• Journal of electromagnetic engineering and science
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• v.4 no.1
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• pp.23-29
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• 2004

In this paper we analyze convergence constraints and time constant of IT-LMS algorithm and derive a method of making it's time constant independent of signal power by using input variance estimation. The method for estimating the input variance is to use a single-pole low-pass filter(LPF) with common smoothing parameter value, θ. The estimator is with narrow bandwidth for large θ but with wide bandwidth for small θ. This small θ gives long term average estimation(low frequency) of the fluctuating input variance well as short term variations (high frequency) of the input power. In our simulations of multipath communication channel equalization environments, the method with large θ has shown not as much improved convergence speed as the speed of the original IT-LMS algorithm. The proposed method with small θ=0.01 reach its minimum MSE in 100 samples whereas the IT-LMS converges in 200 samples. This shows the proposed, tap-power normalized IT-LMS algorithm can be applied more effectively to digital wireless communication systems.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.54.2-54.2
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• 2019

Removing noise which occurs inevitably when taking image data has been a big concern. There is a way to raise signal-to-noise ratio and it is regarded as the only way, image stacking. Image stacking is averaging or just adding all pixel values of multiple pictures taken of a specific area. Its performance and reliability are unquestioned, but its weaknesses are also evident. Object with fast proper motion can be vanished, and most of all, it takes too long time. So if we can handle single shot image well and achieve similar performance, we can overcome those weaknesses. Recent developments in deep learning have enabled things that were not possible with former algorithm-based programming. One of the things is generating data with more information from data with less information. As a part of that, we reproduced stacked image from single shot image using a kind of deep learning, conditional generative adversarial network (cGAN). r-band camcol2 south data were used from SDSS Stripe 82 data. From all fields, image data which is stacked with only 22 individual images and, as a pair of stacked image, single pass data which were included in all stacked image were used. All used fields are cut in $128{\times}128$ pixel size, so total number of image is 17930. 14234 pairs of all images were used for training cGAN and 3696 pairs were used for verify the result. As a result, RMS error of pixel values between generated data from the best condition and target data were $7.67{\times}10^{-4}$ compared to original input data, $1.24{\times}10^{-3}$. We also applied to a few test galaxy images and generated images were similar to stacked images qualitatively compared to other de-noising methods. In addition, with photometry, The number count of stacked-cGAN matched sources is larger than that of single pass-stacked one, especially for fainter objects. Also, magnitude completeness became better in fainter objects. With this work, it is possible to observe reliably 1 magnitude fainter object.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.8B
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• pp.1518-1531
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• 1999

The reconstructed images from highly compressed MPEG or H.263 data have noticeable image degradations, such as blocking artifacts near the block boundaries, corner outliers at cross points of blocks, and ringing noise near image edges, because the MPEG or H.263 quantizes the transformed coefficients of 8$\times$8 pixel blocks. A post-processing algorithm has been proposed by authors to reduce quantization effects, such as blocking artifacts, corner outliers, and ringing noise, in MPEG-decompressed images. Our signal-adaptive post-processing algorithm reduces the quantization effects adaptively by using both spatial frequency and temporal information extracted from the compressed data. The blocking artifacts are reduced by one-dimensional (1-D) horizontal and vertical low pass filtering (LPF), and the ringing noise is reduced by two-dimensional (2-D) signal-adaptive filtering (SAF). A comparison study of the subjective quality evaluation using modified single stimulus method (MSSM), the objective quality evaluation (PSNR) and the computation complexity analysis between the signal-adaptive post-processing algorithm and the MPEG-4 VM (Verification Model) post-processing algorithm is performed by computer simulation with several MPEG-4 image sequences. According to the comparison study, the subjective image qualities of both algorithms are similar, whereas the PSNR and the comparison complexity analysis of the signal-adaptive post-processing algorithm shows better performance than the VM post-processing algorithm.

• Korean Journal of Computational Design and Engineering
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• v.2 no.4
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• pp.253-266
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• 1997

Pencil-curve machining, which is a single-pass ball-end milling along a concave edge on adie surface, is widely employed in die-surface machining. The cutter-path used for pencil-curve machining, which is the trajectory of the “ball-center point” of a ball-endmill sliding along a concave-edge region on the die surface, is called pencil-curve. Presented in the paper is a pencil-curve tracing algorithm in which “concave-type” sharp edges are computed from a “virtually digitized” model of the tool-envelope surface. The resulting “initial” pencil-cures are then refuted by applying a series of fairing operations. illustrative examples and methods for enhancing accuracy are also presented. The proposed pencil-curve tracing algorithm has been successfully implemented in a commercial CAM system specialized in die-machining and in the CAD/CAM system CATIA.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.137-140
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• 1996

Finding line segments in an intensity image has been one of the most fundamental issues in computer vision. In complex scenes, it is hard to detect the locations of point features. Line features are more robust in providing greater positional accuracy. In this paper we present a robust "line features extraction" algorithm which extracts line feature in a single pass without using any assumptions and constraints. Our algorithm consists of five steps: (1) edge scanning, (2) edge normalization, (3) line-blob extraction, (4) line-feature computation, and (5) line linking. By using edge scanning, the computational complexity due to too many edge pixels is drastically reduced. Edge normalization improves the local quantization error induced from the gradient space partitioning and minimizes perturbations on edge orientation. We also analyze the effects of edge processing, and the least squares-based method and the principal axis-based method on the computation of line orientation. We show its efficiency with some real images.al images.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.67 no.1
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• pp.42-46
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• 2018

In this paper, we propose fast object detection method of the cars by applying YOLOv2(You Only Look Once version 2) and UAVs (Unmanned Aerial Vehicles) while on the highway. We operated Darknet, OpenCV, CUDA and Deep Learning Server(SDX-4185) for our simulation environment. YOLOv2 is recently developed fast object detection algorithm that can detect various scale objects as fast speed. YOLOv2 convolution network algorithm allows to calculate probability by one pass evaluation and predicts location of each cars, because object detection process has simple single network. In our result, we could find cars on the highway area as fast speed and we could apply to the real time.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.5
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• pp.440-445
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• 2010

This paper proposes a single accelerometer sensor control algorithm to mobile inverted pendulum, generally called 'Segway', and evaluates the performance of this system comparing to the conventional ones. The commercialized 'Prototype Segway-PT' is initially considered as a next-generation transport vehicle. However, this robot is operated by three gyroscopes and two accelerometers to control the posture and speed, and it requires the complex signal processing for fusing the two sets of data. As the result of this, the growth rate of market size of 'Segway' is slow because of its high price mainly. In this paper, the mobile inverted pendulum is operated by a single accelerometer to simplify the control system to lower the price. Low pass filter is one of the good sensors to reducing the variation of an accelerometer, but it has time delay. This time delay disturbs real-time mobile inverted pendulum control. Like this, other various algorithms are used for this system, but each one has its own weak point. So this paper proposes a new filtering method, median filter and EKF. Median filter is used to image processing to reject impulse elements like salt and pepper noise. As the major performance evaluation parameter for the accelerometer, the high-frequency to low frequency ratio from FFT (Fast Fourier Transform) is used. Effectiveness of the proposed algorithms has been verified through the real experiments and the results are demonstrated.

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1480-1482
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• 2005

The major causes of power quality deterioration are harmonic current through semiconductor switching device, due to use of nonlinear loads such as diodes rectifier or thyristor rectifiers. In response to this concerns, this paper presents a new control method of single-phase active power filter(APF) for the compensation of harmonic current components in nonlinear loads. In order to make the complex calculation to be possible, the single-phase system that has two phases was made by constructing a imaginary second-phase giving time delay to load currents. In the conventional method, a imaginary-phase lagged to the load current T/4(here T is the fundamental cycle) was made. But in this proposed method, the new signal, which has the delayed phase through the filter, using the phase-delay property of low-pass filter, was used as the second phase. As this control method is applied to the system of single phase, an instantaneous calculation was done rather by using the rotating reference frames that synchronizes with source-frequency than by applying instantaneous reactive power theory that uses the conventional fixed reference frames.

• Journal of the HCI Society of Korea
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• v.1 no.1
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• pp.45-52
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• 2006

This paper presents an image-space algorithm to real-time collision detection, which is run completely by GPU. For a single object or for multiple objects with no collision, the front and back faces appear alternately along the view direction. However, such alternation is violated when objects collide. Based on these observations, the algorithm propose the depth peeling method which renders the minimal surface of objects, not whole surface, to find colliding. The Depth peeling method utilizes the state-of-the-art functionalities of GPU such as framebuffer object, vertexbuffer object, and occlusion query. Combining these functions, multi-pass rendering and context switch can be done with low overhead. Therefore proposed approach has less rendering times and rendering overhead than previous image-space collision detection. The algorithm can handle deformable objects and complex objects, and its precision is governed by the resolution of the render-target-texture. The experimental results show the feasibility of GPU-based collision detection and its performance gain in real-time applications such as 3D games.

• The Transactions of the Korean Institute of Power Electronics
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• v.20 no.2
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• pp.182-192
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• 2015

This study develops a digital control scheme with power factor correction for a front-end converter in an electric vehicle battery charger. The front-end converter acts as the boost-type switching-mode rectifier. The converter assumes the two roles of the battery charger, which include power factor control and robust charging performance. The proposed control scheme consists of a charging control algorithm and a grid current control algorithm. The scheme aims to obtain unity input power factor and robust performance. Based on the linear average model of the converter, a constant-current constant-voltage charging control algorithm that passes through only one proportional-integral controller and a current feed-forward path is proposed. In the current control algorithm, we utilized a second band pass filter, a single-phase phase-locked loop technique, and a duty-ratio feed-forward term to control the grid current to be in phase with the grid voltage and achieve pure sinusoidal waveform. Simulations and experiments were conducted to verify the effectiveness of the proposed control scheme, both simulations and experiments.