The Performance Assessment of Curve Fitting Tools of Underwater Object with Glass Condition Using Stereo Vision
[1]
Shadi Mahmoodi Khaniabadi, School of Electrical and Electronic, University Sains Malaysia, Nibong Tebal, Pulau Pinang, Malaysia.
[2]
Ali Khalili Mobarakeh, Department of Mechanical Engineering, University of Málaga, Doctor Ortiz Ramos, Malaga, Spain.
[3]
Saba Nazari, School of Electrical and Electronic, University Sains Malaysia, Nibong Tebal, Pulau Pinang, Malaysia.
[4]
Rana Sabouni Tabari, Department of Material Science and Engineering, Sharif University of Technology, Tehran, Iran.
[5]
Azar Golshahi Porshokoh, Department of Material Science and Engineering, Sharif University of Technology, Tehran, Iran.
[6]
Abolfazl Zargari, Department of Electrical and computer Engineering, University of Oklahoma, Norman, United States.
A growing interest in underwater applications is highlighted in this paper. Stereovision is considered as one of the best methods for distance estimation of underwater objects. The current research contains two pairs of cameras in which, they were used as a stereo image acquisition to assess the distance of underwater objects. The stereovision system in this research consists of calibration of camera, rectification of images, segmentation of images, finding of centroid and localization of object. Edge-based segmentation, mathematical morphology and largest area selection were applied to image segmentation performance. Asa result, it will be illustrated that the curve fitting is more reliable than triangulation method to estimate the coordinates. For example, 0.2 cm of overall error with water and glass conditions while using triangulation resulted in the overall all error of around 1.5 cm.
Range Estimation, Stereovision, Curve-Fitting Tool, Image Segmentation
[1]
BORANGIU, T. & DUMITRACHE, A. (2010) Robot Arms with 3D Vision Capabilities. Advances in Robot Manipulators.
[2]
SONKA, M., HLAVAC, V. & BOYLE, R. (2008) Image processing, analysis, and machine vision, Toronto, Thompson Learning.
[3]
OKUTOMI, M., KATAYAMA, Y. & OKA, S. (2002) A simple stereo algorithm to recover precise object boundaries and smooth surfaces. International Journal of Computer Vision, 47, 261-273.
[4]
HALL, E. L., TIO, J. B. K., MCPHERSON, C. A. & SADJADI, F. A. (1982) Measuring curved surfaces for robot vision. Computer, 15, 42-54.
[5]
JIAN-HONG, S., BYUNG-SEUNG, J., JONG-WOOK, L. & MYO-TAEG, L. (2010) Stereo vision based 3D modeling system for mobile robot. 2010 International Conference on Control Automation and Systems (ICCAS).
[6]
KYOUNG WON NAM, J. P., IN YOUNG KIM, KWANG GI KIM (2012) Application of Stereo-Imaging Technology to Medical Field. 10.4258/hir.2012.18.3.158, 158–163.
[7]
KLETTE, R. (2008) Stereo-Vision-Support for Intelligent Vehicles - The Need for Quantified Evidence.
[8]
BROWN, M. Z., BURSCHKA, D. & HAGER, G. D. (2003) Advances in computational stereo. IEEE Transactions on Pattern Analysis and Machine Intelligence, 993-1008.
[9]
NEGAHDARIPOUR, S. & FIROOZFAM, P. (2005) An ROV Stereovision System for Ship Hull Inspection. IEEE JOURNAL OF OCEANIC ENGINEERING, 31, 551-564.
[10]
BAYAR (2013) Apparent Depth. [Accessed June 2, 2013] Available from World Wide Web: http://physics.dindon.mn/Lesson.aspx?lessonID=f97e037c-9f49-4514-8911-887c5eb3593d
[11]
SILPA-ANAN, C. (2001) Autonomous Underwater Robot Vision and Control. Australian National University.
[12]
ZHANG, Z. (2000) A Flexible New Technique for Camera Calibration, WA 98052-6399, USA, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[13]
QUINTANA, X. A. (2003) Modelling stereoscopic vision systems for robotic applications. Department of Electronics, Computer Science and Automatic Control. Universitat de Girona.
[14]
ENG SWEE, K., ABU HASSAN, A. H. & RANJBARAN, A. (2012) Stereo vision with 3D coordinates for robot arm application guide., 2010 IEEE Conference on Sustainable Utilization and Development in Engineering and Technology (STUDENT).
[15]
MAHMOODI KHANIABADI, SH & KHALILI MOBARAKEH, A. (2015) Comparison between Triangulation and Curve Fitting Tool Methods for Underwater Ranging Using Stereo Vision., Vol. 2, No. 4, 2015, pp. 44-47.
[16]
GONZALEZ, R. C. (1987) DIGITAL IMAGE PROCESSING.
[17]
LEYER, M. & GELAUTZ, M. (2005) A layered stereo matching algorithm using image segmentation and global visibility constraints. ISPRS Journal of Photogrammetry and Remote Sensing, 59, 128-150.
[18]
ABIDIN, Z. Z. (2007) Development of a Vision System for Ship Hull Inspection, Master Thesis, Universiti Sains Malaysia.
