• Journal of Institute of Control, Robotics and Systems
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• v.21 no.4
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• pp.309-314
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• 2015

In this study, an embedded ranging system based on a laser structured light image is developed. The distance measurement by the structured light image processing has efficient computation because the burdensome correspondence problem is avoidable. In order to achieve robustness against environmental illumination noise and real-time laser structured light image processing, a bandpass optical filter is adopted in this study. The proposed ranging system has an embedded image processor performing the whole image processing and distance measurement, and so reduces the computational burden in the main control system. A system calibration algorithm is presented to compensate for the lens distortion.

• The Korean Journal of Applied Statistics
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• v.23 no.4
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• pp.759-765
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• 2010

In this paper, two new inverse regression methods are introduced. One is a distance based method, and the other is a likelihood based method. While a model is fitted by minimizing the sum of squared prediction errors of y's and x's in the classical and inverse methods, respectively. In the new distance based method, we simultaneously minimize the sum of both squared prediction errors. In the likelihood based method, we propose an inverse regression with Arnold-Beaver Skew Normal(ABSN) error distribution. Using the cross validation method with an asymmetric real data set, two new and two existing methods are studied based on the relative prediction bias(RBP) criteria.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2010.03b
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• pp.5-5
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• 2010

The depth of the object pointed by the laser beam is computed depending on the pixel position on the CCD There involved several number of internal and external parameters such as inter-pixel distance, focal length, position and orientation of the system components in the depth measurement error. In this paper, it is shown through the error sensitivity analysis of the parameters that the most important parameters in the sense of error sources are the angle of the laser beam and the inter pixel distance. Also, the calibration technique to minimize their effect for the depth computation is proposed.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.68-72
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• 1990

This paper describes a method of calculating the viewing parameters of a camera using a perspective view of a circular pattern. The proposed method determines the angle of pan, tilt, and swing, as well as the distance from the camera to the reference point of a world coordinate system, using simple equations. The proposed method is so simple and accurate that when used in a well-controled environment as in robot vision systems or visual inspection systems it may even seem trivial.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.1
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• pp.46.2-46.2
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• 2015

Modern methods in determining the value of the Hubble constant are divided into two main ways: the classical distance ladder method and the inverse distance ladder method. The classical distance ladder method is based on Cepheid calibrated Type Ia supernovae (SNe Ia), which are known as powerful distance indicator. The inverse distance ladder method uses cosmic microwave background radiation, which emitted from the high-z universe, and the cosmological model. Recent estimations of the Hubble constant based on these two methods show a $2{\sim}3{\sigma}$ difference, which called the "Hubble tension". It is currently an issue in the modern cosmology. We have been working on the luminosity calibration of SNe Ia based on the Tip of the Red Giant Branch (TRGB), which is a precise population I distance indicator. We present the TRGB distance estimates of 5 SNe Ia host galaxies with the archival Hubble Space Telescope image data. We derive the mean absolute maximum magnitude of 5 SNe Ia and the value of the Hubble constant. Cosmological implications of our estimate will be discussed.

• The Bulletin of The Korean Astronomical Society
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• v.28 no.1
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• pp.62-62
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• 2003

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.3
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• pp.329-336
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• 2010

This study deals with the measurement of reflectivity as well as the distance accuracy with Terrestrial Laser Scanner(TLS) using time of flight methods and near infrared wave length, for a variety of user-made targets. Especially, point clouds' reflection to several targets was measured with Gretag Macbeth il spectrophotometer in the office. And the distance accuracy in comparison to reference distance for TLS performance evaluation, was tested after scanning the user-made targets and measuring the inter-pillars distances over the precise EDM calibration baseline. The results of test was shown that except white resin objects, with approx. 10m and 170m inter-pillar distances, other targets achieved the distance accuracy of several millimeters(mm) with respect to standard distances. Future work should be concentrate on a few parameters influencing on the distance accuracy such as atmospheric correction, instrument correction, the additive constant or zero/index correction, etc.

• Journal of Animal Environmental Science
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• v.18 no.sup
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• pp.81-90
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• 2012

This study was evaluated high end research grade Near infrared spectrophotometer (NIRS) to low end popular field grade multiple Near infrared spectrophotometer (NIRS) for rapid analysis at forage quality at sight with 241 samples of Italian ryegrass silage during 3 years collected whole country for evaluate accuracy and precision between instruments. Firstly collected and build database high end research grade NIRS using with Unity Scientific Model 2500X (650 nm~2,500 nm) then trim and fit to low end popular field grade NIRS with Unity Scientific Model 1400 (1,400 nm~2,400 nm) then build and create calibration, transfer calibration with special transfer algorithm. The result between instruments was 0.000%~0.343% differences, rapidly analysis for chemical constituents, NDF, ADF, and crude protein, crude ash and fermentation parameter such as moisture, pH and lactic acid, finally forage quality parameter, TDN, DMI, RFV within 5 minutes at sight and the result equivalent with laboratory data. Nevertheless during 3 years collected samples for build calibration was organic samples that make differentiate by local or yearly bases etc. This strongly suggest population evaluation technique needed and constantly update calibration and maintenance calibration to proper handling database accumulation and spread out by knowledgable control laboratory analysis and reflect calibration update such as powerful control center needed for long lasting usage of forage analysis with NIRS at sight. Especially the agriculture products such as forage will continuously changes that made easily find out the changes and update routinely, if not near future NIRS was worthless due to those changes. Many research related NIRS was shortly study not long term study that made not well using NIRS, so the system needed check simple and instantly using with local language supported signal methods Global Distance (GD) and Neighbour Distance (ND) algorithm. Finally the multiple popular field grades instruments should be the same results not only between research grade instruments but also between multiple popular field grade instruments that needed easily transfer calibration and maintenance between instruments via internet networking techniques.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.8
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• pp.824-833
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• 2006

In this paper, the image modelling of road's lane markings is established using view frustum(VF) model. From this model, a measurement system of lane markings and obstacles is proposed. The system also involve the real time processing of the 3D position coordinate and the distance data from the camera to the points on the 3D world coordinate by virtue of the camera calibration. In order to reduce their measurement error, an useful algorithm for which analyze the geometric variations due to traveling vehicle's fluctuation using VF model is proposed. In experiments, without correction, for instance, the $0.4^{\circ}$ of pitching rotation gives the error of $0.4{\sim}0.6m$ at the distance of 10m, but the more far distance cause exponentially the more error. We con finned that this algorithm can be reduced less than 0.1m of error at the same condition.

• Journal of Broadcast Engineering
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• v.24 no.4
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• pp.580-591
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• 2019

This paper focuses on to improving object detection performance using the camera and LiDAR on autonomous vehicle platforms by fusing detected objects from individual sensors through a late fusion approach. In the case of object detection using camera sensor, YOLOv3 model was employed as a one-stage detection process. Furthermore, the distance estimation of the detected objects is based on the formulations of Perspective matrix. On the other hand, the object detection using LiDAR is based on K-means clustering method. The camera and LiDAR calibration was carried out by PnP-Ransac in order to calculate the rotation and translation matrix between two sensors. For Sensor fusion, intersection over union(IoU) on the image plane with respective to the distance and angle on world coordinate were estimated. Additionally, all the three attributes i.e; IoU, distance and angle were fused using logistic regression. The performance evaluation in the sensor fusion scenario has shown an effective 5% improvement in object detection performance compared to the usage of single sensor.