The ability to associate labels to colors is very natural for human beings. Though, this apparently simple task hides very complex and still unsolved problems, spreading over many different disciplines ranging from neurophysiology to psychology and imaging. In this paper, we propose a discrete model for computational color categorization and naming. Starting from the 424 color specimens of the OSA-UCS set, we propose a fuzzy partitioning of the color space. Each of the 11 basic color categories identified by Berlin and Kay is modeled as a fuzzy set whose membership function is implicitly defined by fitting the model to the results of an ad hoc psychophysical experiment (Experiment 1). Each OSA-UCS sample is represented by a feature vector whose components are the memberships to the different categories. The discrete model consists of a three-dimensional Delaunay triangulation of the CIELAB color space which associates each OSA-UCS sample to a vertex of a 3D tetrahedron. Linear interpolation is used to estimate the membership values of any other point in the color space. Model validation is performed both directly, through the comparison of the predicted membership values to the subjective counterparts, as evaluated via another psychophysical test (Experiment 2), and indirectly, through the investigation of its exploitability for image segmentation. The model has proved to be successful in both cases, providing an estimation of the membership values in good agreement with the subjective measures as well as a semantically meaningful color-based segmentation map.
In this article, we present an approach for a deep-sea survey based on photogrammetry using a remotely operated underwater vehicle (ROV). A hybrid technique gives us real-time results, sufficient for piloting the ROV from the surface vessel and ensuring a uniform coverage of the site, as well as recording high-definition images using an onboard computer that will later provide a survey with millimetric precision. The measurements are made without any contact and are noninvasive. The time required on-site is minimal and corresponds to the time needed by the ROV to cover the zone. With the photos taken at a frame rate synchronized at 10Hz, the ROV required 2 hours to perform the experiment presented in this article: the survey of the Roman shipwreck Cap Bénat 4 , at a depth of 328m. The approach presented in this work was developed in the scope of the ROV 3D project. This project, financed by the Fond Unique Interministériel (FUI) for 3 years, brings together two industrial partners and a research laboratory. Companie Maritime d’Expertise (COMEX) coordinated this project.
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