• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.1
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• pp.103-119
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• 2010

In this paper, we propose a subpixel shift estimation method using phase correlation with a local region for the registration of noisy images. Phase correlation is commonly used to estimate the subpixel shift between images, which is derived from analyzing shifted and downsampled images. However, when the images are affected by additive white Gaussian noise and aliasing artifacts, the estimation error is increased. Thus, instead of using the whole image, the proposed method uses a specific local region that is less affect by noises. In addition, to improve the estimation accuracy, iterative phase correlation is applied between selected local regions rather than using a fitting function. the restricted range is determined by analyzing the maximum peak and the two adjacent values of the inverse Fourier transform of the normalized cross power spectrum. In the experiments, the proposed method shows higher accuracy in registering noisy images than the other methods. Thus, the edge-sharpness and clearness in the super-resolved image is also improved.

• Journal of Broadcast Engineering
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• v.17 no.1
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• pp.73-80
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• 2012

Recently, medical equipments are developed and used for diagnosis or studies. In addition, demand of techniques which automatically deal with three dimensional medical images obtained from the medical equipments is growing. One of the techniques is automatic bone segmentation which is expected to enhance the diagnosis efficiency of osteoporosis, fracture, and other bone diseases. Although various researches have been proposed to solve it, they are unable to be used in practice since a size of the medical data is large and there are many low contrast boundaries with other tissues. In this paper, we present a fast and accurate automatic framework for bone segmentation based on multi-resolutions. On a low resolution step, a position of the bone is roughly detected using constrained branch and mincut which find the optimal template from the training set. Then, the segmentation and the registration are iteratively conducted on the multiple resolutions. To evaluate the performance of the proposed method, we make an experiment with femur and tibia from 50 test knee magnetic resonance images using 100 training set. The proposed method outperformed the constrained branch and mincut in aspect of segmentation accuracy and implementation time.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.07a
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• pp.439-440
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• 2011

최근 의료 장비들이 발전하고 진단 및 연구에 다양하게 이용되면서 이로부터 얻은 3차원 의료 영상들을 자동으로 처리해주는 기술의 수요가 늘고 있다. 자동 뼈 영역화 기법은 이러한 기술들 중 하나로써 골다공증이나 뼈 골절, 골격질환 등의 진단의 효율성을 크게 높여줄 것으로 기대되고 있다. 그러나 현재까지 이를 위한 다양한 연구들이 진행되었음에도 2차원 영상과는 달리 높은 데이터양과 주변 조직과의 모호한 경계들이 많다는 어려움 때문에 실제 진단에는 사용되지 못하고 있다. 이에 따라 본 논문에서는 다중 해상도를 기반으로 하여 영역화와 정합기법을 반복적으로 수행함으로써 3차원 의료 영상 내에서 자동으로 뼈를 영역화 해내는 기법을 제안한다. 낮은 해상도 단계에서 학습된 집합의 뼈 정보들을 이용하여 대략적인 뼈 위치를 검출하고, 이후 해상도를 높여가면서 정합 과정과 영역화 과정을 반복적으로 수행한다. 성능을 확인하기 위해 무릎 자기공명영상(magnetic resonance image)내에서 대퇴골(femur)과 경골(tibia)을 영역화 하는 실험을 진행하였으며 60개의 학습 데이터들을 바탕으로 40개 영상에서의 뼈들을 영역화 하였다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.15-19
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• 2001

A dedicated reverse engineering(RE) system for rapid manufacturing of human head in a 3D bust has been developed. The first step in the process is to capture the surface details of a human head and shoulder by three scanners based upon the digital moire fringe technique. Then the multiple scans captured from different angles are aligned and merged into a single polygonal mesh, and the aligned data set is refined by smoothing, subdividing or hole filling process. Finally, the refined data set is sent to a 4-axis computer numerically control(NC) machine to manufacture a replica. In this paper, we mainly describe on the algorithms and software for aligning multiple data sets. The method is based on the recently popular Iterative Closest Point(ICP) algorithm that aligns different polygonal meshes into one common coordinate system. The ICP algorithm finds the nearest positions on one scan to a collection of points on the other scan by minimizing the collective distance between different scans. We also integrate some heuristics into the ICP to enhance the aligning process. A typical example is presented to validate the system and further research work is also discussed.

• Journal of the Korea Computer Graphics Society
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• v.10 no.4
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• pp.27-36
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• 2004

본 논문에서는 뇌의 하부구조인 해마를 정확하게 분석하기 위한 형상 정규화 방법과 정상인과 간질 환자의 해마를 분류하기 위한 방법을 제시한다. 해마에 대한 형상 분석 과정은 크게 형상 표현을 구축하는 과정, 형상의 유사도를 측정하는 과정, 정상인 집단과 환자 집단을 분류하는 과정으로 이루어진다. 본 연구에서는 해마의 형상 표현으로 메쉬, 골격, 복셀로 이루어진 하이브리드 옥트리 자료구조를 구축하였다. 또한 Iterative Closest Point (ICP) 알고리즘을 사용하여 해마 골격을 기반으로 한 정규화를 수행하였다. 그리고 정규화된 해마 형상을 전역적, 국부적으로 분석하여 최종적으로 입력된 해마가 정상인 또는 간질 환자에 속하는지를 학습된 데이터를 이용하여 분류하였다. 본 논문에서 제시한 ICP 기반의 정규화 방법은 3차원 해마 형상을 정확하게 분석하게 해주고, 골격의 정점 수를 조절함으로써 정규화 시간을 감소시킬 수 있다. 뿐만 아니라 3차원 해마 모델의 형상을 신경망을 통하여 학습시킴으로써 해마의 형상이 변형된 환자 집단과 정상인 집단을 분류하는데 이용할 수 있다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.2
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• pp.91-102
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• 2017

Backpack-mounted mapping system is firstly introduced for flexible movement in indoor spaces where satellite-based localization is not available. With the achieved advances in miniaturization and weight reduction, use of LiDAR (Light Detection and Ranging) sensors in mobile platforms has been increasing, and indeed, they have provided high-precision information on indoor environments and their surroundings. Previous research on the development of backpack-mounted mapping systems, has concentrated mostly on the improvement of data processing methods or algorithms, whereas practical system components have been determined empirically. Thus, in the present study, a simulator for a LiDAR sensor (Velodyne VLP-16), was developed for comparison of the effects of diverse conditions on the backpack system and its operation. The simulated data was analyzed by visual inspection and comparison of the data sets' statistics, which differed according to the LiDAR arrangement and moving speed. Also, the data was used as input to a point-cloud registration algorithm, ICP (Iterative Closest Point), to validate its applicability as pre-analysis data. In fact, the results indicated centimeter-level accuracy, thus demonstrating the potentials of simulation data to be utilized as a tool for performance comparison of pointdata processing methods.

• Journal of the Korean Society of Marine Environment & Safety
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• v.19 no.5
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• pp.552-560
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• 2013

In this paper, an optimization algorithm for the block assembly accuracy control assessment is proposed with consideration for the current block assembly process and accuracy control procedure used in the shipbuilding site. The objective function of the proposed algorithm consists of root mean square error of the distances between design and measured data of the other control points with respect to a specific point of the whole control points. The control points are divided into two groups: points on the control line and the other points. The grouped data are used as criteria for determining the combination of 6 degrees of freedom in the registration process when constituting constraints and calculating objective function. The optimization algorithm is developed by using combination of the sampling method and the point to point relation based modified ICP algorithm which has an allowable error check procedure that makes sure that error between design and measured point is under allowable error. According to the results from the application of the proposed algorithm with the design and measured data of two blocks data which are verified and validated by an expert in the shipbuilding site, it implies that the choice of whole control points as target points for the accuracy calculation shows better results than that of the control points on the control line as target points for the accuracy of the calculation and the best optimized result can be acquired from the accuracy calculation with a fixed point on the control line as the reference point of the registration.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.345-352
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• 2020

To preserve and restore tidal flats and prevent safety accidents, it is necessary to construct tidal flat topographic information including the exact location and shape of tidal creeks. In the tidal flats where the field surveying is difficult to apply, airborne LiDAR surveying can provide accurate terrain data for a wide area. On the other hand, we can economically obtain relatively high-resolution data from UAV (Unmanned Aerial Vehicle) surveying. In this study, we proposed the methodology to generate high-resolution topographic information of tidal flats effectively by integrating airborne LiDAR and UAV point clouds. For the purpose, automatic ICP (Iterative Closest Points) registration between two different datasets was conducted and tidal creeks were extracted by applying CSF (Cloth Simulation Filtering) algorithm. Then, we integrated high-density UAV data for tidal creeks and airborne LiDAR data for flat grounds. DEM (Digital Elevation Model) and tidal flat area and depth were generated from the integrated data to construct high-resolution topographic information for large-scale tidal flat map creation. As a result, UAV data was registered without GCP (Ground Control Point), and integrated data including detailed topographic information of tidal creeks with a relatively small data size was generated.

• Korean Journal of Remote Sensing
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• v.31 no.5
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• pp.449-459
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• 2015

The conventional National Forest Inventory(NFI)-based forest carbon stock estimation method is suitable for national-scale estimation, but is not for regional-scale estimation due to the lack of NFI plots. In this study, for the purpose of regional-scale carbon stock estimation, we created grid-based forest carbon stock maps using spatial ancillary data and two types of up-scaling methods. Chungnam province was chosen to represent the study area and for which the $5^{th}$ NFI (2006~2009) data was collected. The first method (method 1) selects forest type map as ancillary data and uses regression model for forest carbon stock estimation, whereas the second method (method 2) uses satellite imagery and k-Nearest Neighbor(k-NN) algorithm. Additionally, in order to consider uncertainty effects, the final AGB carbon stock maps were generated by performing 200 iterative processes with Monte Carlo simulation. As a result, compared to the NFI-based estimation(21,136,911 tonC), the total carbon stock was over-estimated by method 1(22,948,151 tonC), but was under-estimated by method 2(19,750,315 tonC). In the paired T-test with 186 independent data, the average carbon stock estimation by the NFI-based method was statistically different from method2(p<0.01), but was not different from method1(p>0.01). In particular, by means of Monte Carlo simulation, it was found that the smoothing effect of k-NN algorithm and mis-registration error between NFI plots and satellite image can lead to large uncertainty in carbon stock estimation. Although method 1 was found suitable for carbon stock estimation of forest stands that feature heterogeneous trees in Korea, satellite-based method is still in demand to provide periodic estimates of un-investigated, large forest area. In these respects, future work will focus on spatial and temporal extent of study area and robust carbon stock estimation with various satellite images and estimation methods.