Utilizing Point Cloud Handling Technology for Study on World Heritage — Silver Mines across Japan

Industry: Archaeological ResearchProduct: InfiPoints

National Institute of Technology, Matsue College

Professor Hideo Kuma from Control Engineering Department of Matsue College investigates and aims to establish a new method — 3D scans deep inside the narrow drift mine utilizing specially-developed remote control robot, and also the ground surface around the entrance — to estimate the start age and the production amount of drift mines across Japan.

  • Entrance and drift of Iwami Silver Mine, a World Heritage

Obstacles to Investigation on Silver Mine of Historical Value

There are many remains of mines all across Japan including Iwami Ginzan Silver Mine which was certified as UNESCO World Heritage in 2007 for its historical value that it produced nearly one third of the silver circulated around the world in sixteenth century and later.

Those mines are, however, now heavily wooded, and the entry is often restricted for the risk of rock-fall, so that it is difficult, or even impossible to grab the complete picture and investigate in detail. Therefore, the research was mainly to record the outside of the drift mines by sketches and photos. Some tried 2D-scanning inside the drift mine, but the obtained data was inaccurate and insufficient for the investigation.

  • Heavily-wooded remain of drift mine

3D Scan the Ground Surface — Auto Detect and Removal of Woods in Point Cloud Data

One day at a trade show, Professor Kuma met 3D laser scanner and point cloud handling software, InfiPoints, which provides a functionality to extract the ground surface from the obtained point cloud data. He quickly introduced a new method to his research — 3D scans the remains of mines, and then extract the points for the ground surface from the obtained point cloud data using InfiPoints.

  • Extracting the points for ground surface only using InfiPoints

He investigated one of the most valuable mines, Tada Silver-and-copper Mine, using this new method, and successfully identified the mark of open-pit mining, a characteristic surface mining technique.

  • Point cloud data of Hyotan drift mine, Tada Silver-and-Copper Mine

Moreover, he optimized the 3D scanned data for 3D printing using InfiPoints, and created a model of remain of the mine for further investigation — estimated the total amount of silver production from the volume of the mark of open-pit mining.

  • Left: Polygons generated from optimized point cloud data
    Right: Model made by 3D printer

He even succeeded to unveil the cultural landscape around the mine by minutely studying the ground surface to identify the artifact such as stone walls.

  • 石垣の形状を分かりやすく再現Left: On-site investigation of stone walls in Tada Silver-and-Copper Mine
    Right: Polygon data of ground surface generated from 3D scanned data — stone walls came out clearly by removing points for woods in InfiPoints

Auto Noise Reduction for 3D Scanned Data from Inside the Drift Mine

The entry to the drift mine is often physically restricted, and even when it is possible, it is still very hard to conduct minute survey for many hours inside the narrow, dusty drift mine. A special robot developed by students in Professor Kuma’s office achieved unattended 3D scanning inside the drift mine. After preprocessing obtained point cloud data using InfiPoints — register shorts, and remove noises caused by dust inside the drift, 3D scanned data is fully utilized for their virtual investigation and researches.

  • Left: Robot developed by Matsue College to carry 3D laser scanner and CCD camera
    Right: Creating point cloud data of entire drift mine by registering 13 shots from 3D scanning

Possibility to Apply Point Cloud Handling Technology to Disaster Prevention

Professor Kuma has investigated about one hundred remains of drift mines all over Japan, and he is seeing a great possibility to apply this 3D scanning and point cloud handling technology to disaster prevention, for example, detecting a risk of landslides by regular observation of mountain slope for the variation.