• The KIPS Transactions:PartB
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• v.11B no.6
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• pp.653-660
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• 2004

Object-oriented analysis-synthesis coding (OOASC) subdivides each image of a sequence into a number of moving objects and estimates and compensates the motion of each object. It employs a motion parameter technique for estimating motion information of each object. The motion parameter technique employing gradient operators requires a high computational load. The main objective of this paper is to present efficient motion parameter estimation techniques using the hierarchical structure in object-oriented analysis-synthesis coding. In order to achieve this goal, this paper proposes two algorithms : hybrid motion parameter estimation method (HMPEM) and adaptive motion parameter estimation method (AMPEM) using the hierarchical structure. HMPEM uses the proposed hierarchical structure, in which six or eight motion parameters are estimated by a parameter verification process in a low-resolution image, whose size is equal to one fourth of that of an original image. AMPEM uses the same hierarchical structure with the motion detection criterion that measures the amount of motion based on the temporal co-occurrence matrices for adaptive estimation of the motion parameters. This method is fast and easily implemented using parallel processing techniques. Theoretical analysis and computer simulation show that the peak signal to noise ratio (PSNR) of the image reconstructed by the proposed method lies between those of images reconstructed by the conventional 6- and 8-parameter estimation methods with a greatly reduced computational load by a factor of about four.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.3
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• pp.217-222
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• 2015

Clustering is one of important data mining techniques known as exploratory data analysis and is being applied in various engineering and scientific fields such as pattern recognition, remote sensing, and so on. The method organizes data by abstracting underlying structure either as a grouping of individuals or as a hierarchy of groups. Weather radar observes atmospheric objects by utilizing reflected signals and stores observed data in corresponding coordinate. To analyze the radar data, it is needed to be separately organized precipitation and non-precipitation echo based on similarities. Thus, this paper studies to apply clustering method to radar data. In addition, in order to solve the problem when precipitation echo locates close to non-precipitation echo, fuzzy logic based clustering method which can consider both distance and other properties such as reflectivity and Doppler velocity is suggested in this paper. By using actual cases, the suggested clustering method derives better results than previous method in near-located precipitation and non-precipitation echo case.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.3
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• pp.557-565
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• 2015

Sea level rise due to global warming causes seawater intrusion into aquifers in coastal areas. Seawater intrusion vulnerability index was developed using PSR (Pressure, State, Response) model and analysis hierarchy process (AHP). Coastal regions in Korea, Gangwon-do Sokcho-si, Incheon-si Ganghwa-gun, Chungcheongnam-do Taean-gun, Jeollanam-do Yeosu-si, Jindo-gun were chosen and 14 indicators were selected by considering the humanities, economic, social, environmental aspects. Re-scaling method was used for the standardization of indices and questionnaire survey was performed to calculate weight values for each index. The results showed that Yeosu-si was selected as the most vulnerable region to seawater intrusion. The seawater intrusion index developed in this research can be used to analyze the vulnerable regions to seawater intrusion and to establish a policy to minimize the seawater intrusion problems in coastal regions.

• Spatial Information Research
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• v.20 no.4
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• pp.93-101
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• 2012

Due to complexity of indoor space, the demand of Location Based Services (LBS) in indoor space is increasing as well as outdoor. However, it includes privacy problems of exposing personal location. Location K-anonymity technology is a method to solve the privacy problems with cloaking their locations by Anonymized Spatial Region(ASR). It guarantees K users within a region containing the location of a given user. However previous researches have dealt the problems based on Euclidean distance in outdoor space, and cannot be applied in indoor space where there are constraints of movement such as walls. For this reason, we propose in this paper a K-anonymity for cloaking indoor location in consideration of structures and representation of indoor space. The basic concept of our approach is to introduce a hierarchical structure as ASR for including K-1 users for cloaking their locations. We also proposed a cost model by K and attributes of hierarchical structure to analyze the performance of the method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.5
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• pp.1044-1051
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• 2003

This paper surveys the EBP(Error Back Propagation) learning, the Cross Entropy function and the LBL(Layer By Layer) learning, which are used for learning the MLP(Multi Layer Perceptrons). We compare the merits and demerits of each learning method in the handwritten digit recognition. Although the speed of EBP learning is slower than other learning methods in the initial learning process, its generalization capability is better. Also, the speed of Cross Entropy function that makes up for the weak points of EBP learning is faster than that of EBP learning. But its generalization capability is worse because the error signal of the output layer trains the target vector linearly. The speed of LBL learning is the fastest speed among the other learning methods in the initial learning process. However, it can't train for more after a certain time, it has the lowest generalization capability. Therefore, this paper proposes the standard of selecting the learning method when we apply the MLP.

• Journal of Digital Contents Society
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• v.8 no.4
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• pp.441-449
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• 2007

In video coding, motion estimation is a process to estimate the pixel of the current frame from the reference frame, which affects directly the predictive quality and the encoding time. This paper is related to AHHS(Adaptive Hierarchical Hexagon Search) using spatio-temporal motion activity for fast motion estimation. The proposed method defines the spatio-temporal motion activity of the current macroblock using the motion vectors of its spatio-temporally adjacent macroblocks, and then conventional AHS(Adaptive Hexagon Search) is performed if the spatio-temporal motion activity is lower, otherwise, hierarchical hexagon search is performed on a multi-layered hierarchical space constructed by multiple sub-images with low frequency in wavelet transform. In the paper, based on computer simulation results for multiple video sequences with different motion characteristics, the performance of the proposed method was analysed and assessed in terms of the predictive quality and the computational time. Experimental results indicate that the proposed method is both suitable for (quasi-) stationary and large motion searches. The proposed method could keep the merit of the adaptive hexagon search capable of fast estimating motion vectors and also adaptively reduce the local minima occurred in the video sequences with higher spatio-temporal motion activity.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2005.11a
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• pp.177-180
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• 2005

MPEG-4 FGS 비트 스트림을 서버측에서는 각 클라이언트의 채널환경에 맞게 적절한 비트율로 추출하여 각 클라이언트에게 전송해야 한다. 부분적인 비트 스트림만으로도 영상 복원이 가능하지만, 같은 비트율에서 전송화질의 극대화를 위해서는 비트 스트림의 추출방법에 대한 연구가 필요하다. 이에 본 논문은 MPEG4 FGS 비디오 스트림을 네트워크 상에서 동적인 통신용량의 변화에 맞춰 적절한 비트율로 추출하는 방법에 대해 제안한다. 제안하는 방법은 같은 비트율에서 전송화질의 극대화를 위해 향상계층의 각 비트 평면(bit-plane)이 손실됐을 때 품질에 미치는 영향을 고려하여 비트율을 줄인다. 이렇게 함으로써 동일한 비트율이 주어진 경우 얻을 수 있는 종단간(end-to-end) 비디오 품질의 향상을 비교 분석하였다.

• Nuclear Engineering and Technology
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• v.27 no.5
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• pp.792-802
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• 1995

국내·외 안전규제기술요건의 현황 및 기술현황 분석 평가 결과를 토대로 안전목표, 안전원칙, 일반안전요건, 상세기술요건, 안전규제지침 및 안전심사지침 등으로 구성된 안전규제기술요건 체계가 구축되었으며, 궁극적인 안전의 지향목표로 부터 구체적인 안전규제방법론에 이르는 일련의 계층을 제시하고있다. 각 계층별 체계설정의 개념, 방법론 및 상세체계도 구성과 이들 구성항목들에 대한주요요점 및 참조 국내·외 규제요건 등이 도출되었으며, 이들은 구체적인 안전규제기술요건의 단위요건 설정에 기본방향을 제공하게 될 것이다. 또한, 안전규제기술요건의 실제적인 설정에 필요한 추진 전략 및 방법을 개략적으로 제시하고 있다. 특히 개발될 안전규제기술요건의 규제위상 정립 및 유관기관의 의견수렴 방안등은 신중히 고려되어야 할 것이며, 산업기준과의 연계방안은 국내에서 개발하고있는 산업기준의 위상을 정립할 수 있는 좋은 계기가 될 것이다.

• Proceedings of the Korean Nuclear Society Conference
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• 1995.05b
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• pp.1099-1104
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• 1995

국내·외 안전규제기술요건의 현황 및 기술현황 분석ㆍ평가 결과를 토대로 안전목표, 안전원칙, 일반안전요건, 상세 기술요건, 안전규제지침 및 안전심사지침 등으로 구성된 안전규제기술요건 체계가 구축되었으며, 궁극적인 안전의 지향목표로부터 구체적인 안전규제방법론에 이르는 일련의 계층을 제시하고있다. 각 계층별 체계설정의 개념, 방법론 및 상세 체계도 구성과 이들 구성 항목들에 대한 주요 요점 및 참조 국내ㆍ외 규제요건 등이 도출되었으며, 이들은 구체적인 안전 규제기술요건의 단위요건 설정에 기본 방향을 제공하게 될 것이다. 또한, 안전규제기술요건의 실제적인 설정에 필요한 추진 전략 및 방법을 개략적으로 제시하고 있다.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.724-726
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• 2005

베이지안망(Bayesian network)은 다수의 변수들 사이의 확률적 관계(조건부독립성: conditional independence)를 그래프 구조로 표현하는 모델이다. 이러한 베이지안망은 비감독학습(unsupervised teaming)을 통한 데이터마이닝에 적합하다. 이를 위해 데이터로부터 베이지안망의 구조와 파라미터를 학습하게 된다. 주어진 데이터의 likelihood를 최대로 하는 베이지안망 구조를 찾는 문제는 NP-hard임이 알려져 있으므로, greedy search를 통한 근사해(approximate solution)를 구하는 방법이 주로 이용된다. 하지만 이러한 근사적 학습방법들도 데이터를 구성하는 변수들이 수천 - 수만에 이르는 경우, 방대한 계산량으로 인해 그 적용이 실질적으로 불가능하게 된다. 본 논문에서는 그러한 대규모 데이터에서 학습될 수 있는 계층적 베이지안망(hierarchical Bayesian network) 모델 및 그 학습방법을 제안하고, 그 가능성을 실험을 통해 보인다.