• 한국통신학회논문지
• /
• 제21권3호
• /
• pp.576-586
• /
• 1996

이진 형태론적 골격(MS: morphology skeleton) 영상점들은 이들의 정보만으로 원영상을 그대로 복원시킬 수 있는 특징이 있기 때문에, 이 골격 정보를 패턴 인식 및 영상통신에 적용할 수 있다. 한편 기존의 MS는 처리시간이 많이 걸릴 뿐만 아니라 골격점들은 중복도가 높다. 이러한 결점을 해결하기 위하여 본 논문에서는 중복도가 영(zero)인 골격영상을 얻는 새로운 직접 총체적 최소 골격화 방법을 제안하고 이를 DGMS(direct globally minimal sketeton)로 정의한다. 이 방법으로 $256{\times}256$ 이진영상 GIRL에 대한 실험 결과 기존의 총체적 최소 골격화(GMS: globally minimal skeleton)보다 처리 시간이 감축되고, 골격점의 수에서 1.5~6.5% 정도 감소하는 결과를 얻었다.

• 한국CDE학회논문집
• /
• 제14권1호
• /
• pp.60-68
• /
• 2009

Because of the reduced product life-cycle, industries are making an effort to bring down the process planning time. In the traditional approach, we have to analyze established process planning, then design the time chart based on process information and drawing the formal time chart such as SOP(sequence of operation). Thereafter, it will be converted to PLC code that is a time consuming and redundant job. Similarly, Industrial automated process uses PLC Code to control the factory; however, control information and control code(PLC code) are difficult to understand. Hence, industries prefer writing new control code instead of using the existing one. It shows the lack of information reusability in the existing process planning. As a result, to reduce this redundancy and lack of reusability, we propose SOS-Net modeling method. Unlike past stabilized process planning that is rigid to any change; our proposed SOS-Net modeling method is more adaptable to the new changes. The SOS-Net model is easy to understand and easy to convert into PLC Code accordingly. Therefore, we can easily modify the control information and reuse it for new process planning. The proposed model plays an intermediary role between process planning and PLC code generation. It can reduce the process planning and implementation time as well as cost.

• 조명전기설비학회논문지
• /
• 제28권11호
• /
• pp.58-67
• /
• 2014

A grid-connected inverter used for renewable energy resources produces harmonic components in the switching frequency. To effectively reduce switching harmonic components, several types of filter are generally used in the output stage of the grid-connected inverter. Many research works on LCL filter design have been done to maintain the performance with low cost. However, it is not easy to make the filter design be economical and optimal due to the varying characteristic of magnetic core and redundancy design by experience. In this paper, a design method for a LCL filter is presented through the inductor optimization scheme in view of the size and cost when the inductor is manufactured using the magnetic core. The effectiveness is verified through tests using a 3kW grid-connected inverter by simulations and experiments.

• 한국방송∙미디어공학회:학술대회논문집
• /
• 한국방송공학회 1999년도 KOBA 방송기술 워크샵 KOBA Broadcasting Technology Workshop
• /
• pp.83-88
• /
• 1999

In this paper, a novel gray-scale lossless image coder combining context-based minimum mean squared error (MMSE) prediction and entropy coding is proposed. To obtain context of prediction, this paper first defines directional difference according to sharpness of edge and gradients of localities of image data. Classification of 4 directional differences forms“geometry context”model which characterizes two-dimensional general image behaviors such as directional edge region, smooth region or texture. Based on this context model, adaptive DPCM prediction coefficients are calculated in MMSE sense and the prediction is performed. The MMSE method on context-by-context basis is more in accord with minimum entropy condition, which is one of the major objectives of the predictive coding. In entropy coding stage, context modeling method also gives useful performance. To reduce the statistical redundancy of the residual image, many contexts are preset to take full advantage of conditional probability in entropy coding and merged into small number of context in efficient way for complexity reduction. The proposed lossless coding scheme slightly outperforms the CALIC, which is the state-of-the-art, in compression ratio.

• 대한기계학회논문집A
• /
• 제20권12호
• /
• pp.3871-3882
• /
• 1996

In this paper, a closed-form formulation for inverse kinematics of robot manipulators with kinematic redundancy under the constrained environment has been derived using the Kuhn-Tucker condition, the extended Lagrange multiplier method and the working set method. The proposed algorithm satisfies the necessaryand sufficient conditions for optimization subject to equality and inequality constraints. In addition, computationally efficient kinematic control methods have been proposed using differential kinemetics and gradient projection mehtod. The effectiveness of the proposed methods has been demonstrated with a 4-dof planar robot, and then a 7-dof spatial robot as a practical application to the nozzle dam task in the Nuclear Power Plant.

• 로봇학회논문지
• /
• 제16권2호
• /
• pp.147-154
• /
• 2021

One of the most challenging issues when robots interact with the environment is to establish contact quickly and avoid high impact force at the same time. The proposed method implements the passive suspension system using the redundancy of the torque-controlled robot. Instead of utilizing the actual mechanical compliance, the distal joints near the end-effector are controlled to act as a virtual spring-damper system with low feedback gains. The proximal joints are precisely controlled to push the mid-link, which is defined as the boundary link between the proximal and distal joints, towards the environment with high feedback gains. Compared to the active compliance methods, the contact force measurements or estimates are not required for contact establishment and the control time delay problems do not occur correspondingly. The proposed method was applied to the landing foot control of the 12-DoF biped robot DYROS-RED in the simulations. In the results, the impact force during landing was significantly reduced at the same collision speed.

• ETRI Journal
• /
• 제41권2호
• /
• pp.235-241
• /
• 2019

In this paper, we propose a rank-weighted reconstruction feature to improve the robustness of a feed-forward deep neural network (FFDNN)-based acoustic model. In the FFDNN-based acoustic model, an input feature is constructed by vectorizing a submatrix that is created by slicing the feature vectors of frames within a context window. In this type of feature construction, the appropriate context window size is important because it determines the amount of trivial or discriminative information, such as redundancy, or temporal context of the input features. However, we ascertained whether a single parameter is sufficiently able to control the quantity of information. Therefore, we investigated the input feature construction from the perspectives of rank and nullity, and proposed a rank-weighted reconstruction feature herein, that allows for the retention of speech information components and the reduction in trivial components. The proposed method was evaluated in the TIMIT phone recognition and Wall Street Journal (WSJ) domains. The proposed method reduced the phone error rate of the TIMIT domain from 18.4% to 18.0%, and the word error rate of the WSJ domain from 4.70% to 4.43%.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2023년도 학술발표회
• /
• pp.180-180
• /
• 2023

To improve global risk management, understanding the characteristics and distribution of precipitation is crucial. However, obtaining spatially and temporally resolved climatic data remains challenging due to sparse gauge observations and limited data availability, despite the use of satellite and reanalysis products. To address this challenge, merging available precipitation products has been introduced to generate spatially and temporally reliable data by taking advantage of the strength of the individual products. However, most of the existing studies utilize all the available products without considering the varying performances of each dataset in different regions. Comprehensively considering the relative contributions of each parent dataset is necessary since their contributions may vary significantly and utilizing all the available datasets for data merging may lead to significant data redundancy issues. Hence, for this study, we introduce a site-specific precipitation merging method that utilizes the Quadruple Collocation (QC) approach, which acknowledges the existence of error-cross correlation between the parent datasets, to create a high-resolution global daily precipitation data from 2001-2020. The performance of multiple gridded precipitation products are first evaluated per region to determine the best combination of quadruplets to be utilized in estimating the error variances through the QC approach and computation of merging weights. The merged precipitation is then computed by adding the precipitation from each dataset in the quadruplet multiplied by each respective merging weight. Our results show that our approach holds promise for generating reliable global precipitation data for data-scarce regions lacking spatially and temporally resolved precipitation data.

• ETRI Journal
• /
• 제44권1호
• /
• pp.73-84
• /
• 2022

The moving picture experts group (MPEG) immersive video (MIV) technology has been actively developed and standardized to efficiently deliver immersive video to viewers in order for them to experience immersion and realism in various realistic and virtual environments. Such services are provided by MIV technology, which uses multiview videos as input. The pruning process, which is an important component of MIV technology, reduces interview redundancy in multiviews videos. The primary aim of the pruning process is to reduce the amount of data that available video codec must handle. In this study, two approaches are presented to improve the existing pruning algorithm. The first method determines the order in which images are pruned. The amount of overlapping region between the source views is then used to determine the pruning order. The second method considers global region-wise color similarity to minimize matching ambiguity when determining the pruning area. The proposed methods are evaluated under common test condition of MIV, and the results show that incorporating the proposed methods can improve both objective and subjective quality.

• 대한전자공학회논문지SP
• /
• 제38권4호
• /
• pp.362-370
• /
• 2001

본 논문에서는 웨이브릿 영역에서의 영역 분류와 대역간 예측 및 선택적 벡터 양자화를 이용한 다분광 화상테이타 압축 기법을 제안하였다. 이 방법에서는 각 대역을 웨이브릿 변환 후, 각 대역의 기저밴드의 대역별 특성을 이용하여 영역 분류를 행하였다. 그리고, 다른 대역과 해상도가 동일하고 공간적 분산이 작으며 분광적 상관성이 큰 기준대역 (reference channel)을 결정한 뒤, 이를 영역별 스칼라 및 분류별 가변 벡터 양자화를 행하여 부호화 하였다. 또한 기준대역과의 대역간 상관성이 큰 대역들에 대해서는 영역별 대역간 예측을 행한 후, 활동도가 높은 블록에 대해서만 선택적 벡터 양자화로 부호화를 행하였다. 이때, 활동도가 높은 블록들의 위치정보는 기준대역으로부터 얻어지는 임계치 지도 (threshold map; THMAP)를 이용하였다. 즉, 제안한 방법에서는 각 대역에 대해 웨이브릿 영역에서의 영역 분류 후 영역별 대역간 예측을 행함으로써 다분광 화상데이타에 존재하는 대역간 중복성을 제거하고 선택적 벡터 양자화를 행함으로써 대역내 중복성을 효과적으로 제거하여 압축효율을 향상시킨다. 실제 원격 센싱된 인공위성 화상데이타에 대한 실험을 통하여 제안한 기법의 부호화 효율이 기존의 기법에 비하여 우수함을 확인하였다.