Fuzzy clustering in avian infrared imagery application

There are large number of reports regarding bird and bat mortality due to strikes with turbine blades in wind farm applications. This issue is threatening the avian life especially migratory birds and bats. Avian monitoring techniques can be used to detect bird and bats, assess their activity, and m...

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Bibliographic Details
Main Authors: Mirzaei, Golrokh, Jamali, Mohsin M., Ross, Jeremy D., Gorsevski, Peter V., Bingman, Verner P.
Format: Conference Proceeding
Language:English
Subjects:
Birds
Cameras
Clustering algorithms
Feature extraction
Insects
Monitoring
Wind turbines
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Summary:There are large number of reports regarding bird and bat mortality due to strikes with turbine blades in wind farm applications. This issue is threatening the avian life especially migratory birds and bats. Avian monitoring techniques can be used to detect bird and bats, assess their activity, and make intelligent decision for construction of wind farms. In this paper, an IR monitoring approach is used for monitoring birds and bats in an area potential for future construction of wind turbines. As there is no a priori database of images for local birds/bats, clustering is used as an effective technique to group different avian categories. Fuzzy C Means is developed in this application to cluster the targets into birds, bats, and insects groups. The results are then compared with a hard Ant Clustering Algorithm. The number of created clusters and number of individuals in each cluster are then compared.
ISSN:2154-0357
2154-0373
DOI:10.1109/EIT.2014.6871768