• Convergence Security Journal
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• v.12 no.6
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• pp.31-37
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• 2012

Today, the core technology of an automobile is becoming to IT-based convergence system technology. To cope with many kinds of situations and provide the convenience for drivers, various IT technologies are being integrated into automobile system. In this paper, we propose an convergence system, which is called Augmented Driving System (ADS), to provide high safety and convenience of drivers based on image information processing. From imaging sensor, the image data is acquisited and processed to give distance from the front car, lane, and traffic sign panel by the proposed methods. Also, a converged interface technology with camera for gesture recognition and microphone for speech recognition is provided. Based on this kind of system technology, car accident will be decreased although drivers could not recognize the dangerous situations, since the system can recognize situation or user context to give attention to the front view. Through the experiments, the proposed methods achieved over 90% of recognition in terms of traffic sign detection, lane detection, and distance measure from the front car.

• 전자공학회논문지 IE
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• v.43 no.2
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• pp.63-69
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• 2006

Islanding phenomenon of utility-connected PV power conditioning systems(PV PCS) can cause a variety of problems and must be prevented. If the real and reactive powers supplied by PV PCS are closely matched to those of load, islanding detection by passive methods becomes difficult. The active frequency drift(AFD) method, called the frequency bias method, enables islanding detection by forcing the frequency of the voltage in the islanding to drift up or down. In this paper, non-detection zone(NDZ) of AFD is analyzed for the islanding detection method of utility-connected PV PCS by simulation tool PSIM.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.8
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• pp.97-105
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• 2015

Content-adaptive steganography methods embed secret messages in hard-to-model regions of covers such as complicated texture or noisy area. Content-adaptive steganalysis methods often need high dimensional features to capture more subtle relationships of local dependencies among adjacent pixels. However, these methods require many computational complexity and depend on the location of hidden message and the exploited distortion metrics. In this paper, we propose an improved steganalysis method for content-adaptive steganography to enhance detection rate with small number features. We first show that the features form the difference between DCT coefficients are useful for analyzing the content-adaptive steganography methods, and present feature extraction mehtod using first-order Markov probability for the the difference between DCT coefficients. The extracted features are used as input of ensemble classifier. Experimental results show that the proposed method outperforms previous schemes in terms of detection rates and accuracy in spite of a small number features in various content-adaptive stego images.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.10B
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• pp.1233-1239
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• 2011

The visible light convergence communication technology is suitable for indoor wireless communication and digital lighting fixtures, it could be used as lighting devices as well as a communication device. However, because that VLC is the technology of came to world a few years ago, there are many problems which had to solve. The signal sensing of VLC transmitter is one of the most challenging issue in VLC systems. Therefore in this paper, we analysis the performance of various sensing scheme for efficient detection of VLC systems. The signal of user is OFDM signal and the wirelss channel between a user and VLC system is modeled as indoor VLC channel. From the simulation results, it is confirmed that the proposed scheme is very effective to signal sensing for VLC systems.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.7
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• pp.50-61
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• 1999

\In this paper, we consider the optimal scheduling of detection and tracking parameters in phased array radars to minimize the radar energy required for track maintenance in a cluttered environment. We develop a mathematical model of target detection induced by a search process in phased array radars. In the mathematical development, we take into account the effect of unwanted measurements that may have originated from clutter or false alarms in the detection process. We use and analytic approximation of the modified Riccati equation of the probabilistic data association (PDA) filter to take into account the effect of clutter interference in tracking. Based on the search process and the tracking models, we formulate the optimal scheduling problem into a nonlinear optimal control problem. We solve a constrained nonlinear optimization problem to obtain the solution of the optimal control problem.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.1149-1152
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• 2005

Detecting faces in images with complex backgrounds is a difficult task. Our approach, which obtains state of the art results, is based on a generative neural network model: the Constrained Generative Model (CGM). To detect side view faces and to decrease the number of false alarms, a conditional mixture of networks is used. To decrease the computational time cost, a fast search algorithm is proposed. The level of performance reached, in terms of detection accuracy and processing time, allows to apply this detector to a real word application: the indexation of face images on the Web.

• Journal of Satellite, Information and Communications
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• v.6 no.2
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• pp.72-77
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• 2011

Spectrum sensing is a critical functionality of CR network; it allow secondary user to detect spectral holes and to opportunistically use under-utilized frequency bands without causing harmful interference to primary use. Recently, wideband service has been increase for processing abundance of data traffic. So CR network needs a realizable implementation design of spectrum sensing for wideband. To get high resolution performance of wideband sensing must precede algorithm processing for reliability signal detection. By the way, the performance of spectrum sensing can be degraded due to fading and shadowing. In order to overcome this problem, we propose system model of wideband sensing scheme on energy detected collaborative technique. we divide wideband into narrowbands and use narrowbands to detect signal excepting some narrowbands including bad channel through the CSI. And we simulate and analyze in terms of detection probability with various SNR.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.1
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• pp.27-36
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• 2019

In this paper, we propose a method to find the most similar answer to the user's response from the question-answer database in order to avoid generating a redundant question in retrieval-based automatic question generation system. As a question of the most similar answer to user's response may already be known to the user, the question should be removed from a set of question candidates. A similarity detector calculates a similarity between two answers by utilizing the same words, paraphrases, and sentential meanings. Paraphrases can be acquired by building a phrase table used in a statistical machine translation. A sentential meaning's similarity of two answers is calculated by an attention-based convolutional neural network. We evaluate the accuracy of the similarity detector on an evaluation set with 100 answers, and can get the 71% Mean Reciprocal Rank (MRR) score.

• The Journal of Korean Institute of Information Technology
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• v.17 no.6
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• pp.9-16
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• 2019

Companies that want to improve their manufacturing processes have recently introduced the smart factory, which is particularly noticeable. The ultimate goal is to maximize the area of the smart factory that performs the process of the production facility completely with minimal manual control and to minimize errors of reasoning. This research is a part of a project for unmanned production, management, packaging, and delivery management and the detection of the start point of rebars to perform the automatic calibration of the rollers through the tracking of the automated facilities of unmanned production. It must meet the requirement to accurately track the position from the start point to the end point. In order to improve the tracking performance, it is important to set the accurate start point. However, the probability of tracking errors is high depending on environments such as illumination and dust through the conventional time-based detection method. In this paper, we propose a starting point detection method using the average brightness change of high speed IR camera to reduce the errors according to the environments, As a result, its performance is improved by more than 15%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.12C
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• pp.1200-1208
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• 2003

Affective computing plays an important role in intelligent Human Computer Interactions(HCI). To detect emotional events, it is desirable to construct a computing model for extracting emotion related features from video. In this paper, we propose a statistical model based on the probabilistic distribution of low level features in video shots. The proposed method extracts low level features from video shots and then from a GMM(Gaussian Mixture Model) for them to detect emotional shots. As low level features, we use color, camera motion and sequence of shot lengths. The features can be modeled as a GMM by using EM(Expectation Maximization) algorithm and the relations between time and emotions are estimated by MLE(Maximum Likelihood Estimation). Finally, the two statistical models are combined together using Bayesian framework to detect emotional events in video.