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This paper presents an exhaustive, extensive and detailed experimental assessment of different types of visual key-points in terms of robustness, stability and traceability, in images taken in marine areas densely colonized with Posidonia Oceanica (P.O.). This work has been focused mainly in two issues: a) evaluating the  capacity of several image color and contrast enhancing preprocessing techniques to increase the image quality and the number of stable features, and b) finding the pair feature detector/descriptor, from a wide range of different combinations, that maximizes the number of inlier correspondences in consecutive frames or frames that close a loop (images that overlap, taken at distant time instants, from different viewpoints or even with different environmental conditions). Conclusions extracted from both evaluations will affect directly the quality of visual odometers and/or the image registration processes involved in visual SLAM approaches

Hacia la Navegación Visual de un Vehículo Autónomo Submarino en Áreas con Posidonia Oceanica