• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.7
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• pp.1672-1686
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• 2013

In this paper, we propose a hybrid super-resolution algorithm robust to cut-change. Existing single-frame based super-resolution algorithms are usually fast, but quantity of information for interpolation is limited. Although the existing multi-frame based super-resolution algorithms generally robust to this problem, the performance of algorithm strongly depends on motions of input video. Furthemore at boundary of cut, applying of the algorithm is limited. In the proposed method, we detect a define boundary of cut using cut-detection algorithm. Then we adaptively apply a single-frame based super-resolution method to detected cut. Additionally, we propose algorithms of normalizing motion vector and analyzing pattern of edge to solve various problems of existing super-resolution algorithms. The experimental results show that the proposed algorithm has better performance than other conventional interpolation methods.

• Journal of the Korea Society of Computer and Information
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• v.20 no.5
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• pp.13-20
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• 2015

In this paper, we propose an algorithm that can recognize not only the number of stretched fingers but also determination of attached fingers for extracting features required for hand gesture recognition. The proposed algorithm detects the hand area in the input image by the skin color range filter based on a color model and labeling, and then recognizes various hand gestures by extracting the number of stretched fingers and determination of attached fingers using curvature information extracted from outlines and feature points. Experiment results show that the recognition rate and the frame rate are similar to those of the conventional algorithm, but the number of gesture cases that can be defined by the extracted characteristics is about four times higher than the conventional algorithm, so that the proposed algorithm can recognize more various gestures.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2546-2566
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• 2016

This paper investigates an efficient transmission scheme for the remote wireless sensors to receive information which is rarely discussed in the integrated remote wireless sensor and multibeam satellite networks (IWSMSNs). The networks can be employed to exchange sensing information for emergency scenario, ocean scenario, and so on, which are isolated from available terrestrial networks. As the efficient transmission link is important to the IWSMSNs, we propose a hybrid full frequency (HFF) precoding by taking advantage of frequency reuse and multiple-input multiple-output (MIMO) precoding. Considering energy efficiency and sinks fairness are crucial to transmission link, thus the HFF precoding problems are formulated as transmit power minimization (TPM) and max-min fair (MMF) received signal to interference plus noise ratio (SINR) problems, which can be transformed to indefinite quadratic optimization programs. Then this paper presents a semi-definite programming (SDP) algorithm to solve the problems for the IWSMSNs. The promising potential of HFF for the real IWSMSNs is demonstrated through simulations.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.6
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• pp.468-476
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• 2002

The confidence of information from image processing depends on the original image quality. Enhancing the confidence by an algorithm has an essential limitation. Especially, road images are exposed to lots of noisy sources, which makes image processing difficult. We, in this paper, propose a FNN (fuzzy-neural network) capable oi deciding the quality of a road image prior to extracting lane-related information. According to the decision by the FNN, road images are classified into good or bad to extract lane-related information. A CDF (cumulative distribution function), a function of edge histogram, is utilized to construct input parameters of the FNN, it is based on the fact that the shape of the CDF and the image quality has large correlation. Input pattern vector to the FNN consists of ten parameters in which nine parameters are from the CDF and the other one is from intensity distribution of raw image. Correlation analysis shows that each parameter represents the image quality well. According to the experimental results, the proposed FNN system was quite successful. We carried out simulations with real images taken by various lighting and weather conditions and achieved about 99% successful decision-making.

• ETRI Journal
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• v.33 no.2
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• pp.184-193
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• 2011

Tailored for wireless local area networks, the present paper proposes a cross-layer resource allocation scheme for multiple-input multiple-output orthogonal frequency-division multiplexing systems. Our cross-layer resource allocation scheme consists of three stages. Firstly, the condition of sharing the subchannel by more than one user is studied. Secondly, the subchannel allocation policy which depends on the data packets' lengths and the admissible combination of users per subchannel is proposed. Finally, the bits and corresponding power are allocated to users based on a greedy algorithm and the data packets' lengths. The analysis and simulation results demonstrate that our proposed scheme not only achieves significant improvement in system throughput and average packet delay compared with conventional schemes but also has low computational complexity.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.3
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• pp.97-104
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• 2007

Adaptive echo canceller(AEC) has become an important component in speech communication systems, including mobile phones and speech recognition. In these applications, the acoustic echo path has a long impulse response. We propose a moving-averge least mean square(MVLMS) algorithm with a detection method for acoustic echo cancellation. Using, the result of the tests that used colored input models clearly shows that the MVLMS detection algorithm has convergence performance superior to the least mean square(LMS) detection algorithm alone. Although the computational complexity of the new MVLMS algorithm is only slightly greater than that of the standard LMS detection algorithm, the new algorithm confers a significant improvement in stability.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.9
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• pp.930-935
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• 2014

A Gabor filter is a linear filter used for edge detectionas frequency and orientation representations of Gabor filters are similar to those of the human visual system. In this thesis, we propose a pedestrian detection algorithm using a Gabor filter bank. In order to extract the features of the pedestrian, we use various image processing algorithms and data structure algorithms. First, color image segmentation is performed to consider the information of the RGB color space. Second, histogram equalization is performed to enhance the brightness of the input images. Third, convolution is performed between a Gabor filter bank and the enhanced images. Fourth, statistical values are calculated by using the integral image (summed area table) method. The calculated statistical values are used for the feature matrix of the pedestrian area. To evaluate the proposed algorithm, the INRIA pedestrian database and SVM (Support Vector Machine) are used, and we compare the proposed algorithm and the HOG (Histogram of Oriented Gradient) pedestrian detector, presentlyreferred to as the methodology of pedestrian detection algorithm. The experimental results show that the proposed algorithm is more accurate compared to the HOG pedestrian detector.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.1
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• pp.32-39
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• 2002

Vector quantization for image compression needs expensive encoding time to find the closest codeword to the input vector. This paper proposes a search algorithm for fast vector quantization encoding. Firstly, we derive a robust condition based on the efficient topological structure of the codebook to dramatically eliminate unnecessary matching operations from the search procedure. Then, we Propose a fast search algorithm using the elimination condition. Simulation results show that with little preprocessing and memory cost, the encoding time of the proposed algorithm is reduced significantly while the encoding quality remains the same with respect to the full search algorithm. It is also found that the Proposed algorithm outperforms the existing search algorithms.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.5
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• pp.432-437
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• 2008

This paper proposes a defect cell extraction algorithm for TFT-LCD auto-repair system. Auto defect search algorithm and automatic defect cell extraction method are very important for TFT-LCD auto repair system. In the previous literature[1], we proposed an automatic visual inspection algorithm of TFT-LCD. Based on the inspected information(defect size and defect axis, if defect exists) by the automatic search algorithm, defect cells should be extracted from the input image for the auto repair system. For automatic extraction of defect cells, we used a novel block matching algorithm and a simple filtering process in order to find a given reference point in the LCD cell. The proposed defect cell extraction algorithm can be used in all kinds of TFT-LCD devices by changing a stored template which includes a given reference point. Various experimental results show the effectiveness of the proposed method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.11-15
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• 2015

SSD(Solide State Disk) Memory is gradually replacing HDD(Hard Disk Drive) for high speed data input and output processing on Internet server system. In this paper, we proposed efficient data distribution storage algorithm in DRAM based SSD. And we did performance test for proposed algorithm and existing algorithm in the same server environment condition. The result of comparison of performance test is as fellows. Data backup processing time of proposed algorithm was reduced by half than that of existing algorithm.