• 대한원격탐사학회지
• /
• 제35권6_2호
• /
• pp.1037-1052
• /
• 2019

저자는 접근불능지역인 북한의 임상도 제작을 위한 첫 단계로 Hyperion과 Sentinel-2 위성영상과 질감정보와 지형정보를 활용하여 정확도 98% 이상의 잣나무 및 낙엽송 분류모델을 개발한 바 있다. 북한의 주요 수종 점유율을 고려해 볼 때, 낙엽송(점유율 17.5%), 잣나무(5.8%) 뿐만 아니라 소나무(12.7%), 전나무(8.2%), 참나무류(29.5%)의 점유율이 크므로 수종분류 모델의 확장이 필요하다. 따라서 본 연구에서는 기존의 2개 수종에서 주요 5개 수종으로 분류모델을 확장하기 위해 분광정보와 침엽수 및 활엽수의 수관특성을 고려한 질감정보 및 수종별 생육특성을 고려한 지형정보를 투입하여 방법론을 개선하였다. 연구대상지인 광릉지역의 임상도에서 수종별 위치정보를 취득하여 11,039개의 훈련자료와 2,330개의 검증자료를 구축하였다. 분광정보는 Sentinel-2 영상을 통해 획득하였으며 질감정보는 고해상도인 PlanetScope 영상을, 지형정보는 북한지역으로의 확장 가능성을 고려하여 SRTM DEM을 활용하였다. 머신 러닝 모델은 기존 연구에서 정확도가 검증된 Random Forest 알고리즘을 활용하였다. 분류 결과 전체 80%(Kappa지수 0.80) 정확도로 수종이 분류되었다. 향후 백두산 지역과 남북 고성지역을 대상으로 본 연구에서 개발된 수종분류모델의 확장성을 검토하여 한반도 지역의 수종 분류 모델을 개발하고자 한다.

• 대한원격탐사학회지
• /
• 제37권2호
• /
• pp.291-304
• /
• 2021

기후변화나 여러 환경문제들로부터 지속 가능한 산림자원 관리 및 모니터링을 위해 임상도의 지속적인 갱신은 필수적이다. 따라서 효율적이고 광역적인 산림 원격탐사의 필요성에 따라 차세대 중형위성 4호의 사업이 확정되어 2023년 발사 예정에 있다. 농림위성(차세대 중형위성 4호)는 5 m급 공간해상도와 Blue, Green, Red, Red Edge, Near Infra Red 총 5개 밴드를 가진다. 본 연구는 농림위성의 발사 및 활용에 앞서 농림위성과 유사한 사양을 가지는 RapidEye를 이용하여 위성 기반 수종분류의 가능성을 모의 평가하기 수행되었다. 본 연구는 춘천 선도산림경영단지를 연구 대상지로 하였으며, RapidEye 위성 영상기반 모의 수종분류는 생육기 영상으로부터 추출한 분광정보와 생육기와 비생육기의 NIR 밴드로부터 추출한 GLCM 질감특성 정보가 활용되었고, 이를 입력데이터로 하여 랜덤 포레스트(Random Forest) 기법을 적용하였다. 본 연구에서는 침엽수종 3종(소나무, 잣나무, 낙엽송), 활엽수종 5종(신갈나무, 굴참나무, 자작나무, 밤나무, 기타활엽수), 침활혼효림 총 9종으로 임상을 분류하였다. 분류 정확도는 임상도와 분류 결과를 대조하여 산출하였으며, 분류 정확도는 분광정보만 사용한 경우 39.41%, 분광정보과 질감정보를 모두 사용한 경우 69.29%의 정확도를 보였으며, 다중시기 분광정보 및 질감정보의 활용을 통해 5 m 해상도의 위성영상으로부터 수종분류의 가능성이 있음을 확인하였다. 향후 식생의 생태적 특성을 더욱 효과적으로 반영한 추가 변수를 대입하여 농림위성 활용 가능성을 제고하고자 한다.

• Journal of information and communication convergence engineering
• /
• 제13권3호
• /
• pp.205-214
• /
• 2015

In this paper, we propose a new approach to learning a discriminative model for figure/ground segmentation by incorporating the bag-of-features and conditional random field (CRF) techniques. We advocate the use of image patches instead of superpixels as the basic processing unit. The latter has a homogeneous appearance and adheres to object boundaries, while an image patch often contains more discriminative information (e.g., local image structure) to distinguish its categories. We use pixel-level sparse coding to represent an image patch. With the proposed feature representation, the unary classifier achieves a considerable binary segmentation performance. Further, we integrate unary and pairwise potentials into the CRF model to refine the segmentation results. The pairwise potentials include color and texture potentials with neighborhood interactions, and an edge potential. High segmentation accuracy is demonstrated on three benchmark datasets: the Weizmann horse dataset, the VOC2006 cow dataset, and the MSRC multiclass dataset. Extensive experiments show that the proposed approach performs favorably against the state-of-the-art approaches.

• 한국컴퓨터그래픽스학회논문지
• /
• 제6권3호
• /
• pp.17-23
• /
• 2000

최근에 비사실적 렌더링 기법에 대한 관심이 증가하면서 여러 컴퓨터 그래픽스 연구자들에 의해서 펜화, 수채화, 인상파 기법 등 예술적 기법들을 표현하기 위한 연구가 진행되어 왔다. 본 논문은 사람의 손으로 찢어진 형태의 색종이를 이용하여 모자이크 영상을 생성하는 기법을 소개한다. 색종이를 칼이나 가위 같은 도구를 이용하는 것이 아니라 손으로 찢는 것 같은 모양을 표현하였다. 이를 위하여, 랜덤 중간점 추출 기법을 적용하였고, 종이의 질감을 표현하기 위해서 Perlin의 노이즈 함수를 적용하였다.

• 한국산업융합학회 논문집
• /
• 제23권3호
• /
• pp.515-521
• /
• 2020

Deep learning methods have been effectively used to provide great improvement in various research fields such as machine learning, image processing and computer vision. One of the most frequently used deep learning methods in image processing is the convolutional neural networks. Compared to the traditional artificial neural networks, convolutional neural networks do not use the predefined kernels, but instead they learn data specific kernels. This property makes them to be used as feature extractors as well. In this study, we compared the quality of CNN features for traditional texture feature extraction methods. Experimental results demonstrate the superiority of the CNN features. Additionally, the recognition process and result of a pioneering CNN on MNIST database are presented.

• Macromolecular Research
• /
• 제9권2호
• /
• pp.122-128
• /
• 2001

Monodisperse composite latex particles with size of ca. 300 nm, which consist ofn-butyl acrylate as a soft phase and methyl methacrylate as a hard phase with different morphology, were synthesized by seeded multi-stage emulsion polymerization. Three types of composite latex particles including random-, core/shell-, and gradient-type particles were obtained by using different monomer feeding methods during semi-batch emulsion polymerization. Effect of poly(butyl acrylate)-poly(methyl methacrylate) rubber particle morphology on the mechanical and rheological properties of rubber toughened poly(methyl methacrylate) was investigated. Among three different rubber particles, the gradient-type rubber particle showed better toughening effect than others. No significant variation of rheological property of poly(methyl methacrylate)/rubber blends was observed for the different rubber particle morphology.

• 한국방송∙미디어공학회:학술대회논문집
• /
• 한국방송공학회 2009년도 IWAIT
• /
• pp.85-88
• /
• 2009

In this paper, we propose a DRF-based object detection method using the object adaptive patch in the satellite imagery. It is a Discriminative Random Fields (DRF) based work, so the detection is done by labeling to the possible patches in the image. For the feature information of each patch, we use the multi-scale and object adaptive patch and its texton histogram, instead of using the single scale and fixed grid patch. So, we can include contextual layout of texture information around the object. To make object adaptive patch, we use "superpixel lattice" scheme. As a result, each group of labeled patches represents the object or object's presence region. In the experiment, we compare the detection result with a fixed grid scheme and shows our result is more close to the object shape.

• 한국표면공학회지
• /
• 제31권1호
• /
• pp.24-33
• /
• 1998

Effects of pH and supporting salts on the characteristics of electrogalvanzied coating in sulfate bath are investigated. The fine grain size is obtained and the whiteness with the amount of supporting salts or pH increased at more than current density of 100A/$dm^2$<\TEX>, With supporting salts increased, the electro-conductivity of the bulk solution increases and the cell voltage decreases, while the width of the cathode burned edge gets wider because it seems that the increased overpotential the vicinity of cathode causes the decreases, of limiting current density. When the amount of supporting salts or pH of sulfate bath decreases, the zinc crystals have preferred orientation (001) planes. However when the amount of supporting salts or pH increase, the crystal texture has less (001) planes and gets to have random crystal planes.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
• /
• pp.270-273
• /
• 2007

In this paper, a SAR-despeck1ing approach of adaptive iteration based a Bayesian model using the lognormal distribution for image intensity and a Gibbs random field (GRF) for image texture is proposed for noise removal of the images that are corrupted by multiplicative speckle noise. When the image intensity is logarithmically transformed, the speckle noise is approximately Gaussian additive noise, and it tends to a normal probability much faster than the intensity distribution. The MRF is incorporated into digital image analysis by viewing pixel types as states of molecules in a lattice-like physical system. The iterative approach based on MRF is very effective for the inner areas of regions in the observed scene, but may result in yielding false reconstruction around the boundaries due to using wrong information of adjacent regions with different characteristics. The proposed method suggests an adaptive approach using variable parameters depending on the location of reconstructed area, that is, how near to the boundary. The proximity of boundary is estimated by the statistics based on edge value, standard deviation, entropy, and the 4th moment of intensity distribution.

• Macromolecular Research
• /
• 제10권1호
• /
• pp.44-48
• /
• 2002

The supermolecular structures of poly(ethylene terephthalate) (PET), poly(ethylene 2,6-naphthalate) (PEN), and their blend were investigated with optical microscopy and small angle light scattering. With increasing the crystallization temperature, incomplete spherulitic texture was developed for the PET samples. At a high crystallization temperature of 220 $^{\circ}C$, the light scattering pattern represented a random collection of uncorrelated lamellae. The general morphological appearances for the PEN samples were similar to that of the PET. A notable feature was that the spherulites of the PEN formed at 200 $^{\circ}C$ showed regular concentric bands arising from a regular twist in the radiating lamellae. The spherulitic morphology of the PET/PEN blend was largely influenced by the changes of the sequence distribution in polymer chains determined by the level of transesterifcation. The increased sequential irregularity in the polymer chains via transesterification caused a morphological transition from a regular folded crystallite to a tilted lamellar crystallite.