No abstract

In some application fields, such as underwater archaeology or marine biology, there is the need to collect three-dimensional, close-range data from objects that cannot be removed from their site. In particular, 3D imaging techniques are widely employed for close-range acquisitions in underwater environment. In this work we have compared in water two 3D imaging techniques based on active and passive approaches, respectively, and whole-field acquisition. The comparison is performed under poor visibility conditions, produced in the laboratory by suspending different quantities of clay in a water tank. For a fair comparison, a stereo configuration has been adopted for both the techniques, using the same setup, working distance, calibration, and objects. At the moment, the proposed setup is not suitable for real world applications, but it allowed us to conduct a preliminary analysis on the performances of the two techniques and to understand their capability to acquire 3D points in presence of turbidity. The performances have been evaluated in terms of accuracy and density of the acquired 3D points. Our results can be used as a reference for further comparisons in the analysis of other 3D techniques and algorithms.

ABSTRACT:Recovering correct or at least realistic colors of underwater scenes is a very challenging issue for imaging techniques, since illumination conditions in a refractive and turbid medium as the sea are seriously altered. The need to correct colors of underwater images or videos is an important task required in all image-based applications like 3D imaging, navigation, documentation, etc. Many imaging enhancement methods have been proposed in literature for these purposes. The advantage of these methods is that they do not require the knowledge of the medium physical parameters while some image adjustments can be performed manually (as histogram stretching) or automatically by algorithms based on some criteria as suggested from computational color constancy methods. One of the most popular criterion is based on gray-world hypothesis, which assumes that the average of the captured image should be gray. An interesting application of this assumption is performed in the Ruderman opponent color space lαβ, used in a previous work for hue correction of images captured under colored light sources, which allows to separate the luminance component of the scene from its chromatic components. In this work, we present the first proposal for color correction of underwater images by using lαβ color space. In particular, the chromatic components are changed moving their distributions around the white point (white balancing) and histogram cutoff and stretching of the luminance component is performed to improve image contrast. The experimental results demonstrate the effectiveness of this method under gray-world assumption and supposing uniform illumination of the scene. Moreover, due to its low computational cost it is suitable for real-time implementation.

The integration of underwater 3D data captured by acoustic and optical systems is a promising technique in various applications such as mapping or vehicle navigation. It allows for compensating the drawbacks of the low resolution of acoustic sensors and the limitations of optical sensors in bad visibility conditions. Aligning these data is a challenging problem, as it is hard to make a point-to-point correspondence. This paper presents a multi-sensor registration for the automatic integration of 3D data acquired from a stereovision system and a 3D acoustic camera in close-range acquisition. An appropriate rig has been used in the laboratory tests to determine the relative position between the two sensor frames. The experimental results show that our alignment approach, based on the acquisition of a rig in several poses, can be adopted to estimate the rigid transformation between the two heterogeneous sensors. A first estimation of the unknown geometric transformation is obtained by a registration of the two 3D point clouds, but it ends up to be strongly affected by noise and data dispersion. A robust and optimal estimation is obtained by a statistical processing of the transformations computed for each pose. The effectiveness of the method has been demonstrated in this first experimentation of the proposed 3D opto-acoustic camera.

We propose a system to process multispectral scans of double-sided

ABSTRACT:In the field of 3D scanning, there is an increasing need for more accurate technologies to acquire 3D models of close range objects. Underwater exploration, for example, is very hard to perform due to the hostile conditions and the bad visibility of the environment. Some application fields, like underwater archaeology, require to recover tridimensional data of objects that cannot be moved from their site or touched in order to avoid possible damages. Photogrammetry is widely used for underwater 3D acquisition, because it requires just one or two digital still or video cameras to acquire a sequence of images taken from different viewpoints. Stereo systems composed by a pair of cameras are often employed on underwater robots (i.e. ROVs, Remotely Operated Vehicles) and used by scuba divers, in order to survey archaeological sites, reconstruct complex 3D structures in aquatic environment, estimate in situ the length of marine organisms, etc. The stereo 3D reconstruction is based on the triangulation of corresponding points on the two views. This requires to find in both images common points and to match them (correspondence problem), determining a plane that contains the 3D point on the object. Another 3D technique, frequently used in air acquisition, solves this point-matching problem by projecting structured lighting patterns to codify the acquired scene. The corresponding points are identified associating a binary code in both images. In this work we have tested and compared two whole-field 3D imaging techniques (active and passive) based on stereo vision, in underwater environment. A 3D system has been designed, composed by a digital projector and two still cameras mounted in waterproof housing, so that it can perform the various acquisitions without changing the configuration of optical devices. The tests were conducted in a water tank in different turbidity conditions, on objects with different surface properties. In order to simulate a typical seafloor, we used various concentrations of clay. The performances of the two techniques are described and discussed. In particular, the point clouds obtained are compared in terms of number of acquired 3D points and geometrical deviation.

No abstract

No abstract