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Procedia Computer Science
Article . 2016 . Peer-reviewed
License: CC BY NC ND
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Procedia Computer Science
Article
License: CC BY NC ND
Data sources: UnpayWall
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Procedia Computer Science
Article . 2016
License: CC BY NC ND
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Efficient Event Driven Sensing in WMSN Using Zernike Moment

Authors: Manal Al-Sabhan; Adel Soudani;

Efficient Event Driven Sensing in WMSN Using Zernike Moment

Abstract

AbstractImage based sensing in wireless multimedia sensor network (WMSN) is mainly depend on the capability of the deployed scheme to ensure low-power consumption. In depth, the approach of periodic image transmission to the end user, even after compression, will shortly exhaust the energy of the sensors and dramatically reduces the network life time. Thus, detecting an event of interest and extracting the useful information's to decide at source node will avoid flooding the network with unusable data and contributes to extend the whole network life-time. The efficiency of this approach for image-based sensing, in severely resource-constrained sensors, heavily depends on the complexity of the designed sensing scheme.The main contribution of this paper is to present a low-complexity scheme using Zernike Moment to detect a new object and to recognize the appearance of a specific target before sending a notification to the end user. The paper presents the specification of the proposed scheme and its implementation on wireless multimedia sensors. It addresses the performance's evaluation in terms of time and energy consumption. The results show the high accuracy of the proposed approach to efficiently recognize the target and notify the end user with interesting performance that overcomes the efficiency of other similar sensing approaches proposed in the literature.

Related Organizations
Keywords

WMSN, low-power, multimedia sensing, object recognition

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold