Abstract
In this article we present a new approach for object recognition in a robotic underwater context. Color is an attractive feature because of its simplicity and its robustness to scale changes, object positions and partial occlusions. Unfortunately, in the underwater medium, the colors are modified by attenuation and are not constant with the distance. To perform a color-based recognition of an object, we develop an algorithm robust with respect to the attenuation which takes into account the light modification during its path between the light source and the camera. Therefore, a given underwater object can be identified in an image by detecting all the colors compatible with its prior known color. Our method is fast, robust and needs a very few computers resources. We successfully used it when experimenting in the sea using a system we built. It is suitable for robotic applications where computers resources are limited and shared between various embedded devices. This novel concept enables the use of the color in many applications such as target interception, object tracking or obstacle detection.
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References
Ahlen J (2005) Color correction of underwater images using spectral data. PhD dissertation, Uppsala University, Centre for Image Analysis
Ahlen J, Bengtsson E, Lindell T (2003) Color correction of underwater images based on estimation of diffuse attenuation coefficients. In: Proceedings of PICS conference
Bazeille S, Quidu I, Jaulin L (2007) Identification of underwater man-made object using a colour criterion. In: Proceedings of the Institute of acoustics, vol 29
Chambah M, Semani D, Renouf A, Courtellemont P, Rizzi A (2003) Underwater color constancy: enhancement of automatic live fish recognition. In: Proceedings of SPIE, vol 5293, pp 157–168
Dudek G et al (2005) A visually guided swimming robot. In: Proceedings of IEEE international conference on intelligent robots and systems, pp 3604–3609
Duntley SQ (1963) Light in the sea. J Opt Soc Am
Foresti GL, Gentili S (2000) A vision based system for object detection in underwater image. In: Proceedings of IEEE international conference on computer vision and pattern recognition, vol 14, pp 544–549
Gevers T, Smeulders AWM (1999) Color based object recognition. Patt Recogn 32: 453–464
Gordon HR (1989) Can the lambert-beer law be applied to the diffuse attenuation coefficient of ocean water. Limnol Oceanogr 34
Jerlov NG (1976) Marine optics. Elsevier oceanography series. Elsevier, New York
Klinker GJ, Shafer SA, Kanade T (1990) A physical approach to color image understanding. Int J Comput Vis 4: 7–38
Kravtchenko V (1999) Tracking color objects in real time. PhD dissertation, University of British Columbia
Mishra DR, Narumalani S, Rundquist D, Lawson M (2005) Characterizing the vertical diffuse attenuation coefficient for downwelling irradiance in coastal waters. ISPRS J Photogram Rem Sens 60: 48–64
Obdrzalek S, Matas J, Chum O (2003) On the interaction between object recognition and colour constancy. In: Proceedings of IEEE international conference on computer vision (ICCV03)
Olmos-Antillon AT (2002) Detecting underwater man-made objects in unconstrained video image. PhD dissertation, Heriot Watt University, Department of Computing and Electrical Engineering
Petillot Y, Ruiz IT, Lane DM (2001) Underwater vehicle obstacle avoidance and path planning using a multi-beam forward looking sonar. IEEE J Ocean Eng 26: 240–251
Pickard GL, Emery WJ (1990) Descriptive physical oceanography: an introduction, 5th edn. Pergamon Press, Oxford
Pizarro O, Singh H (2003) Toward large-area mosaicing for underwater scientific applications. Robotics Sci Syst VI 28: 651–672
Reed S, Petillot Y, Bell J (2003) An automatic approach to the detection and extraction of mine features in sidescan sonar. IEEE J Ocean Eng 28: 90–105
Sattar J, Giguere P, Dudek G, Prahacs C (2005) A visual servoing system for an aquatic swimming robot. In: Proceedings of IEEE international conference on intelligent robots and systems, pp 1483–1488
Schechner YY, Karpel N (2004) Clear underwater vision. In: Proceedings of IEEE international conference on computer vision and pattern recognition, vol 1, pp 536–543
Semani D, Chambah M, Courtellemont P (2005) Processing of underwater color images applied to live aquarium videos. Int J Robotics Autom (IJRA) 20: 123–130
Skaff S, Clark JJ, Rekleitis I (2008) Estimating surface reflectance spectra for underwater color vision. In: Proceedings of the British machine vision conference, Leeds, UK, vol 2, pp 1015–1024
Stavn RH (1988) Lambert-beer law in ocean waters: optical properties of water and of dissolved/suspended material, optical energy budgets. Appl Optic 27: 222–231
Sural S, Qian G, Pramanik S (2002) Segmentation and histogram generation using the hsv color space for image retrieval. In: Proceedings of IEEE international conference on image processing, vol 2, pp 589–592
Vasilescu I, Detweiler C, Rus D (2010) Color-accurate underwater imaging using perceptual adaptive illumination. Robotics Sci Syst 6
Walther D, Edgington DR, Koch C (2004) Detection and tracking of objects in underwater video. IEEE Comput Vis Pattern Recogn 1: 544–549
Yamashita A, Fujii M, Kaneko T (2007) Color registration of underwater of images for underwater sensing with consideration of light attenuation. In: Proceedings of IEEE international conference on robotics and automation, Roma, pp 4570–4575
Zingaretti P, Zanoli SM (1998) Robust real-time detection of an underwater pipeline. Eng Appl Artif Intell 11: 257–268
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Bazeille, S., Quidu, I. & Jaulin, L. Color-based underwater object recognition using water light attenuation. Intel Serv Robotics 5, 109–118 (2012). https://doi.org/10.1007/s11370-012-0105-3
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DOI: https://doi.org/10.1007/s11370-012-0105-3