Perspectives in visual imaging for marine biology and ecology: from acquisition to understanding

Durden J, Schoening T, Althaus F, et al. Perspectives in Visual Imaging for Marine Biology and Ecology: From Acquisition to Understanding. In: Hughes RN, Hughes DJ, Smith IP, Dale AC, eds. Oceanography and Marine Biology: An Annual Review. 54. Boca Raton: CRC Press; 2016: 1-72

Underwater Imaging and Photography

The problem and various techniques for underwater imaging have been reviewed. The effect of various design parameters like pulse shape and duration,etc. has been brought out. System design considerations for underwater photography have also been discussed

Baited remote underwater video survey of reef fish in the Stilbaai marine protected area, with an assessment of monitoring requirements

Includes abstract.Includes bibliographical references.Long-term monitoring of changes in species abundance and community composition within marine protected areas (MPAs) is essential to assess whether conservation goals are being reached. The costs, logistics and sampling biases inherent to traditional monitoring methods limit sustainable monitoring in all MPAs along the South African coastline. Baited remote underwater video (BRUV) technology offers non-extractive monitoring with lower labour and cost requirements, whilst eliminating inter-observer variability and increasing statistical power. Species richness and relative abundance were assessed employing BRUV technology in the Stilbaai MPA in the Western Cape, South Africa. ... [The] result corroborated findings from traditional underwater visual census (UVC) and controlled angling surveys, confirming BRUV technology as a sound monitoring tool

Robotic Detection and Estimation of Single Scuba Diver Respiration Rate from Underwater Video

Human respiration rate (HRR) is an important physiological metric for diagnosing a variety of health conditions from stress levels to heart conditions. Estimation of HRR is well-studied in controlled terrestrial environments, yet robotic estimation of HRR as an indicator of diver stress in underwater for underwater human robot interaction (UHRI) scenarios is to our knowledge unexplored. We introduce a novel system for robotic estimation of HRR from underwater visual data by utilizing bubbles from exhalation cycles in scuba diving to time respiration rate. We introduce a fuzzy labeling system that utilizes audio information to label a diverse dataset of diver breathing data on which we compare four different methods for characterizing the presence of bubbles in images. Ultimately we show that our method is effective at estimating HRR by comparing the respiration rate output with human analysts

Automated Image Analysis for the Detection of Benthic Crustaceans and Bacterial Mat Coverage Using the VENUS Undersea Cabled Network

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) channels. The Scale-Invariant Feature Transform (SIFT) features and Fourier Descriptors (FD) of tracked objects were then extracted. Animal classifications were carried out with the tools of morphometric multivariate statistic (i.e., Partial Least Square Discriminant Analysis; PLSDA) on Mean RGB (RGBv) value for each object and Fourier Descriptors (RGBv+FD) matrices plus SIFT and ED. The SIFT approach returned the better results. Higher percentages of images were correctly classified and lower misclassification errors (an animal is present but not detected) occurred. In contrast, RGBv+FD and ED resulted in a high incidence of records being generated for non-present animals. Bacterial mat coverage was estimated in terms of Percent Coverage and Fractal Dimension. A constant Region of Interest (ROI) was defined and background extraction by a Gaussian Blurring Filter was performed. Image subtraction within ROI was followed by the sum of the RGB channels matrices. Percent Coverage was calculated on the resulting image. Fractal Dimension was estimated using the box-counting method. The images were then resized to a dimension in pixels equal to a power of 2, allowing subdivision into sub-multiple quadrants. In comparisons of manual and automated Percent Coverage and Fractal Dimension estimates, the former showed an overestimation tendency for both parameters. The primary limitations on the automatic analysis of benthic images were habitat variations in sediment texture and water column turbidity. The application of filters for background corrections is a required preliminary step for the efficient recognition of animals and bacterial mat patches

Selected Papers from the 2018 IEEE International Workshop on Metrology for the Sea

This Special Issue is devoted to recent developments in instrumentation and measurement techniques applied to the marine field. ¶The sea is the medium that has allowed people to travel from one continent to another using vessels, even today despite the use of aircraft. It has also been acting as a great reservoir and source of food for all living beings. However, for many generations, it served as a landfill for depositing conventional and nuclear wastes, especially in its deep seabeds, and we are assisting in a race to exploit minerals and resources, different from foods, encompassed in it. Its health is a great challenge for the survival of all humanity since it is one of the most important environmental components targeted by global warming. ¶ As everyone may know, measuring is a step that generates substantial knowledge about a phenomenon or an asset, which is the basis for proposing correct solutions and making proper decisions. However, measurements in the sea environment pose unique difficulties and opportunities, which is made clear from the research results presented in this Special Issue

The copepod Calanus spp. (Calanidae) is repelled by polarized light

Both attraction and repulsion from linearly polarized light have been observed in zooplankton. A dichotomous choice experiment, consisting of plankton light traps deployed in natural waters at a depth of 30 m that projected either polarized or unpolarized light of the same intensity, was used to test the hypothesis that the North Atlantic copepod, Calanus spp., is linearly polarotactic. In addition, the transparency of these copepods, as they might be seen by polarization insensitive vs. sensitive visual systems, was measured. Calanus spp. exhibited negative polarotaxis with a preference ratio of 1.9:1. Their transparency decreased from 80% to 20% to 30% in the unpolarized, partially polarized, and electric (e-) vector orientation domains respectively - that is, these copepods would appear opaque and conspicuous to a polarization-sensitive viewer looking at them under conditions rich in polarized light. Since the only difference between the two plankton traps was the polarization cue, we conclude that Calanus spp. are polarization sensitive and exhibit negative polarotaxis at low light intensities (albeit well within the sensitivity range reported for copepods). We hypothesize that Calanus spp. can use polarization vision to reduce their risk of predation by polarization-sensitive predators and suggest that this be tested in future experiments