Title
ECUHO1 (Edith Cowan University Halophila Ovalis 1)
Collection Type
Dataset
Upload Date
2019
School or Research Centre
School of Science
Contact
Please contact Syed Mohammed Shamsul Islam regarding access to this dataset.
Syed Mohammed Shamsul Islam: Shams.webmail@gmail.comDescription
ECUHO1 contains 2699 underwater 2D digital images of Halophila ovalis (a type of seagrass). Images are collected from both natural shallow shorelines and experimental laboratory setup.
Natural shorelines include Dampier reserve, Mandurah, shallow coastlines of Fremantle and Rottness Island, Coral Bay, Exmouth of Ningaloo area from North-Western Australia, Lucky Bay, Milyu, Pelican Point and Rockey Bay of Swan Canning area of WA. The experimental laboratory setup is situated at Edith Cowan College, Joondalup.
The whole dataset is labelled with expert annotation. The image file format is JPG and labelling was saved as XML files. The entire dataset is divided into a test set and a train set. In the annotation files (.csv) for test set and training set contains the following information:
Filename: Name of the Image file.
Width: Width of the whole image (pixel).
Height: Height of the whole image (pixel).
Class: Object Class of the image patch inside bounding box (bbox).
Xmin: Location of the bottom left corner of the bbox.
Ymin: Location of the top left corner of the bbox.
Xmax: Location of the bottom right corner of the bbox.
Ymax: Location of the top right corner of the bbox.
DOI
10.25958/5dd7566dfaabb
Research Activity Title
Seagrass Detection Using Deep Learning
Research Activity Description
The Research project was undertaken as a part of masters by research (J16). The project aimed to demonstrate the possibility and effectiveness of deep learning-based object detection techniques for seagrass detection from underwater images. Underwater seagrass (Halophila ovalis) images were collected from both natural shallow shorelines and ECU experimental facility. Collected images were labelled with expert advice. Finally, Faster R-CNN object detection framework with a range of deep neural network architectures has been trained with the dataset.
Start of data collection time period
2017
End of data collection time period
2019
Language
eng
Codes
Filename: Name of the Image file.
Width: Width of the whole image (pixel).
Height: Height of the whole image (pixel).
Class: Object Class of the image patch inside bounding box (bbox).
Xmin: Location of the bottom left corner of the bbox.
Ymin: Location of the top left corner of the bbox.
Xmax: Location of the bottom right corner of the bbox.
Ymax: Location of the top right corner of the bbox.
File Format(s)
JPG, XML
File Size
20 GB
Access Rights
metadata only record
Citation
Moniruzzaman, M., Islam, S. M., & Lavery, P. (2019). ECUHO1 (Edith Cowan University Halophila Ovalis 1). Edith Cowan University. http://dx.doi.org/10.25958/5dd7566dfaabb
Author Identifiers
MD Moniruzzaman
ORCID: 0000-0003-1130-7078