2. Underwater positioning and mapping for ship hull inspection
2.1.5. Vision-based systems
2.1.5.1. Monocular and stereo cameras
In contrast to acoustic underwater camera or imaging sonars, respectively (see sec- tion 2.1.4.3), optical cameras provide a rich set of information, such as a high resolution, a high accuracy, a high sampling rate and the ability to detect colours. On the other hand, the absorption and scattering of light rays by particles or water molecules [23] results in poor contrast, distance dependent and wavelength dependent attenuation of light and noise. The attenuation of sun light may require additional lighting, which can increase the backscattering of light by suspended particles in turbid water. Dynamic lighting conditions of shadow patterns cast by the water surface (caustic) represent another challenge for the feature tracking with monocular cameras, but can also be ad- vantageous due to additional texture information if a stereo camera is used [24, 25, 26]. Water bubbles or aquatic snow represent some further challenges. In terms of ship hull inspection, the turbidity of water and the texture characteristic of the hull all impact the camera’s ship hull inspection capability.
Monocular cameras and stereo cameras can be used to reconstruct the scene captured. Monocular cameras achieve 3D reconstruction by structure from motion, where a scene is captured from different views. In in-air structure from motion, monocular cameras are unable to determine the scale of the scene captured. To date, it has not been shown for monocular underwater cameras, yet, that a reconstruction of the scale is possible. On the other hand, stereo cameras enable the direct measurement of the scale and the reconstruction from a single camera pose.
2.1.5.2. Structured light, Time-of-flight and Lidar
Another approach for hull relative navigation was described in [27]. In this paper, three laser pointers and a camera were deployed. The camera measured the distances to the three laser points and thus also enabled the measurement of the orientation to the hull. This approach is, for example, useful for underwater vehicles to keep a fixed distance to ship hulls. A similar approach was proposed in [28].
The sensor system required for ship hull scanning needs to be able to track and to reconstruct ship hull surfaces. Active, structured light systems are advantageous to passive optical camera systems in reconstructing textureless areas and can increase the visibility in turbid water [29]. Various structured light systems using only few laser points [30, 27], laser lines [31] or more sophisticated binary projected patterns [29] are
known.
Only few publications reported on using the popular in-air structured light system, Kinect, underwater [32]. The experiments of Ozsvald [32], in which an in-air Kinect sensor was used to reconstruct submerged objects, showed the limited capability to reconstruct underwater objects at larger distances. In the following paragraphs, we evaluate numerous additional limitations of Kinect for use underwater.
Proposed evaluation of Kinect, Time-of-flight cameras and Lidar for ship hull in- spection Kinect uses infrared light with a wavelength of λ= 830 nm, which is strongly attenuated in water. Considering a submerged Kinect sensor embedded in an underwa- ter housing and assuming for simplicity pure sea water and full light reflection at the ship hull, the maximum remaining light signal strength, S, using the minimal specified viewing distance of z = 80 cm results to S = e−2.07·2·z = 3.6% and drops to ∼0.03 % for z = 2 m (λ = 800 nm) [23]. In all cases, S is very low and can probably not be sensed by Kinect. To solve this problem, a modification of the Kinect hardware would be necessary, in which the near infrared light source could be replaced by light of shorter wavelength, such as blue light.
The refraction of light at the port of the underwater housing leads to a distance dependent 3D distortion resulting in a distorted structured light pattern and a distortion of the reconstructed scene. It is unlikely that the in-hardware implemented pattern recognition and reconstruction algorithms of the Kinect sensor are able to handle these types of distortion or that a correction of the distortions is easily possible.
The horizontal FOV (HFOV) of 57°of the Kinect sensor is also relatively small. Light refraction at the flat port of an underwater housing reduces the (horizontal) field of view in water HFOVw = 2 sin−1 nasin(HFOV2 ) nw ! , (2.1)
to ∼42° (Snell’s law), where na = 1 and nw = 1.33 denote the approximate indices of refraction of air and water.
Another clear disadvantage of the Kinect sensor is the minimum viewing distance, which is too large for ship hull tracking. The minimum viewing distance of the in- air Kinect sensor amounts to ∼80 cm. Apart from the strong light attenuation, as described above, the camera of the Kinect sensor needs to be close to the hull in order to recognise and track the textures of the hull. Under more challenging conditions, such
2.2. Ship hull inspection systems
as turbid water, the maximum ship hull distance is even more restricted. The minimum viewing distance of the Kinect sensor is increased by the smaller FOV, and thus further aggravates the minimum distance problem.
Kinect is an active light system. In turbid water, it suffers from backscattered light emitted by the projector. To minimise backscattering, the projector needs to be placed far from the camera what causes shadows, and so parts of the camera image are not fully covered by the projected pattern. In classic underwater photography, two spot lights on the opposite sites of the camera are used to reduce this effect. Something similar, such as two pattern projectors, would be also necessary for the in-water Kinect case. Another problem for the pattern recognition algorithm would be the blur caused by the forward scattering of light.
Similar to Kinect, time-of-flight (ToF) cameras and light detection and ranging sys- tems (Lidars) are generally based on infrared light and share similar disadvantages, such as strong near infrared light attenuation, backscattering and blur by forward scattering. The resolution of ToF system is also relatively low at about 200 ×200 px. Necessary modifications of these latter systems would be even more complex than modifications needed for the Kinect sensor.