• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제13권2호
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• pp.161-167
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• 2009

An animated ink diffusion on paper is simulated through making a multiple sessions of random walks. The simulated random walk is built and validated against the diffusion model, then animated by varying the intensity thresholds of the accumulated visit counts on each pixels on an image. Two different random walk models are built one of which is a free random walk in that the walker has exactly same probability to move in any four or eight directions in each step. The other is a biased random walk that has a higher chance to go to a pixel that has more similar intensity value. The latter can be used to simulate an ink diffusion radiating through different texture of paper.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2006년도 춘계학술대회 논문집
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• pp.219-221
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• 2006

Asymmetrical rolling was performed by rolling AA 1050 sheets with different velocities of upper and lower rolls. In order to study the effect of roll gap geometry on the evolution of strain states and textures during asymmetrical rolling, the reduction per rolling pass was varied. After asymmetrical rolling, the outer thickness layers depicted shear textures and the center thickness layers displayed a random texture. With decreasing reduction per an asymmetrical rolling pass, the thickness layers depicting shear textures increases. The strain states associated with asymmetrical rolling were investigated by simulations with the finite element method (FEM).

• 복식
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• 제53권1호
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• pp.99-116
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• 2003

Knit is classified into two such as basic texture and applied one according to knitting principle, and the basic texture of weft knitting consists of single knit. rib knit, purl knit and interlock knit. The basic texture of warp knitting consists of double knit texture, double code knit texture and double vandyke knit texture. Fourteen costumes were produced with eighteen (18) different types and twenty four (24) raw materials, and we were trying to show a wide range of costumes produced with knitting by making two different brands at random and making different designs depending on four seasons. Knitting technique is very important element in that it allows special surface effectiveness and decides the characteristic of knitting materials. Knit designer plays very important roles such as selection of raw thread, deciding knitting technique and type of knitting machine in designing the knit. Therefore, the knit designer requires the ability to utilize the function of knitting machine to the maximum, the effort to acquire the variety of knitting technique, develop the new knitting technique and for the improvement of knitting design.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1996년도 춘계학술대회 논문집
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• pp.24-29
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• 1996

The seniconductor, which is precision product, requires many inspection processes. The surface conditions of the semiconductor chip effect on the functions of the semiconductors. The defects of the chip surface is crack or void. Because general inspection method requires many inspection processes, the inspection system which searches immediately and preciselythe defects of the semiconductor chip surface. We propose the inspection method by using the computer vision system. This study presents an image processing algorithm for inspecting the surface defects(crack, void)of the semiconductor test samples. The proposed image processing algorithm aims to reduce inspection time, and to analyze those experienced operator. This paper regards the chip surface as random texture, and deals with the image modeling of randon texture image for searching the surface defects. For texture modeling, we consider the relation of a pixel and neighborhood pixels as noncasul model and extract the statistical characteristics from the radom texture field by using the 2D AR model(Aut oregressive). This paper regards on image as the output of linear system, and considers the fidelity or intelligibility criteria for measuring the quality of an image or the performance of the processing techinque. This study utilizes the variance of prediction error which is computed by substituting the gary level of pixel of another texture field into the two dimensional AR(autoregressive model)model fitted to the texture field, estimate the parameter us-ing the PAA(parameter adaptation algorithm) and design the defect detection filter. Later, we next try to study the defect detection search algorithm.

• 대한금속재료학회지
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• 제47권1호
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• pp.1-6
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• 2009

Magnesium alloys are drawing a lot of attention and have been extensively studied. The major obstacle to the practical application of the alloys is the poor formability at room temperature, originating basically from the insufficient number of slip system. Development of a proper texture is one promising solution to improve the formability. In the present work, after extrusion and full annealing, microstructures, texture developments and tensile properties of AZ31 Mg alloys are studied. After full annealing strong <1010>||ED fiber texture and weak <1120>+<1230>||ED fiber texture (c-axes in the radial direction) were developed. The textures are distinctly influencing the tensile properties, which can be understood in terms of the activation of basal slip modes. With the random orientation, which is developed in the $45^{\circ}$ sample to the extrusion direction, the better workability can be achieved at room temperature.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2023년도 제68차 하계학술대회논문집 31권2호
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• pp.313-315
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• 2023

본 논문에서는 ¹⁸F-FDG PET과 CT에서 추출한 영상인자를 이용하여 비소세포폐암의 전이를 예측하는 머신러닝 모델을 생성하였다. ¹⁸F-FDG는 종양의 포도당 대사 시 사용되며 이를 추적하여 환자의 암 세포를 진단하는데 사용되는 의료영상 기법 중 하나이다. PET과 CT 영상에서 추출한 이미지 특징은 종양의 생물학적 특성을 반영하며 해당 ROI로부터 계산되어 정량화된 값이다. 본 연구에서는 환자의 의료영상으로부터 image texture 프절 전이 예측에 있어 유의한 인자인지를 확인하기 위하여 AUC를 계산하고 단변량 분석을 진행하였다. PET과 CT에서 각각 4개(GLRLM_GLNU, SHAPE_Compacity only for 3D ROI, SHAPE_Volume_vx, SHAPE_Volume_mL)와 2개(NGLDM_Busyness, TLG_ml)의 image texture feature를 모델의 생성에 사용하였다. 생성된 각 모델의 성능을 평가하기 위해 accuracy와 AUC를 계산하였으며 그 결과 random forest(RF) 모델의 예측 정확도가 가장 높았다. 추출된 PET과 CT image texture feature를 함께 사용하여 모델을 훈련하였을 때가 각각 따로 사용하였을 때 보다 예측 성능이 개선됨을 확인하였다. 추출된 영상인자가 림프절 전이를 나타내는 바이오마커로서의 가능성을 확인할 수 있었으며 이러한 연구 결과를 바탕으로 개인별 의료 영상을 기반으로 한 비소세포폐암의 치료 전략을 수립할 수 있을 것이라 기대된다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권7호
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• pp.2938-2956
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• 2020

Objective image quality assessment (IQA) models have been developed by effective features to imitate the characteristics of human visual system (HVS). Actually, HVS is extremely sensitive to color degradation and complex texture changes. In this paper, we firstly reveal that many existing full reference image quality assessment (FR-IQA) methods can hardly measure the image quality with contrast and masking texture changes. To solve this problem, considering texture masking effect, we proposed a novel FR-IQA method, called Texture and Color Quality Index (TCQI). The proposed method considers both in the masking effect texture and color visual perceptual threshold, which adopts three kinds of features to reflect masking texture, color difference and structural information. Furthermore, random forest (RF) is used to address the drawbacks of existing pooling technologies. Compared with other traditional learning-based tools (support vector regression and neural network), RF can achieve the better prediction performance. Experiments conducted on five large-scale databases demonstrate that our approach is highly consistent with subjective perception, outperforms twelve the state-of-the-art IQA models in terms of prediction accuracy and keeps a moderate computational complexity. The cross database validation also validates our approach achieves the ability to maintain high robustness.

• IEIE Transactions on Smart Processing and Computing
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• 제4권6호
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• pp.422-433
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• 2015

In this paper, we demonstrate inter-layer prediction tools for scalable video coders. The proposed scalable coder is designed to support not only spatial, quality and temporal scalabilities, but also view scalability. In addition, we propose quad-tree inter-layer prediction tools to improve coding efficiency at enhancement layers. The proposed inter-layer prediction tools generate texture prediction signal with exploiting texture, syntaxes, and residual information from a reference layer. Furthermore, the tools can be used with inter and intra prediction blocks within a large coding unit. The proposed framework guarantees the rate distortion performance for a base layer because it does not have any compulsion such as constraint intra prediction. According to experiments, the framework supports the spatial scalable functionality with about 18.6%, 18.5% and 25.2% overhead bits against to the single layer coding. The proposed inter-layer prediction tool in multi-loop decoding design framework enables to achieve coding gains of 14.0%, 5.1%, and 12.1% in BD-Bitrate at the enhancement layer, compared to a single layer HEVC for all-intra, low-delay, and random access cases, respectively. For the single-loop decoding design, the proposed quad-tree inter-layer prediction can achieve 14.0%, 3.7%, and 9.8% bit saving.

• 한국자기학회지
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• 제4권4호
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• pp.319-325
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• 1994

제조조건이 다른 여러 퍼멀로이 합금 타게트를 사용하여 RF 마그네트론 스퍼터링법에 의해 퍼멀로이(NiFe) 박막을 증가시킬 경우 타게트의 제조조건이 박막의 자기특성에 미치는 영향을 조사하 였다. 타게트를 온도에서 어닐링한 결과 $650^{\circ}C$ 이상의 온도에서 재결정이 일어나 미세구조는 압 연조직에서 미세한 재결정립 조직으로 바뀌었으며 이에 따른 집합조직은 (110) 집합조직에서 random 집합조직으로 변화가 일어났다. 재결정이 일어나지 않은 타게트를 사용하여 투입전력 300 및 400 W에 서 증착한 박막의 경우 보자력은 1~5 mTorr의 비교적 넓은 범위의 아르곤 압력에서 낮은 값을 나타 내었으며 이때의 최소값은 0.20 Oe 이하였다. 반면, 재결정이 일어난 타게트의 경우 투입저력 300 W에 서는 5 mTorr에서는 1 mTorr에서만 보자력이 낮은 값을 나타내었으며 이때의 최소값은 0.25 Oe 이하였 다. 박막의 내부응력은 타게트에 관계없이 아르곤 압력이 증가함에 따라 압축응력에서 인장응력으로 변하엿으며 타게트에 따라 5 mTorr에서 거의 사라졌다. 박막의 보자력 및 투자율의 변화는 타게트에 따라 변화되는 박막 조성 및 내부응력의 차이에 기인한 것으로 고찰되었다.

• 한국측량학회지
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• 제36권6호
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• pp.433-442
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• 2018

저수구역은 계획된 홍수위에 의하여 둘러싸인 지역 혹은 댐의 계획된 홍수위 내에 있는 지역으로 정의된다. 본 연구에서는 저수구역 내 농경지를 탐지하기 위하여, 대표적인 기계학습 기법인 RF (Random Forest) 기반의 감독 분류 방법을 적용하였다. 저수구역 내의 농경지를 효과적으로 분류하기 위하여, 질감정보를 정량화하기 위한 대표적인 기법인 GLCM (Gray Level Co-occurrence Matrix)과 NDWI (Normalized Difference Water Index), NDVI (Normalized Difference Vegetation Index)를 추가적인 입력자료로 활용하였다. 특히, 질감정보를 생성하는데 사용된 윈도우 크기가 농경지의 분류 정확도에 미치는 영향을 분석하여, 저수구역 내의 농경지를 효과적으로 분류하기 위한 방법론을 제시하였다. 실험결과, UAV 영상을 이용한 분류결과를 통하여 취득된 다중분광영상과 NDVI, NDWI, GLCM 영상들을 이용하여 저수구역 내의 농경지를 효과적으로 탐지할 수 있음을 확인하였다. 또한, GLCM의 윈도우 크기가 분류정확도를 향상시키기 위한 중요한 변수임을 확인하였다.