Automatic classification of deep benthic habitats: detection of microbial mats and siboglinid polychaete fields from optical images on the Hakon Mosby Mud Volcano

被引：0

作者：

Chailloux, C. ^{[1
]}

Allais, A. G. ^{[2
]}

Simeoni, P. ^{[2
]}

Olu, K. ^{[1
]}

机构：

[1] Ifremer Brest, Lab Environm Profond, Dept Etud Ecosyst Profonds, BP 70, F-29280 Plouzane, France

[2] Ifremer Toulon, Serv Positionnement Robot Acoustique Optique, Dept Syst sous Marin, F-83507 La Seyne sur Mer, France

来源：

OCEANS 2008, VOLS 1-4 | 2008年

关键词：

Classification; watershed; region growing; mutual information; texture analysis; bacterial mats; siboglinid polychaete;

D O I：

暂无

中图分类号：

U6 [水路运输]; P75 [海洋工程];

学科分类号：

0814 ; 081505 ; 0824 ; 082401 ;

摘要：

While many seafloor surveys provide a growing number of data, only few automatic techniques are developed to analyze images. This study is interested in the automatic detection and quantification of microbial mats and field of siboglinid polychaete (tubeworm) colonizing the seafloor of the deep-sea Hakon Mosby Mud Volcano surveyed by ROV. Three algorithms are developed to segment the high resolution optical images of the seafloor which apply a watershed transformation coupled with a region growing technique, or a similarity measure operated with a region growing technique, or a texture analysis used with the Kullback-Leibler divergence. The results are compared through the score of a classification ratio estimated with a human-made classification.

引用

页码：68 / +

页数：2