• Title/Summary/Keyword: Image-based Modeling

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A Image-based 3-D Shape Reconstruction using Pyramidal Volume Intersection (피라미드 볼륨 교차기법을 이용한 영상기반의 3차원 형상 복원)

  • Lee Sang-Wook
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.1
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    • pp.127-135
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    • 2006
  • The image-based 3D modeling is the technique of generating a 3D graphic model from images acquired using cameras. It is being researched as an alternative technique for the expensive 3D scanner. In this paper, I propose the image-based 3D modeling system using calibrated camera. The proposed algorithm for rendering 3D model is consisted of three steps, camera calibration, 3D shape reconstruction and 3D surface generation step. In the camera calibration step, I estimate the camera matrix for the image aquisition camera. In the 3D shape reconstruction step, I calculate 3D volume data from silhouette using pyramidal volume intersection. In the 3D surface generation step, the reconstructed volume data is converted to 3D mesh surface. As shown the result, I generated relatively accurate 3D model.

Infrared Image Synthesis of Real Background and Target Model (실제 배경과 표적모델의 적외선 영상 합성)

  • Ahn, Sang-Ho;Kim, Young-Choon;Kim, Ki-Hong
    • Journal of the Korea Institute of Military Science and Technology
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    • v.16 no.2
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    • pp.207-213
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    • 2013
  • An infrared image synthetic method is proposed for infrared system simulation. The synthesis image uses a background IR image captured from real scene and a target IR modeling image. The radiances related with maximum and minimum temperatures of the background and target images are calculated from the Planck's blackbody equation. Based on them, the background and target images are compensated and synthesized. The proposed method is simulated and the IR target images are generated by RadThermIR software.

A study of Image Compression Algorithm using DCT (DCT를 이용한 영상압축 알고리즘에 관한 연구)

  • 한동호;이준노
    • Journal of Biomedical Engineering Research
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    • v.13 no.4
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    • pp.323-330
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    • 1992
  • A Study of Image Compression Algorithm using DCT This paper describes the system that implement a JPEG(Joint Photographic Experts Group) algorithm based on DCT(Discrete Cosine Transform) uslng CCD kameva, Image Grabber, and IBM PC. After cosine transforms the acquisited image, this algorithm quantize and entropy encode the coefficients by JPEG code table. The coefficients are reconstructed by the Huffman decoding, dequantized procedure, and Inverse cosine transform. The results obtained from the impleulented system are as follows. (1) For effcient storage and easy implementation, this system save Image as a PCX formal (2) Thls system get 7:1 compression ratio(3.8 RMSE value) without large distortion. (3) With a low pass filtering, thls system eliminate high frequency components and get 20% enhanced compression ratio. (4) Thls system enhance the reconstructed Image using histogram modeling.

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Visual Quality Optimization for Privacy Protection Bar-based Secure Image Display Technique

  • Park, Sanghyun;Kang, Sang-ug
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.7
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    • pp.3664-3677
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    • 2017
  • Abrupt scene changes generally incur the afterimage effect. So, the unblocked image portion is still viewed by human eyes just after it is blocked by some pattern. Yovo's secure display method utilized this phenomenon and it is systematically analyzed using computational afterimage modeling by replacing the complex afterimage effect via simple low-pass filtering. With this approach, realistic images perceived by the human eye can be computationally generated at every single moment, especially reflecting the afterimage effect. The generated images are compared with the original images to determine the factors that affect the image quality of the secure display method. The simulation results demonstrate that the ratio of the unblocked portion to the blocked portion of an image and the playback rate are two primary factors related to the recognized image quality. We also found that the two factors are still effective for generalized secure display techniques.

Efficient Procedural Modeling of Trees Based on Interactive Growth Volume Control

  • Kim, Jinmo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.9
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    • pp.2232-2245
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    • 2013
  • The present study proposes efficient procedural modeling methods for enabling the growth and creation of various trees with minimal user control. Growth volume algorithms are utilized in order to easily and effectively calculate many parameters that determine tree growth, including branch propagation. Procedural methods are designed so that users' interactive control structures can be applied to these algorithms to create unique tree models efficiently. First, through a two-line-based interactive growth volume control method, the growth information that determines the overall shape of the tree is intuitively adjusted. Thereafter, independent branch control methods designed to control individual branches are added to the growth deformation in order to enable the growth of unique trees. Whether the growth processes of desired trees can be easily and intuitively controlled by the proposed method is verified through experiments. Methods that can apply the proposed methods are also verified.

A Proposal of Deep Learning Based Semantic Segmentation to Improve Performance of Building Information Models Classification (Semantic Segmentation 기반 딥러닝을 활용한 건축 Building Information Modeling 부재 분류성능 개선 방안)

  • Lee, Ko-Eun;Yu, Young-Su;Ha, Dae-Mok;Koo, Bon-Sang;Lee, Kwan-Hoon
    • Journal of KIBIM
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    • v.11 no.3
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    • pp.22-33
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    • 2021
  • In order to maximize the use of BIM, all data related to individual elements in the model must be correctly assigned, and it is essential to check whether it corresponds to the IFC entity classification. However, as the BIM modeling process is performed by a large number of participants, it is difficult to achieve complete integrity. To solve this problem, studies on semantic integrity verification are being conducted to examine whether elements are correctly classified or IFC mapped in the BIM model by applying an artificial intelligence algorithm to the 2D image of each element. Existing studies had a limitation in that they could not correctly classify some elements even though the geometrical differences in the images were clear. This was found to be due to the fact that the geometrical characteristics were not properly reflected in the learning process because the range of the region to be learned in the image was not clearly defined. In this study, the CRF-RNN-based semantic segmentation was applied to increase the clarity of element region within each image, and then applied to the MVCNN algorithm to improve the classification performance. As a result of applying semantic segmentation in the MVCNN learning process to 889 data composed of a total of 8 BIM element types, the classification accuracy was found to be 0.92, which is improved by 0.06 compared to the conventional MVCNN.

Comparison of Orthophotos and 3D Models Generated by UAV-Based Oblique Images Taken in Various Angles

  • Lee, Ki Rim;Han, You Kyung;Lee, Won Hee
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.36 no.3
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    • pp.117-126
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    • 2018
  • Due to intelligent transport systems, location-based applications, and augmented reality, demand for image maps and 3D (Three-Dimensional) maps is increasing. As a result, data acquisition using UAV (Unmanned Aerial Vehicles) has flourished in recent years. However, even though orthophoto map production and research using UAVs are flourishing, few studies on 3D modeling have been conducted. In this study, orthophoto and 3D modeling research was performed using various angle images acquired by a UAV. For orthophotos, accuracy was evaluated using a GPS (Global Positioning System) survey that employed VRS (Virtual Reference Station) acquired checkpoints. 3D modeling was evaluated by calculating the RMSE (Root Mean Square Error) of the difference between the outline height values of buildings obtained from the GPS survey to the corresponding 3D modeling height values. The orthophotos satisfied the acceptable accuracy of NGII (National Geographic Information Institute) for a 1/500 scale map from all angles. In the case of 3D modeling, models based on images taken at 45 degrees revealed better accuracy of building outlines than models based on images taken at 30, 60, or 75 degrees. To summarize, it was shown that for orthophotos, the accuracy for 1/500 maps was satisfied at all angles; for 3D modeling, images taken at 45 degrees produced the most accurate models.

Similarity analysis of pixelated CdTe semiconductor gamma camera image using a quadrant bar phantom for nuclear medicine: Monte Carlo simulation study

  • Park, Chan Rok;Kang, Seong-Hyeon;Lee, Youngjin
    • Nuclear Engineering and Technology
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    • v.53 no.6
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    • pp.1947-1954
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    • 2021
  • In the nuclear medicine imaging, quality control (QC) process using quadrant bar phantom is fundamental aspect of evaluating the spatial resolution. In addition, QC process of gamma camera is performed by daily or weekly. Recently, Monte Carlo simulation using the Geant4 application for tomographic emission (GATE) is widely applied in the pre-clinical nuclear medicine field for modeling gamma cameras with pixelated cadmium telluride (CdTe) semiconductor detector. In this study, we modeled a pixelated CdTe semiconductor detector and quadrant bar phantom (0.5, 1.0, 1.5, and 2.0 mm bar thicknesses) using the GATE tool. Similarity analysis based on correlation coefficients and peak signal-to-noise ratios was performed to compare image qualities for various source to collimator distances (0, 2, 4, 6, and 8 cm) and collimator lengths (0.2, 0.4, 0.6, 0.8, and 1.0 cm). To this end, we selected reference images based on collimator length and source to collimator distance settings. The results demonstrate that as the collimator length increases and the source to collimator distance decreases, the similarity to reference images improves. Therefore, our simulation results represent valuable information for the modeling of CdTe-based semiconductor gamma imaging systems and QC phantoms in the field of nuclear medicine.

Context-Based Minimum MSE Prediction and Entropy Coding for Lossless Image Coding

  • Musik-Kwon;Kim, Hyo-Joon;Kim, Jeong-Kwon;Kim, Jong-Hyo;Lee, Choong-Woong
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 1999.06a
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    • pp.83-88
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    • 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.

Spatial resolution and natural image quality assessment evaluation of gamma camera image using pinhole collimator in lutetium-yttrium oxyorthosilicate scintillation detector

  • Kyuseok Kim;Youngjin Lee
    • Nuclear Engineering and Technology
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    • v.55 no.7
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    • pp.2567-2571
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    • 2023
  • Scintillator materials are widely used in the medical and industrial fields for imaging systems using gamma cameras. In this study, image evaluation is performed by modeling a gamma camera system based on a lutetium-yttrium oxyorthosilicate (LYSO) scintillation detector using a pinhole collimator that can improve the spatial resolution. A LYSO detector-based gamma camera system is modeled using a Monte Carlo simulation tool. The geometric concept of the pinhole collimator is designed using various magnification factors, and the spatial resolution is measured using the acquired source image. To evaluate the resolution, the full width at half maximum (FWHM) and natural image quality assessment (NIQE), a no-reference-based parameter, are used. We confirm that the FWHM and NIQE values decrease simultaneously when the diameter of the pinhole collimator increases. Additionally, we confirm that the spatial resolution improves as the magnification factor increases under the same pinhole diameter condition. Particularly, a 0.57 mm FWHM value is obtained using the modeled gamma camera system with a LYSO scintillation detector. In conclusion, our results demonstrate that a pinhole collimator with a LYSO scintillation detector is a promising gamma camera imaging system.