• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.1153-1154
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• 2006

This paper proposes the optimal design method based on NDZ analysis to secure the islanding defection ability and to maintain the stability and power quality when the grid is connected. A PSiM-based model and analysis of the system is presented, specialty aimed at improving the effectiveness of phase shift anti-islanding method with frequency feedback, which causes the inverter current to be generated slightly lower or higher in frequency than the frequency of the terminal voltage. The proposed method can cause frequency jump with leading and lagging phase of output current in two line cycles. As a result, the proposed algorithm is more sensitive and reliable than the conventional phase shift method. Experimental results, on a 3 kW inverter connected to 220 V, 60 Hz utility, are discussed.

• ETRI Journal
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• v.34 no.3
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• pp.399-409
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• 2012

In this paper, we propose a new color histogram model for object tracking. The proposed model incorporates the color arrangement of the target that encodes the relative spatial distribution of the colors inside the object. Using the color arrangement, we can determine which color bin is more reliable for tracking. Based on the proposed color histogram model, we derive a mean shift framework using a modified Bhattacharyya distance. In addition, we present a method of updating an object scale and a target model to cope with changes in the target appearance. Unlike conventional mean shift based methods, our algorithm produces satisfactory results even when the object being tracked shares similar colors with the background.

• Korean Journal of Remote Sensing
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• v.24 no.3
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• pp.235-243
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• 2008

Object tracking is a common vision task to detect and trace objects between consecutive frames. It is also important for a variety of applications such as surveillance, video based traffic monitoring system, and so on. An efficient moving vehicle clustering and tracking algorithm suitable for traffic monitoring system is proposed in this paper. First, automatic background extraction method is used to get a reliable background as a reference. The moving blob(object) is then separated from the background by mean shift method. Second, the scale invariant feature based method extracts the salient features from the clustered foreground blob. It is robust to change the illumination, scale, and affine shape. The simulation results on various road situations demonstrate good performance achieved by proposed method.

• Journal of Korea Multimedia Society
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• v.24 no.10
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• pp.1319-1325
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• 2021

It is important to remove fog for accurate object recognition and detection during preprocessing because images taken in foggy adverse weather suffer from poor quality of images due to scattering and absorption of light, resulting in poor performance of various vision-based applications. This paper proposes an end-to-end deep learning-based single image de-fogging method using U-Net architecture. The loss function used in the algorithm is a loss function based on Mahalanobis distance with fog features, which solves the problem of domain shifts, and demonstrates superior performance by comparing qualitative and quantitative numerical evaluations with conventional methods. We also design it to generate fog through the VGG19 loss function and use it as the next training dataset.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.29A no.11
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• pp.62-69
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• 1992

In this paper, a measurement system of surface flatness test using 2-Bucket algorithm phase-shifting interferometry is designed and constructed. In the conventional surface flatness test system using phase shifting interferometry, it is needed more than 3 fringe datas but we propose 2-Bucket algorithm phase-shifting interferometry which only uses two fringe datas. 2-Bucket algorithm uses the relative phase differences of the neighbour pixels. If we watch the result of phase-shift error test simulation, 2-Bucket algorithm has the same calculating values that 3-Bucket, 4-Bucket and 5-Bucket algorithm have them. Experiments have been carried out on the silicon wafer. The measurement of silicon wafer's surface flatness shows that the flatness topography using 2-Bucket algorithm is similar to that of other algorithms.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.3
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• pp.38-47
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• 2008

A vehicle counting system at intersection is designed and implemented using analyzing a video stream from a camera. To separate foreground image from background, we compare three different methods, among which Li's method is chosen. Blobs are extracted from the foreground image using connected component analysis and the blobs are tracked by a blob tracker, frame by frame. The primary tracker use only the size and location of blob in foreground image. If there is a collision between blobs, the mean-shift tracking algorithm based on color distribution of blob is used. The proposed system is tested using real video data at intersection. If some huristics is applied, the system shows a good detection rate and a low error rate.

• Proceedings of the Korea Contents Association Conference
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• 2003.11a
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• pp.303-307
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• 2003

In this paper, the W(ultra widebend) system is used for high speed transmission applying BPSK(Binary Phase Shift Keying) and QPSK (Quadrature Phase Shift Keying), and utilizing the convolution coding with code rate, 1/2 and constraint length, K=7 in order to reduce the bit error rate. And the performance of system is analyzed in the AWGN(Additive White Gaussian Noise) channel environment by using the Viterbi decoding algorithm and adopting the time-hopping sequence as a multiple access method in order to avoid the multiuser interference.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.4
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• pp.137-146
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• 2023

The dropout of university freshmen is a very important issue in the financial problems of universities. Moreover, the dropout rate is one of the important indicators among the external evaluation items of universities. Therefore, universities need to predict dropout students in advance and apply various dropout prevention programs targeting them. This paper proposes a method to predict such dropout students in advance. This paper is about a method for predicting dropout students. It proposes a method to select dropouts by applying logistic regression using a shift sigmoid classification function using only quantitative data from the first semester of the first year, which most universities have. It is based on logistic regression and can select the number of prediction subjects and prediction accuracy by using the shift sigmoid function as an classification function. As a result of the experiment, when the proposed algorithm was applied, the number of predicted dropout subjects varied from 100% to 20% compared to the actual number of dropout subjects, and it was found to have a prediction accuracy of 75% to 98%.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.164-167
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• 2002

This paper presents the design of Rijndael crypto-processor with 128 bits, 192 bits and 256 bits key size. In October 2000 Rijndael cryptographic algorithm is selected as AES(Advanced Encryption Standard) by NIST(National Institute of Standards and Technology). Rijndael algorithm is strong in any known attacks. And it can be efficiently implemented in both hardware and software. We implement Rijndael algorithm in hardware, because hardware implementation gives more fast encryptioN/decryption speed and more physically secure. We implemented Rijndael algorithm for 128 bits, 192 bits and 256 bits key size with VHDL, synthesized with Synopsys, and simulated with ModelSim. This crypto-processor is implemented using on-the-fly key generation method and using lookup table for S-box/SI-box. And the order of Inverse Shift Row operation and Inverse Substitution operation is exchanged in decryption round operation of Rijndael algorithm. It brings about decrease of the total gate count. Crypto-processor implemented in these methods is applied to mobile systems and smart cards, because it has moderate gate count and high speed.

• Journal of Korea Multimedia Society
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• v.6 no.4
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• pp.610-619
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• 2003

This paper presents a concept of cellular automata and a modular exponentiation algorithm and implementation of a basic EIGamal encryption by using cellular automata. Nowadays most of modular exponentiation algorithms are implemented by a linear feedback shift register(LFSR), but its structure has disadvantage which is difficult to implement an operation scheme when the basis is changed frequently The proposed algorithm based on a cellular automata in this paper can overcome this shortcomings, and can be effectively applied to the modular exponentiation algorithm by using the characteristic of the parallelism and flexibility of cellular automata. We also propose a new fast multiplier algorithm using the normal basis representation. A new multiplier algorithm based on normal basis is quite fast than the conventional algorithms using standard basis. This application is also applicable to construct operational structures such as multiplication, exponentiation and inversion algorithm for EIGamal cryptosystem.