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Binary video codec for data reduction in wireless visual sensor networks
Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.ORCID iD: 0000-0002-6484-9260
Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.ORCID iD: 0000-0003-1923-3843
Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
2013 (English)In: Proceedings of SPIE - The International Society for Optical Engineering / [ed] Kehtarnavaz, N; Carlsohn, MF, SPIE - International Society for Optical Engineering, 2013, Art. no. 86560L- p.Conference paper, Published paper (Refereed)
Abstract [en]

Wireless Visual Sensor Networks (WVSN) is formed by deploying many Visual Sensor Nodes (VSNs) in the field. Typical applications of WVSN include environmental monitoring, health care, industrial process monitoring, stadium/airports monitoring for security reasons and many more. The energy budget in the outdoor applications of WVSN is limited to the batteries and the frequent replacement of batteries is usually not desirable. So the processing as well as the communication energy consumption of the VSN needs to be optimized in such a way that the network remains functional for longer duration. The images captured by VSN contain huge amount of data and require efficient computational resources for processing the images and wide communication bandwidth for the transmission of the results. Image processing algorithms must be designed and developed in such a way that they are computationally less complex and must provide high compression rate. For some applications of WVSN, the captured images can be segmented into bi-level images and hence bi-level image coding methods will efficiently reduce the information amount in these segmented images. But the compression rate of the bi-level image coding methods is limited by the underlined compression algorithm. Hence there is a need for designing other intelligent and efficient algorithms which are computationally less complex and provide better compression rate than that of bi-level image coding methods. Change coding is one such algorithm which is computationally less complex (require only exclusive OR operations) and provide better compression efficiency compared to image coding but it is effective for applications having slight changes between adjacent frames of the video. The detection and coding of the Region of Interest (ROIs) in the change frame efficiently reduce the information amount in the change frame. But, if the number of objects in the change frames is higher than a certain level then the compression efficiency of both the change coding and ROI coding becomes worse than that of image coding. This paper explores the compression efficiency of the Binary Video Codec (BVC) for the data reduction in WVSN. We proposed to implement all the three compression techniques i.e. image coding, change coding and ROI coding at the VSN and then select the smallest bit stream among the results of the three compression techniques. In this way the compression performance of the BVC will never become worse than that of image coding. We concluded that the compression efficiency of BVC is always better than that of change coding and is always better than or equal that of ROI coding and image coding. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

Place, publisher, year, edition, pages
SPIE - International Society for Optical Engineering, 2013. Art. no. 86560L- p.
Series
Proceedings of SPIE, ISSN 0277-786X ; 8656
Keyword [en]
Change Coding, Energy Consumption, Image Coding, ROI Coding, Video Coding, Wireless Visual Sensor Network
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:miun:diva-18976DOI: 10.1117/12.2003110ISI: 000333051900020Scopus ID: 2-s2.0-84875844212Local ID: STCISBN: 978-0-8194-9429-0 (print)OAI: oai:DiVA.org:miun-18976DiVA: diva2:622632
Conference
Real-Time Image and Video Processing 2013; Burlingame, CA; United States; 6 February 2013 through 7 February 2013; Code 96385
Available from: 2013-05-22 Created: 2013-05-22 Last updated: 2016-10-20Bibliographically approved

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Khursheed, KhursheedAhmad, NaeemImran, MuhammadO'Nils, Mattias
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CiteExportLink to record
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Citation style
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