The University of Southampton
University of Southampton Institutional Repository

Comparison of region proposal methods for marine holograms

Comparison of region proposal methods for marine holograms
Comparison of region proposal methods for marine holograms

A novel technique to analyse deep-sea particles using digital holography (DH) and Raman spectroscopy (RS) is currently being developed. Since RS requires long measurement periods to provide reliable results in water, a flow control system is necessary to trap particles in the instrument. One way in which this can be achieved is to control the flow based on particles detected in DH images that can be rapidly acquired. In this paper, we explore the possibility of using a region proposal technique to detect possible object regions in holographic images. A model using a support vector machine (SVM) and the histogram of oriented gradients (HoG) has been developed. After being trained on a dataset consisting of 1589 particle and 947 non-particle regions, the model was tested on an image set of 10 independent images with 175 positive regions. It took around 0.5 second to analyse a 1000 * 760 image on average, and the proposed regions had a maximum overlap of 59.3% on average compared to the ground truth. The speed and accuracy of this method was also compared against 7 other possible methods. Amongst the tested methods, SVM was shown to provide the best solution for real-time region proposal on digital holograms. The results in this paper show that the SVM model using HoG features is a good solution to implement region proposal on digital holograms.

digital holography, marine holograms, region proposal, support vector machine
IEEE
Liu, Zonghua
76b789cb-cddf-49c2-89dd-ca8a56997486
Takahashi, Tomoko
937057f6-8e83-4a7f-b11f-b549c94afdf6
Thevar, Thangavel
06bf7cc7-cf72-422e-a77b-9d1f55a2b3b1
Lindsay, Dhugal
95b74b27-090f-4b4c-9b2d-892dbc8e6f54
Burns, Nicholas
ec00597b-5a8b-4af1-8a42-252be6c61438
Watson, John
5b87c996-09db-49f2-b114-404dcc418915
Thornton, Blair
8293beb5-c083-47e3-b5f0-d9c3cee14be9
Liu, Zonghua
76b789cb-cddf-49c2-89dd-ca8a56997486
Takahashi, Tomoko
937057f6-8e83-4a7f-b11f-b549c94afdf6
Thevar, Thangavel
06bf7cc7-cf72-422e-a77b-9d1f55a2b3b1
Lindsay, Dhugal
95b74b27-090f-4b4c-9b2d-892dbc8e6f54
Burns, Nicholas
ec00597b-5a8b-4af1-8a42-252be6c61438
Watson, John
5b87c996-09db-49f2-b114-404dcc418915
Thornton, Blair
8293beb5-c083-47e3-b5f0-d9c3cee14be9

Liu, Zonghua, Takahashi, Tomoko, Thevar, Thangavel, Lindsay, Dhugal, Burns, Nicholas, Watson, John and Thornton, Blair (2020) Comparison of region proposal methods for marine holograms. In 2020 Global Oceans 2020: Singapore - U.S. Gulf Coast. IEEE.. (doi:10.1109/IEEECONF38699.2020.9389216).

Record type: Conference or Workshop Item (Paper)

Abstract

A novel technique to analyse deep-sea particles using digital holography (DH) and Raman spectroscopy (RS) is currently being developed. Since RS requires long measurement periods to provide reliable results in water, a flow control system is necessary to trap particles in the instrument. One way in which this can be achieved is to control the flow based on particles detected in DH images that can be rapidly acquired. In this paper, we explore the possibility of using a region proposal technique to detect possible object regions in holographic images. A model using a support vector machine (SVM) and the histogram of oriented gradients (HoG) has been developed. After being trained on a dataset consisting of 1589 particle and 947 non-particle regions, the model was tested on an image set of 10 independent images with 175 positive regions. It took around 0.5 second to analyse a 1000 * 760 image on average, and the proposed regions had a maximum overlap of 59.3% on average compared to the ground truth. The speed and accuracy of this method was also compared against 7 other possible methods. Amongst the tested methods, SVM was shown to provide the best solution for real-time region proposal on digital holograms. The results in this paper show that the SVM model using HoG features is a good solution to implement region proposal on digital holograms.

This record has no associated files available for download.

More information

Published date: 5 October 2020
Additional Information: Publisher Copyright: © 2020 IEEE. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.
Venue - Dates: 2020 Global Oceans: Singapore - U.S. Gulf Coast, OCEANS 2020, , Biloxi, United States, 2020-10-05 - 2020-10-30
Keywords: digital holography, marine holograms, region proposal, support vector machine

Identifiers

Local EPrints ID: 453542
URI: http://eprints.soton.ac.uk/id/eprint/453542
PURE UUID: f862f3d3-88bc-47ed-ac50-f14194c66864

Catalogue record

Date deposited: 19 Jan 2022 17:42
Last modified: 16 Mar 2024 14:44

Export record

Altmetrics

Contributors

Author: Zonghua Liu
Author: Tomoko Takahashi
Author: Thangavel Thevar
Author: Dhugal Lindsay
Author: Nicholas Burns
Author: John Watson
Author: Blair Thornton

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×