• Title/Summary/Keyword: Cloud-free

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Automatic Local Update of Triangular Mesh Models Based on Measurement Point Clouds (측정된 점데이터 기반 삼각형망 곡면 메쉬 모델의 국부적 자동 수정)

  • Woo, Hyuck-Je;Lee, Jong-Dae;Lee, Kwan-H.
    • Korean Journal of Computational Design and Engineering
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    • v.11 no.5
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    • pp.335-343
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    • 2006
  • Design changes for an original surface model are frequently required in a manufacturing area: for example, when the physical parts are modified or when the parts are partially manufactured from analogous shapes. In this case, an efficient 3D model updating method by locally adding scan data for the modified area is highly desirable. For this purpose, this paper presents a new procedure to update an initial model that is composed of combinatorial triangular facets based on a set of locally added point data. The initial surface model is first created from the initial point set by Tight Cocone, which is a water-tight surface reconstructor; and then the point cloud data for the updates is locally added onto the initial model maintaining the same coordinate system. In order to update the initial model, the special region on the initial surface that needs to be updated is recognized through the detection of the overlapping area between the initial model and the boundary of the newly added point cloud. After that, the initial surface model is eventually updated to the final output by replacing the recognized region with the newly added point cloud. The proposed method has been implemented and tested with several examples. This algorithm will be practically useful to modify the surface model with physical part changes and free-form surface design.

Region Selective Transmission Method of MMT based 3D Point Cloud Content (MMT 기반 3차원 포인트 클라우드 콘텐츠의 영역 선별적 전송 방안)

  • Kim, Doohwan;Kim, Junsik;Kim, Kyuheon
    • Journal of Broadcast Engineering
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    • v.25 no.1
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    • pp.25-35
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    • 2020
  • Recently, the development of image processing technology, as well as hardware performance, has been continuing the research on 3D point processing technology that provides users with free viewing angle and stereoscopic effect in various fields. Point cloud technology, which is a type of representation of 3D point, has attracted attention in various fields because it can acquired/expressed point precisely. However, since Hundreds of thousands, millions of point are required to represent one 3D point cloud content, there is a disadvantage that a larger amount of storage space is required than a conventional 2D content. For this reason, the MPEG (Moving Picture Experts Group), an international standardization organization, is continuing to research how to efficiently compress, store, and transmit 3D point cloud content to users. In this paper, a V-PCC bitstream generated by a V-PCC (Video-based Point Cloud Compression) encoder proposed by the MPEG-I (Immersive) group is composed of an MPU (Media Processing Unit) defined by the MMT. In addition, by extending the signaling message defined in the MMT standard, a parameter for a segmented transmission method of the 3D point cloud content by area and quality parameters considering the characteristic of the 3D point cloud content, so that the quality parameters can be selectively determined according to the user's request. Finally, in this paper, we verify the result through design/implementation of the verification platform based on the proposed technology.

The Conversion of Mixed Fat of Beef Tallow and Jatropha Oil into Biodiesel Using Acid / Alkali Catalysts (산/알칼리 촉매를 사용한 우지와 자트로파유 혼합지방의 바이오디젤화)

  • Hyun, Young-Jin
    • Journal of the Korean Applied Science and Technology
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    • v.26 no.2
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    • pp.179-185
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    • 2009
  • The esterification of the reactants of Jatropha oil and methanol added by propyleneglycol was done using p-TSA catalyst. And then the emulsification of triglyceride and methanol was conduced by 1.0vol% GMS. The emulsified reactants were transesterified at $65^{\circ}C$ using TMAH and mixed catalyst (50wt%-TMAH+50wt%-NaOH) respectively. The esterification conversion at the 1:8 molar ratio of free fatty acid to methanol using 8.0wt% p-TSA was 94.7% within 80min. The overall conversion at the 1:8 molar ratio of mixed fat(50wt% Beef Tallow) to methanol and $65^{\circ}C$ using mixed catalyst was 95.4% The cloud point of Biodiesel decreased with the addition of petroleum diesel.

Phase Separations in Random Copolymer Solutions by Continuous Thermodynamics (연속열역학을 이용한 랜덤공중합체 용액의 상분리)

  • Sheo, Shin-Ho;Kim, Ki-Chang;Lee, Kwang-Rae
    • Journal of Industrial Technology
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    • v.18
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    • pp.277-287
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    • 1998
  • In this work continuous thermodynamics was adopted for describing the influence of copolymer polydispersity on phase separations in random copolymer solutions. Continuous themodynamic frameworks were formulated using the Flory-Huggin's excess Gibbs free energy model in which the concentration- and temperature-depentent terms of interaction parameter x were modified. Cloud-point curves and coexistence curves of poly(ethylene-vinylactate)/methylacetate solutions and poly(ehtylene-vinylacetate)/ethylacetate solutions were measured, and experimental data were fitted with theoretical relations formulated in this work. Calculated could-point curves were more good ageeable with experimental data than the modified Flory-Huggins's relations. Coexistence curves which were evaluated by using parameters of x estimated from experimental cloud-point curves, were found to coincide with experimental data.

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Analysis of the Cloud Removal Effect of Sentinel-2A/B NDVI Monthly Composite Images for Rice Paddy and High-altitude Cabbage Fields (논과 고랭지 배추밭 대상 Sentinel-2A/B 정규식생지수 월 합성영상의 구름 제거 효과 분석)

  • Eun, Jeong;Kim, Sun-Hwa;Kim, Taeho
    • Korean Journal of Remote Sensing
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    • v.37 no.6_1
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    • pp.1545-1557
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    • 2021
  • Crops show sensitive spectral characteristics according to their species and growth conditions and although frequent observation is required especially in summer, it is difficult to utilize optical satellite images due to the rainy season. To solve this problem, Constrained Cloud-Maximum Normalized difference vegetation index Composite (CC-MNC) algorithm was developed to generate periodic composite images with minimal cloud effect. In thisstudy, using this method, monthly Sentinel-2A/B Normalized Difference Vegetation Index (NDVI) composite images were produced for paddies and high-latitude cabbage fields from 2019 to 2021. In August 2020, which received 200mm more precipitation than other periods, the effect of clouds, was also significant in MODIS NDVI 16-day composite product. Except for this period, the CC-MNC method was able to reduce the cloud ratio of 45.4% of the original daily image to 14.9%. In the case of rice paddy, there was no significant difference between Sentinel-2A/B and MODIS NDVI values. In addition, it was possible to monitor the rice growth cycle well even with a revisit cycle 5 days. In the case of high-latitude cabbage fields, Sentinel-2A/B showed the short growth cycle of cabbage well, but MODIS showed limitations in spatial resolution. In addition, the CC-MNC method showed that cloud pixels were used for compositing at the harvest time, suggesting that the View Zenith Angle (VZA) threshold needsto be adjusted according to the domestic region.

Direct Finite Element Model Generation using 3 Dimensional Scan Data (3D SCAN DATA 를 이용한 직접유한요소모델 생성)

  • Lee Su-Young;Kim Sung-Jin;Jeong Jae-Young;Park Jong-Sik;Lee Seong-Beom
    • Journal of the Korean Society for Precision Engineering
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    • v.23 no.5 s.182
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    • pp.143-148
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    • 2006
  • It is still very difficult to generate a geometry model and finite element model, which has complex and many free surface, even though 3D CAD solutions are applied. Furthermore, in the medical field, which is a big growth area of recent years, there is no drawing. For these reasons, making a geometry model, which is used in finite element analysis, is very difficult. To resolve these problems and satisfy the requests of the need to create a 3D digital file for an object where none had existed before, new technologies are appeared recently. Among the recent technologies, there is a growing interest in the availability of fast, affordable optical range laser scanning. The development of 3D laser scan technology to obtain 3D point cloud data, made it possible to generate 3D model of complex object. To generate CAD and finite element model using point cloud data from 3D scanning, surface reconstruction applications have widely used. In the early stage, these applications have many difficulties, such as data handling, model creation time and so on. Recently developed point-based surface generation applications partly resolve these difficulties. However there are still many problems. In case of large and complex object scanning, generation of CAD and finite element model has a significant amount of working time and effort. Hence, we concerned developing a good direct finite element model generation method using point cloud's location coordinate value to save working time and obtain accurate finite element model.

Automated Construction of IndoorGML Data Using Point Cloud (포인트 클라우드를 이용한 IndoorGML 데이터의 자동적 구축)

  • Kim, Sung-Hwan;Li, Ki-Joune
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.38 no.6
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    • pp.611-622
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    • 2020
  • As the advancement of technologies on indoor positioning systems and measuring devices such as LiDAR (Light Detection And Ranging) and cameras, the demands on analyzing and searching indoor spaces and visualization services via virtual and augmented reality have rapidly increasing. To this end, it is necessary to model 3D objects from measured data from real-world structures. In addition, it is important to store these structured data in standardized formats to improve the applicability and interoperability. In this paper, we propose a method to construct IndoorGML data, which is an international standard for indoor modeling, from point cloud data acquired from LiDAR sensors. After examining considerations that should be addressed in IndoorGML data, we present a construction method, which consists of free space extraction and connectivity detection processes. With experimental results, we demonstrate that the proposed method can effectively reconstruct the 3D model from point cloud.

Point Cloud-based Automated Building Tilt Measurement (포인트 클라우드 기반 건축물 기울기 측정 자동화)

  • Dayoung Yu;Chaeeun Lee;Sung-Han Sim
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.27 no.5
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    • pp.84-88
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    • 2023
  • This study proposes an automated tilt measurement method using point cloud for buildings. The proposed method consists of two main steps: 1) exterior wall plane extraction, and 2) edge estimation and angle calculation. To validate the performance of the proposed method, the algorithm is applied to a target building, of which the estimated tilt values are compared with those obtained from a total station, a commonly used tool for tilt measurement. The result shows that most estimated tilt values are within the maximum and minimum ranges of the total station measurement, suggesting that the proposed algorithm provides sufficient measurement accuracy. Furthermore, the proposed method is shown to be automated and reliable as well as free from human-induced errors compared to the total station.

Integrating UAV Remote Sensing with GIS for Predicting Rice Grain Protein

  • Sarkar, Tapash Kumar;Ryu, Chan-Seok;Kang, Ye-Seong;Kim, Seong-Heon;Jeon, Sae-Rom;Jang, Si-Hyeong;Park, Jun-Woo;Kim, Suk-Gu;Kim, Hyun-Jin
    • Journal of Biosystems Engineering
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    • v.43 no.2
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    • pp.148-159
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    • 2018
  • Purpose: Unmanned air vehicle (UAV) remote sensing was applied to test various vegetation indices and make prediction models of protein content of rice for monitoring grain quality and proper management practice. Methods: Image acquisition was carried out by using NIR (Green, Red, NIR), RGB and RE (Blue, Green, Red-edge) camera mounted on UAV. Sampling was done synchronously at the geo-referenced points and GPS locations were recorded. Paddy samples were air-dried to 15% moisture content, and then dehulled and milled to 92% milling yield and measured the protein content by near-infrared spectroscopy. Results: Artificial neural network showed the better performance with $R^2$ (coefficient of determination) of 0.740, NSE (Nash-Sutcliffe model efficiency coefficient) of 0.733 and RMSE (root mean square error) of 0.187% considering all 54 samples than the models developed by PR (polynomial regression), SLR (simple linear regression), and PLSR (partial least square regression). PLSR calibration models showed almost similar result with PR as 0.663 ($R^2$) and 0.169% (RMSE) for cloud-free samples and 0.491 ($R^2$) and 0.217% (RMSE) for cloud-shadowed samples. However, the validation models performed poorly. This study revealed that there is a highly significant correlation between NDVI (normalized difference vegetation index) and protein content in rice. For the cloud-free samples, the SLR models showed $R^2=0.553$ and RMSE = 0.210%, and for cloud-shadowed samples showed 0.479 as $R^2$ and 0.225% as RMSE respectively. Conclusion: There is a significant correlation between spectral bands and grain protein content. Artificial neural networks have the strong advantages to fit the nonlinear problem when a sigmoid activation function is used in the hidden layer. Quantitatively, the neural network model obtained a higher precision result with a mean absolute relative error (MARE) of 2.18% and root mean square error (RMSE) of 0.187%.

AVHRR MOSAIC IMAGE DATA SET FOR ASIAN REGION

  • Yokoyama, Ryuzo;Lei, Liping;Purevdorj, Ts.;Tanba, Sumio
    • Proceedings of the KSRS Conference
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    • 1999.11a
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    • pp.285-289
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    • 1999
  • A processing system to produce cloud-free composite image data set was developed. In the process, a fine geometric correction based on orbit parameters and ground control points and radiometric correction based on 6S code are applied. Presently, by using AVHRR image data received at Tokyo, Okinawa, Ulaanbaatar and Bangkok, data set of 10 days composite images covering almost whole Asian region.

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