• Journal of Korea Multimedia Society
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• v.5 no.2
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• pp.176-190
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• 2002

According as vehicles increases, system such as Advanced Drivers Assistance System(ADAS ) to inform forward situation to driver is required. In this paper, we proposes method to detect forward vehicles and lane from sequential color images by basis process to inform forward situation to driver. We detect a front vehicle using that shadow area exists on part under vehicles and that road area occupies many parts even if road traffic is confused. We detect lane information using that lane part is white order by reverse characteristic of shadow area. This method shows good result in case road is confused or there is direction indication to road. HSV color space is selected for color modeling. This method uses saturation component and value component in HSV color model to detect vehicles and lane. It uses statistics features of HSV component and position to know whether detected vehicles area is vehicles such as vehicles previous frame. To verify the effects of the proposed method, we capture the road images with notebook and CCD camera for PC and Present the results such as processing time, accuracy and vehicles detection against the images.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.1
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• pp.56-63
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• 2003

This paper introduces a vision based autonomous mini mobile robot that is an approach to produce real autonomous vehicle. Previous autonomous vehicles are dependent on PC, because of complexity of designing hardware, difficulty of installation and abundant calculations. In this paper, we present an autonomous motile robot system that has abilities of accurate steering, quick movement in high speed and intelligent recognition as a stand-alone system using a mono camera. The proposed system has been implemented on mini track of which width is 25~30cm, and length is about 200cm. Test robot can run at average 32.9km/h speed on straight lane and average 22.3km/h speed on curved lane with 30~40m radius. This system provides a model of autonomous mobile robot adapted a lane recognition algorithm in odor to make real autonomous vehicle easily.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.6
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• pp.536-541
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• 2015

In this paper, we propose a the image-based automatic flight control system for the mini drone. Automatic flight system with a camera on the ceiling and markers on the floor and landing position is designed in an indoor environment. Images from the ceiling camera is used not only to recognize the makers and landing position but also to track the drone motion. PC sever identifies the location of the drone and sends control commands to the mini drone. Flight controller of the mini drone is designed using state-machine algorithm, PID control and way-point position control method. From the, The proposed automatic flight control system is verified through the experiments of the mini drone. We see that known makers in environment are recognized and the drone can follows the trajectories with the specific ㄱ, ㄷ and ㅁ shapes. Also, experimental results show that the drone can approach and correctly land on the target positions which are set at different height.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.751-753
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• 2017

In this paper, we implement remote training kit using camera, Arduino and AVR practice kit so that AVR practice kit can be practiced remotely. Implemented systems can be practiced by a large number of users one at a time from a remote location. The practitioner creates the AVR Studio program using the PC remote control method and downloads it to the AVR training kit. When a computer program is created and a mouse is clicked or dragged, the input signal is transmitted to the Arduino and the Arduino transmits the actual button input signal or the analog voltage to the AVR kit. When the AVR kit is activated by receiving the input signal, you can check the operation through the camera. Therefore, using the implemented system, a plurality of users can perform AVR training using one kit.

• 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.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.341-350
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• 2022

In this paper, we propose a deep learning based on-device augmented reality (AR) system in which multiple input images are used to implement the correct occlusion in a real environment. The proposed system is composed of three technical steps; camera pose estimation, depth estimation, and object augmentation. Each step employs various mobile frameworks to optimize the processing on the on-device environment. Firstly, in the camera pose estimation stage, the massive computation involved in feature extraction is parallelized using OpenCL which is the GPU parallelization framework. Next, in depth estimation, monocular and multiple image-based depth image inference is accelerated using the mobile deep learning framework, i.e. TensorFlow Lite. Finally, object augmentation and occlusion handling are performed on the OpenGL ES mobile graphics framework. The proposed augmented reality system is implemented as an application in the Android environment. We evaluate the performance of the proposed system in terms of augmentation accuracy and the processing time in the mobile as well as PC environments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.4
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• pp.2363-2369
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• 2014

The DVR system supports multiple cameras and should be able to receive images at 30 frames per channel in real time. Thus, The system is using Full-HD-grade Multiplexer and Hardware compression codec. In this paper, Describing the design and implementation for the 4-channel Full-HD-grade PC-based DVR using FPGA and GPU inside CPU without Multiplexer and Hardware codec. The existing DVR system for Full-HD-grade has drawbacks to acquire images of about only 20 frames per channel in real time. The system to acquire images of multiple channel in real time was designed using FPGA. The software for the system was implemented using Intel Media SDK. At the result of performance evaluation, It was satisfied all for the required conditions. The practicality of the system was confirmed as implementation the system without using hardware compression.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.39 no.2
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• pp.7-13
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• 2002

When a USB digital camera is used for PC video-conference applications, motion picture data need to be transferred to the PC through the USB port. Due to the mismatch between the data rates of the USB and the motion picture, data compression should be performed before the transmission from the USB. While many motion picture compression algorithms require large intermediate memory space, the JPEG algorithm does not need to store an entire frame for the compression. Instead, a relatively small buffer is required at the input of the JPEG compression engine to resolve the inconsistency between the orders of the inputted data and the consumed data. Data reordering can be easily implemented using a double buffering scheme, which still requires a considerable size of memory. In this paper, a novel memory management scheme is proposed to avoid the double buffering. The proposed memory architecture requires a small amount of memory and a simple address generation scheme, resulting in overall cost reduction.

• Journal of Astronomy and Space Sciences
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• v.24 no.4
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• pp.367-378
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• 2007

We present a software which we developed for the multi-purpose CCD camera. This software can be used on the all 3 types of CCD - KAF-0401E ($768{\times}512$), KAF-1602E ($1536{\times}1024$), KAF-3200E ($2184{\times}1472$) made in KODAK Co.. For the efficient CCD camera control, the software is operated with two independent processes of the CCD control program and the temperature/shutter operation program. This software is designed to fully automatic operation as well as manually operation under LINUX system, and is controled by LINUX user signal procedure. We plan to use this software for all sky survey system and also night sky monitoring and sky observation. As our results, the read-out time of each CCD are about 15sec, 64sec, 134sec for KAF-0401E, KAF-1602E, KAF-3200E., because these time are limited by the data transmission speed of parallel port. For larger format CCD, the data transmission is required more high speed. we are considering this control software to one using USB port for high speed data transmission.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.2
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• pp.45-56
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• 2015

In this paper we propose a very rapid moving object tracking method for an object-based auto focus on a smart phone camera. By considering the limit of non-learning approach on low-performance platforms, we use a sliding-window detection technique based on histogram features. By adapting the integral histogram, we solve the problem of the time-consuming histogram computation on each sub-window. For more speed up, we propose a local candidate search, and an adaptive scaling template method. In addition, we propose to apply a stabilization term in the matching function for a stable detection location. In experiments on our dataset, we demonstrated that we achieved a very rapid tracking performance demonstrating over 100 frames per second on a PC environment.