• Journal of Korea Multimedia Society
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• v.6 no.1
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• pp.78-88
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• 2003

A novel adaptive error concealment technique is proposed using a variable operating region algorithm based on MPEG-4 coding. In the algorithm, a missing block is classified as flat or edge block based on local information from the surrounding blocks extracted using a Sobel operation in a variable operating region (VOR). In this case, the VOR is determined adaptively according to the number of edge directions in the missing block. 1;sing the classification, the flat blocks are then concealed by the Proposed mean based weighted bilinear interpolation (MWBLI) method, and the edge blocks by the boundary directional interpolation (BDI) method. Consequently, the use of the Proposed VOR improves the subjective performance in a curved edge region, while the adaptive processing based on block classification improves the objective performance. Experimental results confirmed that the proposed algorithm produced better results than conventional algorithms, both subjectively and objectively.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.11a
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• pp.200-201
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• 2010

블록 기반의 적응적 루프 필터(BALF : Block Adaptive Loop Filter)는 압축 성능에 있어서 상당히 높은 효율을 보이는 기술 중 하나이다. BALF는 복원된 영상을 원본 영상에 최대한 유사하게 만드는 Weiner 필터계수와 해당 필터가 적용될 영역에 대한 정보를 복원된 영상에 적용함으로써 화질을 높일 수 있다. 그러나 BALF는 단위블록 전체에 대해 하나의 필터를 생성하여 적용하는 방법으로, 블록 내부에서 구분되는 신호적 특성을 따로 분류하지 않는다. 그러므로 BALF는 높은 부호화 성능을 보이는 반면, 높은 복호화 복잡도를 요구한다는 단점이 있다. 본 논문에서는 필터가 적용될 블록을 내부와 경계 영역으로 나누어 경계 영역을 위한 필터를 구분하여 생성하는 루프필터를 제안한다. 제안하는 알고리즘은 기존의 BALF에 비해 부호화 성능이 저하되지만, 필터를 적용할 영역을 선택 가능하게 함으로써 복호화 복잡도를 조절할 수 있도록 하였다. 제안한 방법의 실험결과, 기존의 방법인 BALF에 대하여 블록의 경계 영역 필터를 사용할 경우, 약 3.77%의 부호화 성능 저하에 대하여 약 33.76%의 필터링 속도 향상을 보였다.

• The Journal of the Acoustical Society of Korea
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• v.18 no.4
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• pp.60-64
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• 1999

In this paper, we apply CART(Classification And Regression tree) and OC1(Oblique Classifier1) which methods are widely used for continuous speech recognition and synthesis. We prediet prosodic boundary index by applying CART and OC1, which combine right depth of tree-structured method and To_Right of link grammar method with tri_gram model. We assigned four prosodic boundary index level from 0 to 3. Experimental results show that OC1 method is superior to CART method. In other words, in spite of OC1's having fewer nodes than CART, it can make more improved prediction than CART.

• Journal of Korean Association for Spatial Structures
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• v.4 no.3 s.13
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• pp.103-109
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• 2004

The lowest load when the equilibrium condition becomes to be unstable is defined as the buckling load. The primary objective of this paper is to be analyse stability boundaries for star dome under combined loads and is to investigate the iteration diagram under the independent loading parameter. In numerical procedure of the geometrically nonlinear problems, Arc Length Method and Newton-Raphson iteration method is used to find accurate critical point(bifurcation point and limit point). In this paper independent loading vector is combined as proportional value and star dome was used as numerical analysis model to find stability boundary among load parameters and many other models as multi-star dome and arch were studied. Through this study we can find the type of buckling mode and the value of buckling load.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.10
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• pp.1244-1251
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• 1988

Edge is one of the primitive features of an image and is widely used in image classification and analysis. New edge extration methods using central moments are presented and show various characteristics according to the order of moment, definition of both random variables and probability density functions. The proposed methods use the integral of differences between local mean and pixels in the window whereas most of conventional edge operators use only differential concepts. This gives good noise immunity and extracts fine edges.

• Journal of KIISE:Software and Applications
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• v.33 no.4
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• pp.427-439
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• 2006

The SBF (Simple Boundary Follower) is a boundary-following algorithm, and is used mainly for image recognition and presentation. The SBF is very popular because of its simplicity and efficiency in tracing the boundary of an object from an acquired binary image; however, it does have two drawbacks. First, the SBF cannot consistently process inner or inner-outer corners according to the follower's position and direction. Second, the SBF requires movement operations for the non-boundary pixels that are connected to boundary pixels. The MSBF (Modified Simple Boundary Follower) has a diagonal detour step for preventing inner-outer corner inconsistency, but is still inconsistent with inner-corners and still requires extra movement operations on non-boundary pixels. In this paper, we propose the ISBF (Improved Simple Boundary Follower), which solves the inconsistencies and reduces the extra operations. In addition, we have classified the tour maps by paths from a current boundary pixel to the next boundary pixel and have analyzed SBF, MSBF, and ISBF. We have determined that the ISBF has no inconsistency issues and reduces the overall number of operations.

• Journal of Korea Water Resources Association
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• v.56 no.10
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• pp.619-629
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• 2023

Recent intensification of climate change has led to an increase in damages caused by droughts. Currently, in Korea, the Standardized Precipitation Index (SPI) is used as a criterion to classify the intensity of droughts. Based on the accumulated precipitation over the past six months (SPI-6), meteorological drought intensities are classified into four categories: concern, caution, alert, and severe. However, there is a limitation in classifying drought intensity solely based on precipitation. To overcome the limitations of the meteorological drought warning criteria based on SPI, this study collected emergency water supply damage data from the National Drought Information Portal (NDIP) to classify drought intensity. Factors of SPI, such as precipitation, and factors used to calculate evapotranspiration, such as temperature and humidity, were indexed using min-max normalization. Coefficients for each factor were determined based on the Genetic Algorithm (GA). The drought intensity based on emergency water supply was used as the dependent variable, and the coefficients of each meteorological factor determined by GA were used as coefficients to derive a new Drought Severity Classification Index (DSCI). After deriving the DSCI, cumulative distribution functions were used to present intensity stage classification boundaries. It is anticipated that using the proposed DSCI in this study will allow for more accurate drought intensity classification than the traditional SPI, supporting decision-making for disaster management personnel.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.3
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• pp.107-116
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• 2003

This study investigated how appropriate the classification methods based on conventional spectral characteristics are for high resolution imagery. A supervised classification mixing parametric and non-parametric rules, a method in which fuzzy theory is applied to such classification, and an unsupervised method were performed and compared to each other for accuracy. In addition, comparing the result screen-digitized through interpretation to the classification result using spectral characteristics, this study analyzed the conformity of both methods. Although the supervised classification to which fuzzy theory was applied showed the best performance, the application of conventional classification techniques to high resolution imagery had some limitations due to there being too much information unnecessary to classification, shadows, and a lack of spectral information. Consequently, more advanced techniques including integration with other advanced remote sensing technologies, such as lidar, and application of filtering or template techniques, are required to classify land cover/use or to extract useful information from high resolution imagery.

• Proceedings of the Korea Contents Association Conference
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• 2018.05a
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• pp.189-190
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• 2018

Digital content requires the concept and structure that give us insights into the languages between computers and humans and how humans experience manifested among the flow of characters, images, and voice. Communicology, $Vil{\acute{e}}m$ Flusser's original study, allows us to reconsider and to reconstruct the boundary of human awareness. This paper intends to begin understanding digital content consisting of numerical codes by reviewing communicology. communicology helps to break up pre-existing categories and thinking about new standards. ith the help of information technology. Planning content can be actualized by classifying and reconstructing content that are input/output of senses. The standard of classification is 'boundary' and 'direction,' communication elements that cannot be broken down any further. There is no need to communicate if there is no boundary. The operation of communication is comprised of 'direction.' Considering humankind as the standard, the boundary that takes in stimulation from outside can be seen as senses. Direction can be expressed as input/output. Output assumes that technical pictures receive information. The coordinates for various pre-existing platforms and content and uncovered platforms can be set with a consistent standard. This allows us to escape from the standard of flat content that was activated by sight and rationality at the ideology of characters, to seek a three-dimensional standard that can be vitalized by various senses and irrationality, and to reconstruct the input/output of senses to show the possibility of planning a new platform.

• The KIPS Transactions:PartB
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• v.10B no.6
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• pp.611-618
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• 2003

In this paper, we describe a fuzzy inference approach for detecting and classifying shot transitions in video sequences. Our approach basically extends FAM (Fuzzy Associative Memory) to detect and classify shot transitions, including cuts, fades and dissolves. We consider a set of feature values that characterize differences between two consecutive frames as input fuzzy sets, and the types of shot transitions as output fuzzy sets. The inference system proposed in this paper is mainly composed of a learning phase and an inferring phase. In the learning phase, the system initializes its basic structure by determining fuzzy membership functions and constructs fuzzy rules. In the inferring phase, the system conducts actual inference using the constructed fuzzy rules. In order to verify the performance of the proposed shot transition detection method experiments have been carried out with a video database that includes news, movies, advertisements, documentaries and music videos.