Segmentation through patch classification: A neural network approach to detect Posidonia oceanica in underwater images [preprint]

Abstract

[eng] This paper focuses on the detection of Posidonia oceanica in underwater images. The input image is split into a set of patches that are classified as depicting Posidonia or not. Two different Neural Networks are proposed to perform the classification. A region growing algorithm able to accurately detect the contours of the Posidonia oceanica from the output of the classifier is also described. The experimental results, performed using images gathered in coastal areas of Mallorca, show that our proposal surpasses previous studies based on Machine Learning, being superior in some cases to Deep Learning methods. The advantages in terms of computational requirements, which are crucial in underwater robotics, are also highlighted.