• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.39-44
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• 2022

This paper presents LiDAR static obstacle map based vehicle position correction algorithm for urban autonomous driving. Real Time Kinematic (RTK) GPS is commonly used in highway automated vehicle systems. For urban automated vehicle systems, RTK GPS have some trouble in shaded area. Therefore, this paper represents a method to estimate the position of the host vehicle using AVM camera, front camera, LiDAR and low-cost GPS based on Extended Kalman Filter (EKF). Static obstacle map (STOM) is constructed only with static object based on Bayesian rule. To run the algorithm, HD map and Static obstacle reference map (STORM) must be prepared in advance. STORM is constructed by accumulating and voxelizing the static obstacle map (STOM). The algorithm consists of three main process. The first process is to acquire sensor data from low-cost GPS, AVM camera, front camera, and LiDAR. Second, low-cost GPS data is used to define initial point. Third, AVM camera, front camera, LiDAR point cloud matching to HD map and STORM is conducted using Normal Distribution Transformation (NDT) method. Third, position of the host vehicle position is corrected based on the Extended Kalman Filter (EKF).The proposed algorithm is implemented in the Linux Robot Operating System (ROS) environment and showed better performance than only lane-detection algorithm. It is expected to be more robust and accurate than raw lidar point cloud matching algorithm in autonomous driving.

• Proceedings of the Korea Multimedia Society Conference
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• 2012.05a
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• pp.18-21
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• 2012

자동 백색 보정은 디지털 비디오 프로세싱에서 매우 중요한 기능이며, IP 네트워크 카메라의 경우에도 필수적인 영상 전처리 과정이다. 본 논문은 TI 사의 비디오 프로세서인 DM36x을 이용하여 제작된 HD IP 네트워크 카메라에서의 실시간으로 동작할 수 있는 효과적인 비디오 자동 백색 보정 알고리즘을 구현한 결과를 기술한다. 구현한 자동 백색 보정 알고리즘은 매우 효과적인 것으로 알려진 그레이 컬러 포인트 기반 알고리즘을 DM36x의 AWB 엔진이 제공하는 기능을 이용하여 실시간으로 동작될 수 있도록 고쳐서 구현하였다.

• Journal of Broadcast Engineering
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• v.7 no.3
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• pp.211-218
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• 2002

This paper introduces the HD 3DTV camera and 3DTV receiver that are compatible with the ATSC HDTV broadcasting system. The developed 3DTV camera is based on stereoscopic techniques, and it has control function to control both left and right zoom lens simultaneously and to control the vergence. Moreover, in order to control the vergence manually and to eliminate the synchronization problem of the both images, the 3DTV camera has the 3DTV video multiplexing function to combine the left and right images into the single image. The developed 3DTV signal, and it has the various analog/digital interfaces. The performance of the developed system is confirmed by shooting the selected soccer game in 2002 FIFA KOREA/JAPANTM World Cup and by broadcasting the match. The HD 3DTV camera and receiver will be applied to the 3DTV industries such as 3D movie, 3D game, 3D image processing, 3DTV broadcasting system, and so on.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.245-250
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• 2015

We have developed an optical video transmission device for HD-SDI signal transmission. The optical transmitter/receiver unit operates at DC 5 volt and small enough to be attaced near surveillance camera. They have internal voltage regulating circuits to supply 3.3V to other circuits inside the unit. The optical transmitter is composed of cable driver, laser diode driver, and laser diode. The optical receiver is composed of photodiode, limiting amp, and cable equalizer. The wavelength of the trasmitter was 1.3 um, and optical power was -5dBm, and the speed was 1.485Gbps. The receiver sensitivity was -23 dBm. We confirmed that the optical device can transmit HD-SDI video through 30 km optical fiber without any interruption.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.10a
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• pp.763-764
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• 2013

A three-dimensional image capturing device and its signal processing algorithm and apparatus are presented. Three dimensional information is one of emerging differentiators that provides consumers with more realistic and immersive experiences in user interface, game, 3D-virtual reality, and 3D display. It has the depth information of a scene together with conventional color image so that full-information of real life that human eyes experience can be captured, recorded and reproduced. 20 Mega-Hertz-switching high speed image shutter device for 3D image capturing and its application to system prototype are presented[1,2]. For 3D image capturing, the system utilizes Time-of-Flight (TOF) principle by means of 20MHz high-speed micro-optical image modulator, so called 'optical resonator'. The high speed image modulation is obtained using the electro-optic operation of the multi-layer stacked structure having diffractive mirrors and optical resonance cavity which maximizes the magnitude of optical modulation[3,4]. The optical resonator is specially designed and fabricated realizing low resistance-capacitance cell structures having small RC-time constant. The optical shutter is positioned in front of a standard high resolution CMOS image sensor and modulates the IR image reflected from the object to capture a depth image (Figure 1). Suggested novel optical resonator enables capturing of a full HD depth image with depth accuracy of mm-scale, which is the largest depth image resolution among the-state-of-the-arts, which have been limited up to VGA. The 3D camera prototype realizes color/depth concurrent sensing optical architecture to capture 14Mp color and full HD depth images, simultaneously (Figure 2,3). The resulting high definition color/depth image and its capturing device have crucial impact on 3D business eco-system in IT industry especially as 3D image sensing means in the fields of 3D camera, gesture recognition, user interface, and 3D display. This paper presents MEMS-based optical resonator design, fabrication, 3D camera system prototype and signal processing algorithms.

• Journal of information and communication convergence engineering
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• v.8 no.1
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• pp.51-58
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• 2010

This paper proposes an edge adaptive color interpolation for an ultra-small HD-grade complementary metal-oxide semiconductor (CMOS) video sensor in camera phones that can process 720-p/30-fps videos. Recently, proposed methods with great image quality perceptually reconstruct the green component and then estimate the red/blue component using the reconstructed green and neighbor red and blue pixels. However, these methods require the bulky memory line buffers in order to temporally store the reconstructed green components. The edge adaptive color interpolation method uses seven or nine patterns to calculate the six edge directions. At the same time, the threshold values are adaptively adjusted by the sum of the color values of the selected pixels. This method selects the suitable one among the patterns using two flowcharts proposed in this paper, and then interpolates the missing color values. For verification, we calculated the peak-signal-to-noise-ratio (PSNR) in the test images, which were processed by the proposed algorithm, and compared the calculated PSNR of the existing methods. The proposed color interpolation is also fabricated with the 0.18-${\mu}m$ CMOS flash memory process.

• Journal of information and communication convergence engineering
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• v.7 no.4
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• pp.507-515
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• 2009

In this paper, we propose an image signal processor (ISP) for an ultra small HD-grade video sensor with 3A (AWB, AE, and AF) in camera phones that can process 720P/30fps videos. In order to enhance the video quality of the systems, it is necessary to achieve the high performance of the 3A. The proposed AWB algorithm multiplies the adjusted coefficients of color gains to the captured data of white objects. The proposed AE method adopts the index step moving based on the difference between an averaged Y luminance and a target luminance, together with IIR filters with variable time responses. The proposed AF technique controls the focus curve to find the lens position that maximizes the integrated high frequency components in luminance values by using highpass filters. Finally, we compare the image quality captured from our system to the quality of a commercial HD camcorder in order to evaluate the performance of the proposed ISP. The proposed ISP system is also fabricated with 0.18um CMOS flash memory process.

• Journal of Internet Computing and Services
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• v.17 no.4
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• pp.11-17
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• 2016

In this paper, we proposed a multi-viewer system with multiple HD cameras based AVB(Audio Video Bridge) ethernet cable using IP networking, and FPGA(Xilinx Zynq 702) for bus safety systems. This AVB (IEEE802.1BA) system can be designed for the low latency based on FPGA, and transmit real-time with HD video and audio signals in a vehicle network. The proposed multi-viewer platform can multiplex H.264 video signals from 4 wide-angle HD cameras with existed ethernet 1Gbps. and 2-wire 100Mbps cables. The design of Zynq 702 based low latency to H.264 AVC CODEC was proposed for the minimization of time-delay in the HD video transmission of car area network, too. And the performance of PSNR(Peak Signal-to-noise-ratio) was analyzed with the reference model JM for encoding and decoding results in H.264 AVC CODEC. These PSNR values can be confirmed according the theoretical and HW result from the signal of H.264 AVC CODEC based on Zynq 702 the multi-viewer with multiple cameras. As a result, proposed AVB multi-viewer platform with multiple cameras can be used for the surveillance of audio and video around a bus for the safety due to the low latency of H.264 AVC CODEC design.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1095-1109
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• 2021

The technology used to recognize the location and surroundings of autonomous vehicles is called SLAM. SLAM standsfor Simultaneously Localization and Mapping and hasrecently been actively utilized in research on autonomous vehicles,starting with robotic research. Expensive GPS, INS, LiDAR, RADAR, and Wheel Odometry allow precise magnetic positioning and mapping in centimeters. However, if it can secure similar accuracy as using cheaper Cameras and GPS data, it will contribute to advancing the era of autonomous driving. In this paper, we present a method for converging monocular camera with RTK-enabled GPS data to perform RMSE 33.7 cm localization and mapping on the urban road.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1163-1175
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• 2021

In autonomous driving, road markings are an essential element for object tracking, path planning and they are able to provide important information for localization. This paper presents an approach to update and measure road surface markers with HD maps as well as matching using inverse perspective mapping. The IPM removes perspective effects from the vehicle's front camera image and remaps them to the 2D domain to create a bird-view region to fit with HD map regions. In addition, letters and arrows such as stop lines, crosswalks, dotted lines, and straight lines are recognized and compared to objects on the HD map to determine whether they are updated. The localization of a newly installed object can be obtained by referring to the measurement value of the surrounding object on the HD map. Therefore, we are able to obtain high accuracy update results with very low computational costs and low-cost cameras and GNSS/INS sensors alone.