Use of seafloor stereo-images to validate automatic classification of benthic habitats
Here we present a technique for automatic classification of seafloor data collected during the 2012 HABCAMV4 cruises led by NOAA, UNH and WHOI a federally funded long term project part of the annual NOAA seascallop’s survey.
This project will analyze a unique data set that includes simultaneously collected data such as:
- Hi-resolution multi-beam (digital bathymetry and backscatter intensity)
- Seafloor stereo image data (e.g. species and substrate)
- Environmental parameters (e.g. temperature, salinity, water turbidity)
The analysis will be based on an unsupervised spatial clustering (K-means) of a combination of several predictors like morphological features (curvature, rugosity, fractal index, surface area) and backscatter intensity.
The final results will be validated by analyzing the identified classes with a randomly selected subset of underwater photographs for each class.
The seafloor classification map produced is then used as a preliminary "habitat classification" for further classification. It can be reused to define selection-criteria for the underwater images used by automatic classifier or by manual image annotator tools.
Results from this project will also help to define new survey track-lines prior to and during HABCAM surveys.
Journal or Conference Title
May 5 - May 9, 2014
Lorne, Victoria, Australia
Di Stefano, Massimo and Mayer, Larry A., "Use of seafloor stereo-images to validate automatic classification of benthic habitats" (2014). Center for Coastal and Ocean Mapping. 866.
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