Automatic recognition of piping system from laser scanned point clouds using normal-based region growing

Kawashima, Kazuaki; Kanai, Satoshi; Date, Hiroaki

doi:10.5194/isprsannals-ii-5-w2-121-2013

Cited by 8 publications

(1 citation statement)

References 8 publications

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“…To this end, many researches have been intensively studies to recognize piping objects such as straight pipes, elbows, junctions and valves from point clouds captured from terrestrial laser scanners (Vosselman et al, 2004), , (Rabbani et al, 2006), (Belton et al, 2006), (Bey et al, 2011), (Masuda et al, 2012), (Kawashima et al, 2013). When capturing the plant objects using a terrestrial laser scanner, several scans must be taken from different scanner positions to ensure a full coverage of the object surfaces and to avoid the occlusions.…”

Section: Introductionmentioning

confidence: 99%

Finding the next-best scanner position for as-built modeling of piping systems

Kawashima

Yamanishi

Kanai

et al. 2014

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Renovation of plant equipment of petroleum refineries or chemical factories have recently been frequent, and the demand for 3D asbuilt modelling of piping systems is increasing rapidly. Terrestrial laser scanners are used very often in the measurement for as-built modelling. However, the tangled structures of the piping systems results in complex occluded areas, and these areas must be captured from different scanner positions. For efficient and exhaustive measurement of the piping system, the scanner should be placed at optimum positions where the occluded parts of the piping system are captured as much as possible in less scans. However, this "nextbest" scanner positions are usually determined by experienced operators, and there is no guarantee that these positions fulfil the optimum condition. Therefore, this paper proposes a computer-aided method of the optimal sequential view planning for object recognition in plant piping systems using a terrestrial laser scanner. In the method, a sequence of next-best positions of a terrestrial laser scanner specialized for as-built modelling of piping systems can be found without any a priori information of piping objects. Different from the conventional approaches for the next-best-view (NBV) problem, in the proposed method, piping objects in the measured point clouds are recognized right after an every scan, local occluded spaces occupied by the unseen piping systems are then estimated, and the best scanner position can be found so as to minimize these local occluded spaces. The simulation results show that our proposed method outperforms a conventional approach in recognition accuracy, efficiency and computational time.

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Section: Introductionmentioning

confidence: 99%