• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.3955-3971
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• 2020

Due to the significant increase in the use of autonomous car technology, it is essential to integrate this technology with high-precision digital map data containing more precise and accurate roadway information, as compared to existing conventional map resources, to ensure the safety of self-driving operations. While existing map technologies may assist vehicles in identifying their locations via Global Positioning System, it is however difficult to update the environmental changes of roadways in these maps. Roadway vision algorithms can be useful for building autonomous vehicles that can avoid accidents and detect real-time location changes. We incorporate a hybrid architectural design that combines unsupervised classification of vision data with supervised joint fusion classification to achieve a better noise-resistant algorithm. We identify, via a deep learning approach, an intelligent hybrid fusion algorithm for fusing multimodal vision feature data for roadway classifications and characterize its improvement in accuracy over unsupervised identifications using image processing and supervised vision classifiers. We analyzed over 93,000 vision frame data collected from a test vehicle in real roadways. The performance indicators of the proposed hybrid fusion algorithm are successfully evaluated for the generation of roadway digital maps for autonomous vehicles, with a recall of 0.94, precision of 0.96, and accuracy of 0.92.

• Journal of Broadcast Engineering
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• v.19 no.1
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• pp.109-117
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• 2014

This paper presents a superresolution restoration technique that can restore high-resolution images from differently blurred low resolution images rather than using the motion information between low-resolution images. In order to restore the super-resolution image the rotatable aperture mask lens system is proposed. The proposed technique does not need to estimate point spread function at each frame. In addition, it does not require image registration because there is no global translational motion between low resolution images. By using a rotatable rectangular aperture, two consecutive captured images provide sufficiently exclusive information for superresolution. Therefore, the proposed method can reduce the registration error between the low-resolution image as well as the calculation amount for superresolution restoration. The existing lens system of the camera can be extended to obtain a superresolution image by only adding an rotatable rectangular aperture mask. Finally, in order to verify the performance of the proposed system, experimental results are performed. By comparing with the existing superresolution methods, the proposed method showed the significant improvements in the sense of spatial resolution.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.3
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• pp.49-56
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• 2009

Recently, a generation of high quality mosaic images from video sequences has been attempted by a variety of investigations. Among the matter of investigation, in this paper, generation on stereo mosaic utilizing airborne-video sequence images is focused upon. The stereo mosaic is made by creating left and right mosaic which are fabricated by front and rear slices having different viewing angle in consecutive video frames. For making the stereo mosaic, motion parameters which are able to define geometric relationship between consecutive video frames are determined. For determining motion parameters, affine model which is able to explain relative motion parameters is applied by this paper. The mosaicing method using relative motion parameters is called by free mosaic. The free mosaic proposed in this paper consists of 4 step processes: image registration with reference to first frame using affine model, front and rear slicing, stitching line definition and image mosaicing. As the result of experiment, the left and right mosaic image, anaglyphic image for stereo mosaic images are showed and analyzed y-parallax for checking accuracy.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.2
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• pp.49-56
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• 2008

Image registration is one of the critical techniques of image mosaic which has many applications such as generating panoramas, video monitoring, image rendering and reconstruction, etc. The fundamental tasks of image registration are point features extraction and tracking which take much computation time. KLT(Kanade-Lucas-Tomasi) feature tracker has proposed for extracting and tracking features through image sequences. The aim of this study is to demonstrate the usage of effective and robust KLT feature detector and tracker for an image registration using the sequence image frames captured by UAV video camera. In result, by using iterative implementation of the KLT tracker, the features extracted from the first frame of image sequences could be successfully tracked through all frames. The process of feature tracking in the various frames with rotation, translation and small scaling could be improved by a careful choice of the process condition and KLT pyramid implementation.

• Journal of Digital Contents Society
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• v.17 no.2
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• pp.89-96
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• 2016

SVC(Scalable Video Coding), which is one form among video encoding technologies, makes video streaming with the various frame rate, resolution, and video quality by combining three different scalability dimensions: temporal, spatial, and video quality scalability. As the above SVC-encoded video streaming consists of one base layer and several enhancement layers, and a wireless AP(Access Point) chooses and sends a suitable layer according to the received power from the receiving terminals in the changeable wireless network environment, the receiving terminals supporting SVC are able to receive video streaming with the appropriate resolution and quality according to their received powers. In this paper, after the performance analysis for the received power, packet loss rate, PSNR(Required Peak Signal to Noise Ratio), video quality level and amount of received video data based on the number of SVC layers was performed, an efficient method for selecting the number of SVC layer satisfying the RSNR and minimizing the amount of received video data is proposed.

• The Journal of Korea Robotics Society
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• v.13 no.2
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• pp.113-120
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• 2018

To fly a drone or unmanned aerial vechicle(UAV) safely, its pilot needs to maintain high situation awareness of its flight space. One of the important ways to improve the flight space awareness is to integrate both the global and the local navigation map a drone provides. However, the drone pilot often has to use the inconsistent reference frames or perspectives between the two maps. In specific, the global navigation map tends to display space information in the third-person perspective, whereas the local map tends to use the first-person perspective through the drone camera. This inconsistent perspective problem makes the pilot use mental rotation to align the different perspectives. In addition, integrating different dimensionalities (2D vs. 3D) of the two maps may aggravate the pilot's cognitive load of mental rotation. Therefore, this study aims to investigate the relation between perspective difference ($0^{\circ}$, $90^{\circ}$, $180^{\circ}$, $270^{\circ}$) and the map dimensionality matches (3D-3D vs. 3D-2D) to improve the way of integrating the two maps. The results show that the pilot's flight space awareness improves when the perspective differences are smaller and also when the dimensionalities between the two maps are matched.

• Journal of the Society of Naval Architects of Korea
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• v.42 no.6 s.144
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• pp.619-630
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• 2005

A two-frame PIV (Particle Image Velocimetry) technique is used to investigate the wake characteristics behind a marine propeller with 4 blades at high Reynolds number. For each of 9 different blade phases from $ 0^{\circ} $ to $ 80^{\circ} $, one hundred and fifty instantaneous velocity fields are measured. They are ensemble averaged to study the spatial evolution of the propeller wake in the region ranging from the trailing edge to one propeller diameter (D) downstream location. The phase-averaged mean velocity shows that the trailing vorticity is related to radial velocity jump, and the viscous wake is affected by boundary layers developed on the blade surfaces and centrifugal force. Both Galilean decomposition method and vortex identification method using swirling strength calculation are very useful for the study of vortex behaviors En the propeller wake legion. The slipstream contraction occurs in the near-wake region up to about X/D : 0.53 downstream. Thereafter, unstable oscillation occurs because of the reduction of interaction between the tip vortex and the wake sheet behind the maximum contraction point.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.6
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• pp.1-8
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• 2007

In this paper, research on joint optimization of the image spatial registration and the exposure compensation is conducted. The exposure compensation is performed in a frame work of the intensity compensation based on the polynomial approximation of the relationship between images. This compensation is jointly combined with the registration problem employing the Gauss-Newton nonlinear optimization method. In this paper, to perform for a simple and stable optimization, the block-coordinate method is combined with the Gauss-Newton optimization and extensively compared with the traditional approaches. Furthermore, regression analysis is considered in the compensation part for a better stable performance. By combining the block-coordinate method with the Gauss-Newton optimization, we can obtain a compatible performance reducing the computational complexity and stabilizing the performance. In the numerical result for a particular image, we obtain a satisfactory result for 10 repeats of the iteration, which implies a 50% reduction of the computational complexity. The error is also further reduced by 1.5dB compared to the ordinary method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.2C
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• pp.86-92
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• 2011

This paper details the downlink performance analysis of an multiple antennas system that combines adaptive beamforming and spatial multiplexing (SM) Multiple Input Multiple Output (MIMO). The combination of MIMO signal processing with adaptive beamforming is applied to WiBro, the South Korean Orthogonal Frequency Division Multiple Access (OFDMA) system that follows the IEEE 802.16e standard. Performance analysis is based on the results of experiments and simulations obtained from a fixed-point simulation testbed. Simulations demonstrate that the MIMO Beamforming OFDMA system improves the required signal to noise ratio (SNR) over the conventional MIMO OFDMA system by 3 dB (QPSK) / 2.5 dB (16-QAM) for the frame error rate (FER) of 1% in the WiBro signal environments. From the implementation of the fixed-point simulation testbed and its experimental results, we verify the feasibility of the MIMO Beamforming technology for realizing a practical WiBro base station.

• Journal of the Korea Society of Computer and Information
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• v.13 no.7
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• pp.99-108
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• 2008

For video compression, we have to consider two performance factors that are the search speed and coded video's quality. In this paper, we propose an enhanced fast block matching algorithm using the spatial correlation of the video sequence and the center-biased characteristic of motion vectors(MV). The proposed algorithm first finds a predicted motion vector from the adjacent macro blocks of the current frame and determines an exact motion vector using the cross pattern and a flat hexagon search pattern. From the performance evaluations, we can see that our algorithm outperforms both the hexagon-based search(HEXBS) and the cross-hexagon search(CHS) algorithms in terms of the search speed and coded video's quality. Using our algorithm, we can improve the search speed by up to 31%, and also increase the PSNR(Peak Signal Noise Ratio) by at most 0.5 dB, thereby improving the video quality.