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Proceedings Paper

Posidonia oceanica recognition using context points
Author(s): Mostafa Hatimi; Marc Salotti; Vanina Pasqualini; Christine Pergent-Martini
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Paper Abstract

We address the problem of identifying Posidonia oceanica areas in multispectral aerial seacoast images. P. oceanica is a marine phanerogam endemic to the Mediterranean. Several diving have been performed in order to get information at specific locations. At each point (context point), a measure of depth has been made and the presence or absence of P. oceanica has been noticed. The first difficulty is to separate the sea from the coast. We propose a least square technique to distinguish sea points from the others. Then, the major problem is that the color of P. oceanica in shallow water is the same as the color of the sand in deeper water. We proceed in two steps: for each point of the sea, the three closer context points are used to compute a depth map. Then, the sea points are split in three categories, with respect to the depth. A classification is learned from the context points, and the final segmentation is obtained by generalizing to all points of the sea.

Paper Details

Date Published: 17 November 1995
PDF: 8 pages
Proc. SPIE 2579, Image and Signal Processing for Remote Sensing II, (17 November 1995); doi: 10.1117/12.226854
Show Author Affiliations
Mostafa Hatimi, Univ. des Sciences (France)
Marc Salotti, Univ. des Sciences (France)
Vanina Pasqualini, Univ. des Sciences (France)
Christine Pergent-Martini, Univ. des Sciences (France)


Published in SPIE Proceedings Vol. 2579:
Image and Signal Processing for Remote Sensing II
Jacky Desachy, Editor(s)

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