Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Topographic distance and watershed lines
Signal Processing - Special issue on mathematical morphology and its applications to signal processing
Wireless integrated network sensors
Communications of the ACM
The watershed transform: definitions, algorithms and parallelization strategies
Fundamenta Informaticae - Special issue on mathematical morphology
Watershed-based segmentation and region merging
Computer Vision and Image Understanding
A two-dimensional interpolation function for irregularly-spaced data
ACM '68 Proceedings of the 1968 23rd ACM national conference
EnviroTrack: Towards an Environmental Computing Paradigm for Distributed Sensor Networks
ICDCS '04 Proceedings of the 24th International Conference on Distributed Computing Systems (ICDCS'04)
A fast watershed algorithm based on chain code and its application in image segmentation
Pattern Recognition Letters
Region Abstraction for Event Tracking in Wireless Sensor Networks
ISPAN '05 Proceedings of the 8th International Symposium on Parallel Architectures,Algorithms and Networks
Using logical neighborhoods to enable scoping in wireless sensor networks
Proceedings of the 3rd international Middleware doctoral symposium
An improved watershed algorithm based on efficient computation of shortest paths
Pattern Recognition
Programming sensor networks using abstract regions
NSDI'04 Proceedings of the 1st conference on Symposium on Networked Systems Design and Implementation - Volume 1
State-Centric Programming for Sensor-Actuator Network Systems
IEEE Pervasive Computing
Parallel Volume Image Segmentation with Watershed Transformation
SCIA '09 Proceedings of the 16th Scandinavian Conference on Image Analysis
Fast, parallel watershed algorithm based on path tracing
ICCVG'10 Proceedings of the 2010 international conference on Computer vision and graphics: Part II
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The availability and quality of information extracted from Wireless Sensor Networks (WSNs) revolutionised a wide range of application areas. The success of any WSN application is, nonetheless, determined by the ability to retrieve information with the required level of accuracy, within specified time constraints, and with minimum resource utilisation. This paper presents a new approach to localised information extraction that utilises theWatershed segmentation algorithm to dynamically group nodes into segments, which can be used as programming abstractions upon which different query operations can be performed. Watershed results in a set of well delimited areas, such that the number of necessary operations (communication and computation) to answer a query are minimised. This paper presents a fully asynchronous Watershed implementation, where nodes can compute their local data in parallel and independently from one another. The preliminary experimental results demonstrate that the proposed approach is able to significantly reduce the query processing cost and time without involving any loss of efficiency.