AUTOMATING THE MEASUREMENT OF RED CORAL IN SITU USING UNDERWATER PHOTOGRAMMETRY AND CODED TARGETS

A photogrammetry tool dedicated to the monitoring of red coral populations in situ has been developed by LSIS in Marseille (France). This tool is used to collect in an efficient and precise manner key data for the study of the population dynamics of red coral. In selected red coral populations, scuba-divers obtain a series of photographs from the permanent plots (about 2 m 2 ) on an annual basis. To facilitate the photographic sampling and measurements, the scuba-divers use a 20 x 20 cm quadrat to cover the permanent plots. The analysis of the photographs provides reliable measurements on colony sizes (basal diameter and maximum height), occurrence of breakage of colonies and the occurrence of necrosis. To minimize the divers' tasks during the acquisition phase, we opted for stereoscopic acquisition using a single device to easily adapt the measurement procedure to the scene configuration. The material is quite light, one camera and two electronic strobes and a simple procedure with two photographs taken for each site. To facilitate the measurement phase of colony sizes; the exploitation of photographs consists of four key steps: orientation, scaling, measurement of the characteristic points of coral colonies and result validation (checking measurement consistency to detect possible errors in measurement or interpretation). Since the context of the shooting can vary widely, dominant colors, contrast, etc. may often change. In order to have a stable and common reference in all photographs independently of the site, we decided to always include a quadrat in the scene which then will be used for the orientation and scaling phases. The automation of orientation and the lack of constraints to adapt the analytical technique to the features of each site offer the possibility to multiply field surveys and to measure hundreds of quadrats from several different populations in a very efficient manner. The measurement results are exported into a spreadsheet application and integrated into the biologists' workflow. The results obtained from different red coral populations displaying contrasting characteristics (small versus large colony sizes) are presented and discussed at the end of this article.

[1]  F. Sánchez,et al.  Photogrammetric quantitative study of habitat and benthic communities of deep Cantabrian Sea hard grounds. , 2009 .

[2]  P. Drap,et al.  Fine‐scale genetic structure and inferences on population biology in the threatened Mediterranean red coral, Corallium rubrum , 2010, Molecular ecology.

[3]  Euan S. Harvey,et al.  A Review of Underwater Stereo-Image Measurement for Marine Biology and Ecology Applications , 2009 .

[4]  Jun Rekimoto,et al.  Matrix: a realtime object identification and registration method for augmented reality , 1998, Proceedings. 3rd Asia Pacific Computer Human Interaction (Cat. No.98EX110).

[5]  A. Duester,et al.  Quantitative stereo imaging from the Autonomous Benthic Explorer (ABE) , 1999, Oceans '99. MTS/IEEE. Riding the Crest into the 21st Century. Conference and Exhibition. Conference Proceedings (IEEE Cat. No.99CH37008).

[6]  Jun Rekimoto,et al.  CyberCode: designing augmented reality environments with visual tags , 2000, DARE '00.

[7]  Julien Seinturier,et al.  Fusion réversible : application à l'information archéologique , 2002 .

[8]  Manolis I. A. Lourakis,et al.  SBA: A software package for generic sparse bundle adjustment , 2009, TOMS.

[9]  Julien Seinturier Fusion de connaissances : Applications aux relevés photogrammétriques de fouilles archéologiques sous-marines. (Knowledge Fusion : Applications to photogrammetric surveys of underwater archaeological excavations) , 2007 .

[10]  David Nister,et al.  Recent developments on direct relative orientation , 2006 .

[11]  Weon-Geun Oh,et al.  An analysis of the effect of different image preprocessing techniques on the performance of SURF: Speeded Up Robust Features , 2011, 2011 17th Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV).

[12]  Pierre Drap,et al.  Performances Analysis of Underwater Image Preprocessing Techniques on the Repeatability of SIFT and SURF Descriptors , 2012 .

[13]  Fan Xiao,et al.  What is the best fiducial? , 2002, The First IEEE International Workshop Agumented Reality Toolkit,.

[14]  P. Drap,et al.  Marine Protected Areas and the conservation of long-lived marine invertebrates: the Mediterranean red coral , 2010 .

[15]  David G. Lowe,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004, International Journal of Computer Vision.

[16]  Ivan Poupyrev,et al.  Virtual object manipulation on a table-top AR environment , 2000, Proceedings IEEE and ACM International Symposium on Augmented Reality (ISAR 2000).

[17]  Eric Foxlin,et al.  Circular data matrix fiducial system and robust image processing for a wearable vision-inertial self-tracker , 2002, Proceedings. International Symposium on Mixed and Augmented Reality.

[18]  Alastair R. Beresford,et al.  Cantag: an open source software toolkit for designing and deploying marker-based vision systems , 2006, Fourth Annual IEEE International Conference on Pervasive Computing and Communications (PERCOM'06).

[19]  Tom Drummond,et al.  Faster and Better: A Machine Learning Approach to Corner Detection , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[20]  J. Bythell,et al.  Three-dimensional morphometric measurements of reef corals using underwater photogrammetry techniques , 2001, Coral Reefs.

[21]  M. Shortis,et al.  A Review of Underwater Stereo-Image Measurement for Marine Biology and Ecology Applications , 2009 .

[22]  Gary A. Kendrick,et al.  Efficiently measuring complex sessile epibenthic organisms using a novel photogrammetric technique , 2006 .

[23]  Matthijs C. Dorst Distinctive Image Features from Scale-Invariant Keypoints , 2011 .

[24]  H. Madjidi,et al.  3-D photo-mosaicking of benthic environments , 2003, Oceans 2003. Celebrating the Past ... Teaming Toward the Future (IEEE Cat. No.03CH37492).

[25]  Mark Fiala,et al.  Designing Highly Reliable Fiducial Markers , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[26]  Michael Rohs,et al.  USING CAMERA-EQUIPPED MOBILE PHONES FOR INTERACTING WITH REAL-WORLD OBJECTS , 2004 .