Automated image analysis for the detection of benthic crustaceans and bacterial mat coverage using the VENUS undersea cabled network.

Sensors
Jacopo AguzziPaolo Menesatti

Abstract

The development and deployment of sensors for undersea cabled observatories is presently biased toward the measurement of habitat variables, while sensor technologies for biological community characterization through species identification and individual counting are less common. The VENUS cabled multisensory network (Vancouver Island, Canada) deploys seafloor camera systems at several sites. Our objective in this study was to implement new automated image analysis protocols for the recognition and counting of benthic decapods (i.e., the galatheid squat lobster, Munida quadrispina), as well as for the evaluation of changes in bacterial mat coverage (i.e., Beggiatoa spp.), using a camera deployed in Saanich Inlet (103 m depth). For the counting of Munida we remotely acquired 100 digital photos at hourly intervals from 2 to 6 December 2009. In the case of bacterial mat coverage estimation, images were taken from 2 to 8 December 2009 at the same time frequency. The automated image analysis protocols for both study cases were created in MatLab 7.1. Automation for Munida counting incorporated the combination of both filtering and background correction (Median- and Top-Hat Filters) with Euclidean Distances (ED) on Red-Green-Blue (RGB...Continue Reading

References

Dec 17, 2005·IEEE Transactions on Pattern Analysis and Machine Intelligence·Ashok VeeraraghavanRama Chellappa
Jan 5, 2011·Frontiers in Bioscience (Landmark Edition)·Jacopo AguzziFrancesc Sarda

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Methods Mentioned

BETA
imaging techniques
biosensor
biosensors

Software Mentioned

RGBv
VENUS
Image J
MatLab
PLSDA
Munida

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