• Journal of Broadcast Engineering
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• v.12 no.3
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• pp.278-288
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• 2007

We propose the fast full search algorithm that reduces the computational load of the block matching algorithm which is used for a motion estimation in the video coding. Since the conventional spiral search method starts searching at the center of the search window and then moves search point to estimate the motion vector pixel by pixel, it is good for the slow motion picture. However we proposed the efficient motion estimation method which is good for the fast and slow motion picture. Firstly, when finding the initial threshold value, we use the expanded predictor that can approximately calculate minimum threshold value. The proposed algorithm estimates the motion in the new search order after partitioning the search window and adapt the directional search order in the re-divided search window. At the result, we can check that the proposed algorithm reduces the computational load 94% in average compared to the conventional spiral full search algorithm without any loss of image quality.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.8
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• pp.81-95
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• 1996

In this paper, we propose a motio estiamtion algorithm using low-resolution quantization to reduce the computation of the full search algorithm. The proposed algorithm consists of the low-resolution search which determins the candidate motion vectors by comparing the low-resolution image and the full-resolution search which determines the motion vector by comparing the full-resolution image on the positions of the candidate motion vectors. The low-resolution image is generated by subtracting each pixel value in the reference block or the search window by the mean of the reference block, and by quantizing it is 2-bit resolution. The candidate motion vectors are determined by counting the number of pixels in the reference block whose quantized codes are unmatched to those in the search window. Simulation results show that the required computational cost of the proposed algorithm is reduced to 1/12 of the full search algorithm while its performance degradation is 0.03~0.12 dB.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.3
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• pp.636-644
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• 2015

This research aims to suggest methods to improve object tracking performance by combining CAM shift algorithm with 8-way search window, and reduce arithmetic operation by reducing the number of frame used for tracking. CAM shift has its adverse effect in tracking methods using signature color or having difficulty in tracking rapidly moving object. To resolve this, moving search window of CAM shift makes it possible to more accurately track high-speed moving object after finding object by conducting 8-way search by using information at a final successful timing point from a timing point missing tracking object. Moreover, hardware development led to increased unnecessary arithmetic operation by increasing the number of frame produced per second, which indicates efficiency can be enhanced by reducing the number of frame used in tracking to reduce unnecessary arithmetic operation.

• Journal of the Ergonomics Society of Korea
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• v.25 no.2
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• pp.23-32
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• 2006

Window buttons located on a task bar provide information about windows that have been open as well as active. When the number of buttons on the task bar increases, the button size gets smaller and as a result, it is more difficult to identify. This study proposes new alternatives of presenting window buttons to search for a target button efficiently. An experiment was conducted to evaluate the usability of the new. Factors manipulated in the experiment include 'button arrangement methods' and 'order of buttons'. The 'button arrangement methods' factor is composed of three levels, 'one line', 'changeable line', and 'grouping buttons'. The 'order of buttons' factor is composed of three levels, 'fixed order', 'click-right', and 'order control by user'. The results showed that the main effects were significant in search time. In subjective satisfaction, the interaction effect was also significant. The results could be applied to the design of small screens such as PDA or cellular phones.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1227-1232
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• 2015

Several works help make sliding window object detection fast, nevertheless, computational demands remain prohibitive for numerous applications. This paper proposes a fast object detection method based on three strategies: cascade classifier, selective window search and fast feature extraction. Experimental results show that the proposed method outperforms the compared methods and achieves both high detection precision and low computation cost. Our approach runs at 17ms per frame on 640×480 images while attaining state-of-the-art accuracy.

• Journal of the Korea Computer Industry Society
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• v.4 no.12
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• pp.953-964
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• 2003

In the block matching algorithm, search patterns of different shapes or sizes and the distribution of motion vectors have a large impact on both the searching speed and the image quality. In this paper, we propose a new fast block matching algorithm using the cross pattern and the flat-hexagon search pattern. Our algorithm first finds the motion vectors that are close to the center of search window using the cross pattern, and then lastly finds the other motion vectors that are not close to the center of search window using the flat-hexagon search pattern. Through experiments, compared with the hexagon-based search algorithm(HEXBS), the proposed cross pattern and flat-hexagonal pattern search algorithm(CFHPS ) improves about 0.2-6.2% in terms of average number of search point per motion vector estimation and improves about 0.02-0.31dB in terms of PSNR(Peak Signal to Noise Ratio).

• The Journal of the Acoustical Society of Korea
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• v.30 no.3
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• pp.123-128
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• 2011

In this paper, we propose the improved noise power estimation in speech enhancement under various noise environments. The previous MS algorithm tracking the minimum value of finite search window uses the optimal power spectrum of signal for smoothing and adopts minimum probability. From the investigation of the previous MS-based methods it can be seen that a fixed size of the minimum search window is assumed regardless of the various environment. To achieve the different search window size, we use the noise classification algorithm based on the Gaussian mixture model (GMM). Performance of the proposed enhancement algorithm is evaluated by ITU-T P.862 perceptual evaluation of speech quality (PESQ) under various noise environments. Based on this, we show that the proposed algorithm yields better result compared to the conventional MS method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.2
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• pp.207-217
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• 1993

In this paper, knowing a priori probability of phase offset between transmitted codes and reference codes in the receiver, we construct the state diagram of acquisition process of the direct sequence spread-spectrum communication system using the expanding window search. The scannings are performed from the cell with higher probability code epoch synchronization to that with lower one. We expand window size from initial value by r times of its previous size in each search, construct the corresponding the state diagrams, and derive average synchronization time using the Markov process and Mason's gain formula. Average synchronization times versus number of search n and detection probability $P_d$ are calculated.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.405-406
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• 2008

This paper presents a high performance 2D PE architecture for H.264 Motion Estimation(ME). While existing 2D PE architectures reuse the overlapped data of adjacent search windows scanned in 1 or 3-way, the new architecture scan adjacent windows and multiple paths instead of single raster and zigzag scanning of adjacent windows in 4 way(up,down,left,right). By reducing the redundant access factor by 1.4, the new 4-way search window improve the memory bandwidth by 70-58% compared with 1/3-way search window. With Altera Stratix-III implementation, the high performance 2D PE architecture deals with SD ($720{\times}480$) video of 2 reference frame, $48{\times}48$ search area and $16{\times}16$ macroblock by 30fps at 97.1MHz.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.1
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• pp.123-128
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• 2018

In this paper, we propose a multi-vehicle object detection algorithm using feature point matching that tracks efficient vehicle objects. The proposed algorithm extracts the feature points of the vehicle using the FAST algorithm for efficient vehicle object tracking. And True if the feature points are included in the image segmented into the 5X5 region. If the feature point is not included, it is processed as False and the corresponding area is blacked to remove unnecessary object information excluding the vehicle object. Then, the post processed area is set as the maximum search window size of the vehicle. And A minimum search window using the outermost feature points of the vehicle is set. By using the set search window, we compensate the disadvantages of the search window size of mean-shift algorithm and track vehicle object. In order to evaluate the performance of the proposed method, SIFT and SURF algorithms are compared and tested. The result is about four times faster than the SIFT algorithm. And it has the advantage of detecting more efficiently than the process of SUFR algorithm.