• KIPS Transactions on Software and Data Engineering
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• v.7 no.10
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• pp.377-382
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• 2018

This study deals with internal state and tissue density analysis methods for red ginseng grade determination. For internal measurement of red ginseng, there have been various studies on nondestructive testing methods since the 1990s, It was difficult to grasp the most important inner hole and inside whites in the grading. So in this study, we developed a closed capturing device for infra-red illumination environment, and developed an internal measurement system that can detect the presence and diameter of inner hole and inside whites. Made devices consisted of infrared lights with a high transmission rate of red ginseng in 920 nanometer wave band, a infra-red camera and a Y axis actuator with a red ginseng automatically controlled focus on the camera. The proposed algorithm performs an auto-focus system on the Y-axis actuator to automatically adjust the sharp focus of the object according to the size and thickness. Then red ginseng is rotated $360^{\circ}$ at $1^{\circ}$ intervals and 360 total images are acquired, and reconstructed as a sinogram through Radon transform and Back-projection algorithm was performed to acquire internal images of red ginseng. As a result of the algorithm, it was possible to acquire internal cross-sectional image regardless of the thickness and shape of red ginseng. In the future, if more than 10,000 different shapes and sizes of red ginseng internal cross-sectional image are acquired and the classification criterion is applied, it can be used as a reliable automated ginseng grade automatic measurement method.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.6
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• pp.157-166
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• 2022

Structural supervision on the construction site has been performed based on visual inspection, which is highly labor-intensive and subjective. In this study, the remote technique was developed to improve the efficiency of the measurements on rebar spacing using a 360° camera and reconstructed 3D models. The proposed method was verified by measuring the spacings in reinforced concrete structure, where the twelve locations in the construction site (265 m²) were scanned within 20 seconds per location and a total of 15 minutes was taken. SLAM, consisting of SIFT, RANSAC, and General framework graph optimization algorithms, produces RGB-based 3D and 3D point cloud models, respectively. The minimum resolution of the 3D point cloud was 0.1mm while that of the RGB-based 3D model was 10 mm. Based on the results from both 3D models, the measurement error was from 10.8% to 0.3% in the 3D point cloud and from 28.4% to 3.1% in the RGB-based 3D model. The results demonstrate that the proposed method has great potential for remote structural supervision with respect to its accuracy and objectivity.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05a
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• pp.679-682
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• 2003

카타디옵트릭 카메라는 거울을 이용하여 $360^{\circ}$의 3차원 이미지를 한 장에 촬영할 수 있는 이미지 시스템이다. 본 논문에서는 이 시스템을 사용할 때에 발생하는 이미지 왜곡 문제를 해결하는 구형투영 알고리즘을 제안한다. 흔히 사용하는 실린더형 알고리즘의 경우 계산은 비교적 간단하지만, 거울의 바로 아래에 있는 물체의 경우 전체적인 영상을 볼 수 없다는 단점이 있다. 본 연구에서 사용한 카메라는 포물면 거울을 사용한 카타디옵트릭 카메라이며, 쌍곡면거울을 사용한 카메라에 대해서도 이론적으로 공식을 유도하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.18-20
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• 2019

In this paper, in order to prevent accidents when deviating from the lane during high-speed self-driving, we are going to design a warning system that will sound an alarm after recognizing the surrounding situation with a $360^{\circ}$ camera. Accidents often occur while driving on self-driving cars because they try to change lanes excessively or fail to recognize people, animals and objects that appear suddenly when driving at high speeds. The government wants to identify the surrounding situation with cameras when driving off a lane during high-speed autonomous driving, and to create a car that sounds a warning system through a lane departure sensor on the underside of the vehicle to reduce various accidents that occur during self-driving and to have a safer driving system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.5
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• pp.1080-1088
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• 2004

In this paper, the interesting moving objects tracking algorithm using color information on Multi-Video camera against variance of intensity, shape and background is proposed. Moving objects are detected by using difference image method and integral projection method to background image and objects image only with hue area, after converting RGB color coordination of image which is input from multi-video camera into HSI color coordination. Hue information of the detected moving area are segmented to 24 levels from $0^{\circ}$ to $360^{\circ}$. It is used to the feature parameter of the moving objects that are three segmented hue levels with the highest distribution and difference among three segmented hue levels. To examine propriety of the proposed method, human images with variance of intensity and shape and human images with variance of intensity, shape and background are targeted for moving objects. As surveillance results of the interesting human, hue distribution level variation of the detected interesting human at each camera is under 2 level, and it is confirmed that the interesting human is tracked and surveilled by using feature parameters at cameras, automatically.

• Journal of IKEEE
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• v.24 no.4
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• pp.1050-1057
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• 2020

Immersive 360-degree media has a problem of slowing down the video recognition speed when the video is processed by the conventional method using a variety of rendering methods, and the video size becomes larger with higher quality and extra-large volume than the existing video. In addition, in most cases, only one scene is captured by fixing the camera in a specific place due to the characteristics of the immersive 360-degree media, it is not necessary to extract feature information from all scenes. In this paper, we propose a reference frame selection method for immersive 360-degree media and describe its application process to copyright protection technology. In the proposed method, three pre-processing processes such as frame extraction of immersive 360 media, frame downsizing, and spherical form rendering are performed. In the rendering process, the video is divided into 16 frames and captured. In the central part where there is much object information, an object is extracted using an RGB vector per pixel and deep learning, and a reference frame is selected using object feature information.

• The KIPS Transactions:PartB
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• v.11B no.3
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• pp.267-274
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• 2004

In this paper, the interesting moving objects tracking algorithm using color information on Multi-Video camera is proposed Moving objects are detected by using difference image method and integral projection method to background image and objects image only with hue area, after converting RGB color coordination of image which is input from multi-video camera into HSI color coordination. Hue information of the detected moving area are normalized by 24 steps from 0$^{\circ}$ to 360$^{\circ}$ It is used for the feature parameters of the moving objects that three normalization levels with the highest distribution and distance among three normalization levels after obtaining a hue distribution chart of the normalized moving objects. Moving objects identity among four cameras is distinguished with distribution of three normalization levels and distance among three normalization levels, and then the moving objects are tracked and surveilled. To examine propriety of the proposed method, four cameras are set up indoor difference places, humans are targeted for moving objects. As surveillance results of the interesting human, hue distribution chart variation of the detected Interesting human at each camera in under 10%, and it is confirmed that the interesting human is tracked and surveilled by using feature parameters at four cameras, automatically.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.5
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• pp.442-450
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• 2011

A measurement system using stereo pattern recognition (SPR) method was configured to measure the rotor blade deformations and motions. An SPR-based measurement system was prepared using six stereo cameras. Through a series of experiments to evaluate the system measurement uncertainty, it was verified that the SPR system had less than 0.2mm standard uncertainty. The combined standard uncertainties for the lead-lag, flapping, and pitching motions were estimated as 0.296mm, 0.209mm, and $0.238^{\circ}$, respectively. The SPR system was installed at a general small-scaled rotor test system at Korea Aerospace Research Institute. The blade motions and elastic deformation were successfully measured under the conditions with rotating speeds of 360rpm or 589rpm, and collective pitch angles of $0^{\circ}$, $4^{\circ}$, or $6^{\circ}$. The advantages of the SPR system was analyzed in comparison with the measurement system used in Higher Harmonic Control Aeroacoustic Rotor Test -II.

• Progress in Medical Physics
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• v.26 no.1
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• pp.18-27
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• 2015

Since a Compton camera has high detection sensitivity due to electronic collimation and a good energy resolution, it is a potential imaging system for nuclear medicine. In this study, we investigated the feasibility of a Compton camera for multi-tracer imaging and proposed a rotating Compton camera to satisfy Orlov's condition for 3D imaging. Two software phantoms of 140 and 511 keV radiation sources were used for Monte-Carlo simulation and then the simulation data were reconstructed by listmode ordered subset expectation maximization to evaluate the capability of multi-tracer imaging in a Compton camera. And the Compton camera rotating around the object was proposed and tested with different rotation angle steps for improving the limited coverage of the fixed conventional Compton camera over the field-of-view in terms of histogram of angles in spherical coordinates. The simulation data showed the separate 140 and 511 keV images from simultaneous multi-tracer detection in both 2D and 3D imaging and the number of valid projection lines on the conical surfaces was inversely proportional to the decrease of rotation angle. Considering computation load and proper number of projection lines on the conical surface, the rotation angle of 30 degree was sufficient for 3D imaging of the Compton camera in terms of 26 min of computation time and 5 million of detected event number and the increased detection time can be solved with multiple Compton camera system. The Compton camera proposed in this study can be effective system for multi-tracer imaging and is a potential system for development of various disease diagnosis and therapy approaches.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.573-576
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• 2017

본 연구는 홍삼 등급판정 과정에서 내부 조직 치밀도 분석을 위해 의료 영상 분석 방법을 이용하여 적외선 영상 측정기기를 개발하였다. 기존 홍삼 내부분석방법은 수동으로 암실환경에서 강한 조명을 홍삼에 투과하여 사람 눈으로 직접 판별하는 과정을 거친다. 이러한 기존 검사 과정은 작업 비효율성과 불균일한 검사기준으로 제품 품질 신뢰도 저하의 단점을 가져온다. 이러한 문제점을 해결하기 위해 본 연구는 적외선 조명환경에서 자동 측정이 가능한 홍삼 내부 측정기기를 개발하였다. 개발된 장치는 홍삼의 빛 투과 특성을 응용한 920nm 파장대역의 적외선 조명기구, 조명 제어회로, 적외선 대역 촬영이 가능한 영상 측정 카메라 장치, $0.9^{\circ}$의 간격으로 $360^{\circ}$ 홍삼 영상취득이 가능한 회전 엑츄에이터로 구성이 된다. 본 연구에서 제안 하는 홍삼 단층 영상분석 방법은, 홍삼을 $0.9^{\circ}$ 간격으로 회전시키어 $360^{\circ}$ 홍삼 내부영상을 취득하여 라돈 변환(Radon transform)을 통해 사이노그램(Sinogram)으로 재구성 하였으며, 역 라돈 변환(Inverse Radon transform)을 통해 단층 영상복원(Back-projection)알고리즘을 구현하였다. 이 결과 홍삼을 절단하지 않고 홍삼 내부 단면영상 획득이 가능하였으며 내공(內空), 내백(內白)의 유무를 판단하고 직경을 파악할 수 있었다. 이를 토대로 등급 판별 공식을 산출하면 신뢰성 있는 홍삼 등급 자동화 측정기기를 개발할 수 있을 것으로 기대된다.