MATEC Web of Conferences
Volume 32, 2015International Symposium of Optomechatronics Technology (ISOT 2015)
|Number of page(s)||6|
|Section||Optomechatronics sensing and robotics|
|Published online||02 December 2015|
- O. Duron, K. Althoefer, and L. D. Senevirante, “Automated sewer pipe inspection through image processing”, Proc. of the IEEE International Conf. on Robotics and Automation (ICRA), Vol. 3 , pp. 2551–2556, (2002)
- O. Duran, K. Althoefer, and L. D. Senevirante, “Pipe inspection using a laser-based transducer and automated analysis techniques”, IEEE/ASME Transactions on Mechatronics, Vol. 8, No. 3, pp. 401–409, (2003). [CrossRef]
- A. Basu, and D. Southwell, “Omni-directional sensors for pipe inspection”, Proc. of the IEEE International Conf. on Systems, Man and Cybernetics, Vol. 4, pp. 3107–3112, (1995).
- C. Frey, “Rotating optical geometry sensor for fresh water pipe inspection”, IEEE Journal of Sensors, pp. 337–340, (2008).
- K. Matsui, A. Yamashita, and T. Kaneko, “3-d shape measurement of pipe by range finder constructed with omni-directional laser and omni-directional camera”, Proc. of the IEEE International Conf. on Robotics and Automation (ICRA), pp. 2537–2542, (2010).
- T. Inari, et. al., “Optical inspection system for the inner surface of a pipe using detection of circular images projected by a laser square”, Open-access Journal of Measurements, Vol. 13, No. 2, pp. 99–106, (1994).
- A. D. Tezerjani, M. Mehrandezh, and R. Paranjape, “Optimal spatial resolution of omnidirectional imaging systems for pipe inspection applications”, in press, Journal of Optomechatronics, (2015).
- A. D. Tezerjani, “High resolution visual pipe characterization system using an omnidirectional camera”, Ph.D. thesis under final review (2015).
- T. Morwald, et. al., “Geometric data abstraction using B-splines for range image segmentation”, Proc. of the IEEE International Conf. on Robotics and Automation (ICRA), Vol. 1, pp. 148–153, , (2013).
- S. K. Nayar, “A theory of single-viewpoint Catadioptric image formation”, International Journal of Computer Vision, Vol. 35, Issue 2, pp. 175–196, (1999). [CrossRef]
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