Abstract:The recent decline in the condition of coral reef communities worldwide has fueled the need to develop innovative assessment tools to document coral abundance and distribution rapidly and effectively. While most monitoring programs rely primarily on data collected in situ by trained divers, digital photographs and video are used increasingly to extract ecological indicators, provide a permanent visual record of reef condition, and reduce the time that divers spend underwater. In this study, we describe the dev… Show more
“…Ewing et al 1967, Torlegård & Lundalv 1974, Corliss et al 1979, Gutt et al 1996, Clarke 2003, Bailey et al 2007, Lirman et al 2007, Bowen et al 2009, Shortis et al 2009). This includes the use of manual image equipment (digital still and video cameras) operated by SCUBA divers and remote imaging technology in deep waters, such as remotely operated vehicles (ROVs), autonomous underwater vehicles (AUVs), landers equipped with cameras for long-term observations and a variety of other still camera systems.…”
An important aspect of marine research is to quantify the areal coverage of benthic communities. It is technically feasible to efficiently obtain images of marine environments at different depths and benthic habitats over large spatial and temporal scales. Currently, there is a large and growing library of digital images to analyze, representing a valuable benthic ecological archive. Benthic coverage is the basis of studies on biodiversity, characterization of communities and evaluation of changes over temporal and spatial scales. However, there is still a lack of automatic or semi-automatic analytical methods for deriving ecologically relevant data from these images. We introduce a software program named Seascape to obtain semi-automatically segmented images (patch outlines) from underwater photographs of benthic communities, where each individual patch (species/categories) is routinely associated to its area cover and perimeter. Seascape is an analog to the classical and better known discipline of landscape ecology approach, which focuses on the concept that communities can be observed as a patch mosaic at any scale. The process starts with a hierarchical segmentation, using a color space criteria adapted to the problem of segmenting complex benthic images. As an endproduct, we obtain a set of images segmented into classified homogenous regions at different resolution levels (hierarchical segmentation). To illustrate the versatility and capacity of Seascape, we analyzed 4 digital images from different habitats and depths: coral reefs (Pacific Ocean), coralligenous communities (NW Mediterranean Sea), deep-water coral reefs (NW Mediterranean Sea) and the Antarctic continental shelf (Weddell Sea). The development of this semi-automatic outline tool and its use for classification constitute an important step forward in the analysis and processing time of underwater seabed images at any scale.
“…Ewing et al 1967, Torlegård & Lundalv 1974, Corliss et al 1979, Gutt et al 1996, Clarke 2003, Bailey et al 2007, Lirman et al 2007, Bowen et al 2009, Shortis et al 2009). This includes the use of manual image equipment (digital still and video cameras) operated by SCUBA divers and remote imaging technology in deep waters, such as remotely operated vehicles (ROVs), autonomous underwater vehicles (AUVs), landers equipped with cameras for long-term observations and a variety of other still camera systems.…”
An important aspect of marine research is to quantify the areal coverage of benthic communities. It is technically feasible to efficiently obtain images of marine environments at different depths and benthic habitats over large spatial and temporal scales. Currently, there is a large and growing library of digital images to analyze, representing a valuable benthic ecological archive. Benthic coverage is the basis of studies on biodiversity, characterization of communities and evaluation of changes over temporal and spatial scales. However, there is still a lack of automatic or semi-automatic analytical methods for deriving ecologically relevant data from these images. We introduce a software program named Seascape to obtain semi-automatically segmented images (patch outlines) from underwater photographs of benthic communities, where each individual patch (species/categories) is routinely associated to its area cover and perimeter. Seascape is an analog to the classical and better known discipline of landscape ecology approach, which focuses on the concept that communities can be observed as a patch mosaic at any scale. The process starts with a hierarchical segmentation, using a color space criteria adapted to the problem of segmenting complex benthic images. As an endproduct, we obtain a set of images segmented into classified homogenous regions at different resolution levels (hierarchical segmentation). To illustrate the versatility and capacity of Seascape, we analyzed 4 digital images from different habitats and depths: coral reefs (Pacific Ocean), coralligenous communities (NW Mediterranean Sea), deep-water coral reefs (NW Mediterranean Sea) and the Antarctic continental shelf (Weddell Sea). The development of this semi-automatic outline tool and its use for classification constitute an important step forward in the analysis and processing time of underwater seabed images at any scale.
“…4.7). This second dataset was composed of 30 images, extracted from an underwater image sequence acquired by a Phantom 500 ROV during a survey in Andros, in the Bahamas [66]. The results for the second dataset are summarised in Table 4.3.…”
Section: Resultsmentioning
confidence: 99%
“…1.2 and 1.3). Many scientifically interesting sites are located in areas which are nearly flat, such as the coral reefs in the Florida Reef Tract [66]. We consider in this thesis cases where the 3D relief of the scene is negligible compared to the altitude of the robot, and the seafloor is therefore assumed to be and is modelled as a planar scene 1 .…”
Section: Objectivesmentioning
confidence: 99%
“…Therefore, mosaicing techniques are needed to create high-resolution maps of the surveyed area using a large number of acquired images and to get a global perspective of the underwater terrain [45,89,109,60,94,96]. Thus, robotic exploration with the aim of constructing photo-mosaics is becoming a common requirement in geological [112,33] and archaeological surveys [36], mapping [59], ecology studies [56,66,89], environmental damage assessment [41,65] and temporal change detection [29]. Owing to the rapid development in data acquisition platforms, there is an increasing need for large-scale image mosaicing methods.…”
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PhD
AbstractLarge scale image mosaicing methods are in great demand among scientists who study different aspects of the seabed, and have been fostered by impressive advances in the capabilities of underwater robots in gathering optical data from the seafloor. Cost and weight constraints mean that low-cost Remotely operated vehicles (ROVs) usually have a very limited number of sensors. When a low-cost robot carries out a seafloor survey using a downlooking camera, it usually follows a predefined trajectory that provides several non time-consecutive overlapping image pairs. Finding these pairs (a process known as topology estimation) is indispensable to obtaining globally consistent mosaics and accurate trajectory estimates, which are necessary for a global view of the surveyed area, especially when optical sensors are the only data source.This thesis presents a set of consistent methods a...
“…The mosaic building process is detailed in [16,17]. It starts by searching for correspondences between consecutive images (referred to as consecutive image registration) to determine their homographies.…”
Starting in January 2009, the RAUVI (Reconfigurable Autonomous Underwater Vehicle for Intervention Missions) project is a three years coordinated research action funded by the Spanish Ministry of Research and Innovation. In this paper, the state of progress after two years of continuous research is reported. As a first experimental validation of the complete system, a Search & Recovery problem is addressed, consisting of finding and recovering a flight data recorder placed at an unknown position at the bottom of a water tank. An overview of the techniques used to successfully solve the problem in an autonomous way is provided. The obtained results are very promising and are the first step toward the final test in shallow water at the end of 2011.
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