be reduced. However, the data reduction capability of bi-level image compression standards is fixed and is limited by the used compression algorithm. For applications attributing few changes in adjacent frames, change coding can be applied for further data reduction. Detecting and compressing only the Regions of Interest (ROIs) in the change frame is another possibility for further data reduction. In a communication system, where both the sender and the receiver know the employed compression standard, there is a possibility for further data reduction by not including the header information in the compressed bit stream of the sender. This paper summarizes different information reduction techniques such as image coding, change coding and ROI coding. The main contribution is the investigation of the combined effect of all these coding methods and their application to a few representative real life applications. This paper is intended to be a resource for researchers interested in techniques for information reduction in energy constrained embedded applications.