• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.177-180
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• 2006

In this paper we proposed a method of automatic point segmentation acquired by 2D laser scanner to recognize moving objects. Recently, Laser scanner is noticed as a new method in the field of close range 3D modeling. But the majority of the researches are pointed on precise 3D modeling of static objects using expensive 3D laser scanner. 2D laser scanner is relatively cheap and can obtain 2D coordinate information of moving object's surface or can be utilized as 3D laser scanner by rotating the system body. In these reasons, some researches are in progress, which are adopting 2D laser scanner to robot control systems or detection of objects moving along linear trajectory. In our study, we automatically segmented point data of 2D laser scanner thus we could recognize each of the object passing through a section.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.5
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• pp.313-323
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• 2016

With the development of autonomous vehicle, there has been active research on advanced driver assistance system for road marking detection using vision sensor and 3D Laser scanner. However, vision sensor has the weak points that detection is difficult in situations involving severe illumination variance, such as at night, inside a tunnel or in a shaded area; and that processing time is long because of a large amount of data from both vision sensor and 3D Laser scanner. Accordingly, this paper proposes a road marking detection and classification method using single 2D Laser scanner. This method road marking detection and classification based on accumulation distance data and intensity data acquired through 2D Laser scanner. Experiments using a real autonomous vehicle in a real environment showed that calculation time decreased in comparison with 3D Laser scanner-based method, thus demonstrating the possibility of road marking type classification using single 2D Laser scanner.

• Journal of Technologic Dentistry
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• v.41 no.2
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• pp.53-61
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• 2019

Purpose: The purpose of this study is to evaluate the discrepancy of scan process in dental intra oral scanner by comparing model scanner and anticipate possibility to introduce intra oral scan technique. Methods: 3D superimposition test was conducted to compare the scan discrepancy. The scanners used in this study are the e-oral scanner, the D750 model scanner, and the high precision CMM(3D Coordinate Measuring Machine). The standard of accuracy verification is ISO 5725-1; trueness and precision. Master model was manufactured by dental stone and scanned 5 times by intra oral, model scanner. Reference data was scanned 5 times by high accuracy CMM to evaluate the trueness. Results: Trueness of D750 scanner were $7.4{\mu}m$ $5.1{\mu}m$ $6.8{\mu}m$ at an abutment, an occluasal, a specific area. and trueness of e-scanner were $20.2{\mu}m$ $27.4{\mu}m$ $37.8{\mu}m$ at an abutment, an occluasal, a specific area. Precision of D750 scanner was $7.04{\mu}m$, e-scanner was $15.95{\mu}m$. Conclusion: When conducting in vitro test, The mean difference of trueness between e-scanner and D750 were $12.8{\mu}m$ at an abutment area, $22.3{\mu}m$ at an occlusal area, $31.0{\mu}m$ at a specific area and $8.91{\mu}m$ in precision. The scan discrepancies are within the range of clinical acceptance.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.10
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• pp.811-816
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• 2016

In light of recently developed 3D printers for rapid prototyping, there is increasing attention on the 3D scanner as a 3D data acquisition system for an existing object. This paper presents a prototypical 3D scanner based on a striped laser light image. In order to solve the problem of shadowy areas, the proposed 3D scanner has two cameras with one laser light source. By using a horizontal rotation table and a rotational arm rotating about the latitudinal axis, the scanner is able to scan in all directions. To remove an additional optical filter for laser light pixel extraction of an image, we have adopted a differential image method with laser light modulation. Experimental results show that the scanner's 3D data acquisition performance exhibited less than 0.2 mm of measurement error. Therefore, this scanner has proven that it is possible to reconstruct an object's 3D surface from point cloud data using a 3D scanner, enabling reproduction of the object using a commercially available 3D printer.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.4
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• pp.138-144
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• 2014

Now, Autonomous unmanned vehicle has become an issue in next generation technology. 2D Laser scanner as the distance measurement sensor is used. 2D Laser scanner detects the distance of 80m, measured angle is -5 to 185 degree. Laser scanner detects only the plane, but using motor swings. As a result, traffic signs detect and analyze patterns. Traffic signs when driving at low speed, shape of the detected pattern is very similar. By shaking the laser scanner, traffic signs and other obstacles became clear distinction.

• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.478-480
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• 2009

This experiment implemented a laser projection system that used the 2D MEMS scanner as the driving method for the display device. The 2D MEMS scanner, which can scan the images horizontally and vertically, was applied to drive the projection system using the interlaced scanning method. The laser was directly modulated to implement the grayscale and the images were WVGA resolution quality.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.3
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• pp.186-191
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• 2016

This paper addresses the development of 3D data acquisition system (3D scanner) based laser structured-light image. The 3D scanner consists of a stripe laser generator, a conventional camera, and a rotation table. The stripe laser onto an object has distortion according to 3D shape of an object. By analyzing the distortion of the laser stripe in a camera image, the scanner obtains a group of 3D point data of the object. A simple semiconductor stripe laser diode is adopted instead of an expensive LCD projector for complex structured-light pattern. The camera has an optical filter to remove illumination noise and improve the performance of the distance measurement. Experimental results show the 3D data acquisition performance of the scanner with less than 0.2mm measurement error in 2 minutes. It is possible to reconstruct a 3D shape of an object and to reproduce the object by a commercially available 3D printer.

• Journal of the Korean Society of Costume
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• v.53 no.5
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• pp.1-12
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• 2003

This paper proposes a system for measuring the 3D human bodies using the multiple 2D images. The system establishes the multiple image input circumstance from the digital camera for image measurement. The algorithm considering perspective projection leads us to estimate the 3D human bodies from the multiple 2D images such as frontal. side and rear views. The results of the image measurement is compared those of the direct measurement and the 3D scanner for the total 40 items (12 heights, 15 widths and 13 depths). Three persons measure the 40 items using the three measurement methods. In comparison of the results obtained among the measurement methods and the persons, the results between the image measurement and the 3D scanner are very similar. However, the errors for the direct measurement are relatively larger than those between the image measurement and the 3D scanner. For example, the maximum errors between the image measurement and the 3D scanner are 0.41cm in height, 0.39cm in width and 0.95cm in depth. The errors are acceptable in body measurement. Performance of the image measurement is superior to the direct. because the algorithm estimates the 3D positions using the perspective projection. In above comparison, the image measurement is expected as a new method for measuring the 3D body, since it has the various advantages of the direct measurement and 3D scanner in performance for measurement as well as in the devices, cost, Portability and man power.

• Current Optics and Photonics
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• v.2 no.6
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• pp.554-562
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• 2018

This study presents a color 3D scanner based on the laser structured-light imaging method that can simultaneously acquire 3D shape data and color of a target object using a single camera. The 3D data acquisition of the scanner is based on the structured-light imaging method, and the color data is obtained from a natural color image. Because both the laser image and the color image are acquired by the same camera, it is efficient to obtain the 3D data and the color data of a pixel by avoiding the complicated correspondence algorithm. In addition to the 3D data, the color data is helpful for enhancing the realism of an object model. The proposed scanner consists of two line lasers, a color camera, and a rotation table. The line lasers are deployed at either side of the camera to eliminate shadow areas of a target object. This study addresses the calibration methods for the parameters of the camera, the plane equations covered by the line lasers, and the center of the rotation table. Experimental results demonstrate the performance in terms of accurate color and 3D data acquisition in this study.

• Korean Journal of Ecology and Environment
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• v.47 no.3
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• pp.232-238
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• 2014

We have developed a non-destructive, touch-free method for estimating leaf areas with a structured-light three-dimensional (3D) scanner. When the surfaces of soybean leaves were analyzed with both the 3D scanner and a leaf area meter, the results were linearly related ($R^2=0.90$). The strong correlation ($R^2=0.98$) was calculated between shoot fresh weights and leaf areas when the scanner was employed during growth stages V1 to V4. We also found that leaf areas measured by the scanner could be used to detect changes in growth responses to abiotic stress. Whereas under control conditions the areas increased over time, salt and drought treatments were associated with reductions in those values after 14 d and 12 d, respectively. Based on our findings, we propose that a structured-light 3D scanner can be used to obtain reliable estimates of leaf area and plant biomass.