• 한국전자파학회논문지
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• 제14권9호
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• pp.936-943
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• 2003

초소형 무선내시경은 CMOS Image sensor, FPGA, LED, Battery,DC to DC Converter, Antenna 그리고 송신기로 구성되어 있다. 최대 전자파 노출규제, 시스템의기, 전력소모, 선형성 및 변조방법 등을 고려하여 지름 10 mm, 두께 2.3 mm인 FSK송신기를 설계, 제작 및 측정하였다. 제작된 송신기는 1.2 GHz 대역에서 동작하며, -3.67dBm의 출력전력, -99dBc/Hz(@100 KHz offset)의 위상잡음, -20.17 dBc의 고조파 억압을 나타내었다. 동물실험에서 제작된 무선내시경용 FSK 송신기는 만족할만한 성능을 나타내었다.

• Journal of International Society for Simulation Surgery
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• 제1권2호
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• pp.83-86
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• 2014

Purpose This paper was purposed to suggest the method to produce the supportive helmet (head correction) for the infants who are suffering from plagiocephaly and to evaluate the level of transformation through 3D model. Method Either of CT or X-ray restored images has been used in making the supportive helmet (Head correction) in general, but these methods of measuring have problems in cost and safety. 3D surface measurement technology was suggested to solve such matters. Results It was to design the transformed model of the head within 0.7cm in average by scanning the surface of head and performing 3D restoration with marching cube and the changing rate of the head was compared in numerical data with 3D model. Conclusion The suggested methods displayed the better performance than the conventional method in respect of the speed and cost.

• 한국정보전자통신기술학회논문지
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• 제13권1호
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• pp.8-16
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• 2020

본 논문에서는 polymerase chain reaction (PCR) 응용에 적합한 저잡음 CMOS 이미지 센서에 사용되는 컬럼-패러럴 analog-to-digital converter (ADC) 어레이를 위한 cascaded-of-integrator feedforward (CIFF) 구조의 단일 비트 2차 델타-시그마 모듈레이터를 제안하였다. 제안된 모듈레이터는 CMOS 이미지 센서에 입사된 빛의 신호에 해당하는 픽셀 출력 전압을 디지털 신호로 변환시키는 컬럼-패러럴 ADC 어레이를 위해 하나의 픽셀 폭과 동일한 10㎛ 컬럼 폭 내에 2개의 스위치드 커패시터 적분기와 단일 비트 비교기로 구현하였다. 또한, 모든 컬럼의 모듈레이터를 동시에 구동하기 위한 주변 회로인 비중첩 클록 발생기 및 바이어스 회로를 구성하였다. 제안된 델타-시그마 모듈레이터는 110nm CMOS 공정으로 구현하였으며 12kHz 대역폭에 대해 418의 oversampling ratio (OSR)로 88.1dB의 signal-to-noise-and-distortion ratio (SNDR), 88.6dB의 spurious-free dynamic range (SFDR) 및 14.3비트의 effective-number-of-bits (ENOB)을 달성하였다. 델타 시그마 모듈레이터의 면적 및 전력 소비는 각각 970×10 ㎛2 및 248㎼이다.

• 센서학회지
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• 제21권6호
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• pp.413-419
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• 2012

A dynamic range extension technique is proposed based on a 3-transistor active pixel sensor (APS) with gate/body-tied p-channel metal oxide semiconductor field effect transistor (PMOSFET)-type photodetector using a feedback structure. The new APS consists of a pseudo 3-transistor APS and an additional gate/body-tied PMOSFET-type photodetector, and to extend the dynamic range, an NMOSFET switch is proposed. An additional detector and an NMOSFET switch are integrated into the APS to provide negative feedback. The proposed APS and pseudo 3-transistor APS were designed and fabricated using a $0.35-{\mu}m$ 2-poly 4-metal standard complementary metal oxide semiconductor (CMOS) process. Afterwards, their optical responses were measured and characterized. Although the proposed pixel size increased in comparison with the pseudo 3-transistor APS, the proposed pixel had a significantly extended dynamic range of 98 dB compared to a pseudo 3-transistor APS, which had a dynamic range of 28 dB. We present a proposed pixel that can be switched between two operating modes depending on the transfer gate voltage. The proposed pixel can be switched between two operating modes depending on the transfer gate voltage: normal mode and WDR mode. We also present an imaging system using the proposed APS.

• 센서학회지
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• 제33권3호
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• pp.179-184
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• 2024

In the car industry, welding is a fundamental linking technique used for joining components, such as steel, molds, and automobile parts. However, accurate inspection is required to test the reliability of the welding components. In this study, we investigate the detection of weld beads using 2D image processing in an automatic recognition system. The sample image is obtained using a 2D vision camera embedded in a lighting system, from where a portion of the bead is successfully extracted after image processing. In this process, the soot removal algorithm plays an important role in accurate weld bead detection, and adopts adaptive local gamma correction and gray color coordinates. Using this automatic recognition system, geometric parameters of the weld bead, such as its length, width, angle, and defect size can also be defined. Finally, on comparing the obtained data with the industrial standards, we can determine whether the weld bead is at an acceptable level or not.

• International journal of advanced smart convergence
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• 제9권3호
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• pp.232-238
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• 2020

In this paper, we study on aerial objects detection and position estimation algorithm for the safety of UAV that flight in BVLOS. We use the vision sensor and LiDAR to detect objects. We use YOLOv2 architecture based on CNN to detect objects on a 2D image. Additionally we use a clustering method to detect objects on point cloud data acquired from LiDAR. When a single sensor used, detection rate can be degraded in a specific situation depending on the characteristics of sensor. If the result of the detection algorithm using a single sensor is absent or false, we need to complement the detection accuracy. In order to complement the accuracy of detection algorithm based on a single sensor, we use the Kalman filter. And we fused the results of a single sensor to improve detection accuracy. We estimate the 3D position of the object using the pixel position of the object and distance measured to LiDAR. We verified the performance of proposed fusion algorithm by performing the simulation using the Gazebo simulator.

• 한국산업융합학회 논문집
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• 제22권3호
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• pp.293-301
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• 2019

Based on accurate image processing technology, a system for measuring displacement in ${\mu}m$ for drive error (position error, straightness error, flatness error) at a distance using parallel light and image sensor is developed, and a system for applying this technology development to a large 3D rapid prototyping machine and compensating in real time is developed to dramatically reduce the range of measurement error and enable intelligent 3D production of high quality products.

• 제어로봇시스템학회논문지
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• 제22권12호
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• pp.1061-1067
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• 2016

Position of the vehicle for driving is essential to autonomous navigation. However, there appears GPS position error due to multipath which is occurred by tall buildings in downtown area. In this paper, GPS position error is corrected by using camera sensor and highly accurate map made with 3D-Lidar. Input image through inverse perspective mapping is converted into top-view image, and it works out map matching with the map which has intensity of 3D-Lidar. Performance comparison was conducted between this method and traditional way which does map matching with input image after conversion of map to pinhole camera image. As a result, longitudinal error declined 49% and complexity declined 90%.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1177-1179
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• 2003

Recently, the ground-based laser profiler is used for acquisition of 3D spatial information of a rchaeological objects. However, it is very difficult to measure complicated objects, because of a relatively low-resolution. On the other hand, texture mapping can be a solution to complement the low resolution, and to generate 3D model with higher fidelity. But, a huge cost is required for the construction of textured 3D model, because huge labor is demanded, and the work depends on editor's experiences and skills . Moreover, the accuracy of data would be lost during the editing works. In this research, using the laser profiler and a non-calibrated digital camera, a method is proposed for the automatic generation of 3D model by integrating these data. At first, region segmentation is applied to laser range data to extract geometric features of an object in the laser range data. Various information such as normal vectors of planes, distances from a sensor and a sun-direction are used in this processing. Next, an image segmentation is also applied to the digital camera images, which include the same object. Then, geometrical relations are determined by corresponding the features extracted in the laser range data and digital camera’ images. By projecting digital camera image onto the surface data reconstructed from laser range image, the 3D texture model was generated automatically.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권8호
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• pp.3136-3150
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• 2015

A vision-based 3D tracking of articulated human hand is one of the major issues in the applications of human computer interactions and understanding the control of robot hand. This paper presents an improved approach for tracking and recovering the 3D position and orientation of a human hand using the Kinect sensor. The basic idea of the proposed method is to solve an optimization problem that minimizes the discrepancy in 3D shape between an actual hand observed by Kinect and a hypothesized 3D hand model. Since each of the 3D hand pose has 23 degrees of freedom, the hand articulation tracking needs computational excessive burden in minimizing the 3D shape discrepancy between an observed hand and a 3D hand model. For this, we first created a 3D hand model which represents the hand with 17 different parts. Secondly, Random Forest classifier was trained on the synthetic depth images generated by animating the developed 3D hand model, which was then used for Haar-like feature-based classification rather than performing per-pixel classification. Classification results were used for estimating the joint positions for the hand skeleton. Through the experiment, we were able to prove that the proposed method showed improvement rates in hand part recognition and a performance of 20-30 fps. The results confirmed its practical use in classifying hand area and successfully tracked and recovered the 3D hand pose in a real time fashion.