• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.649-652
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• 2007

이 논문에서는 영화, CF 같은 영상물 제작 시 CG/실사 합성을 위해 배경기하정보를 추출하는 알고리즘을 제안한다. Metric Reconstruction 은 카메라 자동 보정을 통해 이루어지며 이는 오랫동안 연구되어 온 분야이다. 접근방법은 영상의 특징점 추적 정보와 카메라 내부변수 가정으로부터 유도되는 자기 보정 방식과 공간상에서 미리 기하 정보를 알고 있는 보정틀을 사용하는 방식으로 크게 분류될 수 있다. CG/실사 합성의 작업 효율성을 위해서는 배경 영상에 보정틀이 보이지 않는 것이 좋은데 자연 특징점(Natural Feature)에만 의존하는 자기 보정 방식의 경우 2K 급 영상에서 CG 객체를 합성했을 때 떨림이 느껴지지 않을 만큼 정확한 결과를 얻기 힘들다. 이 논문에서는 Polleyfeys[2]가 제안하였던 영상 시퀀스를 입력으로 하는 자기 보정 시스템을 바탕으로 마야 작업 환경에서의 핀홀 카메라 모델에 맞도록 카메라 내부변수의 비선형 최적화를 수행하는 방법과 사용자 개입을 통한 카메라 변수 정확도 향상방법을 제안한다.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.391-394
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• 2005

In this paper, we present an approach that is able to reconstruct 3 dimensional metric models from un-calibrated images acquired by a freely moved camera system. If nothing is known of the calibration of either camera, nor the arrangement of one camera which respect to the other, then the projective reconstruction will have projective distortion which expressed by an arbitrary projective transformation. The distortion on the reconstruction is removed from projection to metric through self-calibration. The self-calibration requires no information about the camera matrices, or information about the scene geometry. Self-calibration is the process of determining internal camera parameters directly from multiply un-calibrated images. Self-calibration avoids the onerous task of calibrating cameras which needs to use special calibration objects. The root of the method is setting a uniquely fixed conic(absolute quadric) in 3D space. And it can make possible to figure out some way from the images. Once absolute quadric is identified, the metric geometry can be computed. We compared reconstruction image from calibrated images with the result by self-calibration method.

• ETRI Journal
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• v.44 no.1
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• pp.94-104
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• 2022

Because of its convenience and compatibility with various image processing techniques, digital image representation of holograms is generally used in digital holography, and thus, quality assessment of digital holograms is an essential issue. This study proposes a new objective quality metric for digital phase hologram image processing. The proposed metric is based on a newly defined phase distortion created by taking the 2π periodicity of phase information into account. The experimental results show that the proposed metric correlates with reconstruction image quality better than the existing metric under random distortions and also works well with JPEG 2000 compression. It is expected to be broadly used in phase image processing and compression applications including phase holograms.

• Journal of the Korea Computer Graphics Society
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• v.4 no.1
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• pp.41-46
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• 1998

An image processing techniques for image compression and its reconstruction are to be considered seriously for the generated huge size data as in the present multimedia environment based on the graphics. So far some approaches for this matter are proposed such as a Wavelet and JPEG method and got desirable result. In this paper, we have studied for the rms(root mean square) metric which is more effective than the existing sup(supremum)metric, and compared with sup metric by means of mathematical verification.

• The KIPS Transactions:PartB
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• v.17B no.3
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• pp.183-188
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• 2010

A factorization-based 3D reconstruction system is realized to recover 3D scene from an image sequence. The image sequence is captured from uncalibrated perspective camera from several views. Many matched feature points over all images are obtained by feature tracking method. Then, these data are supplied to the 3D reconstruction module to obtain the projective reconstruction. Projective reconstruction is converted to Euclidean reconstruction by enforcing several metric constraints. After many triangular meshes are obtained, realistic reconstruction of 3D models are finished by texture mapping. The developed system is implemented in C++, and Qt library is used to implement the system user interface. OpenGL graphics library is used to realize the texture mapping routine and the model visualization program. Experimental results using synthetic and real image data are included to demonstrate the effectiveness of the developed system.

• The KIPS Transactions:PartC
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• v.12C no.4 s.100
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• pp.543-550
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• 2005

Many routing algorithms, proposed for ad-hoc wireless networks, we based on source routing scheme and shortest path route has short lifetime especially in highly dense ad-hoc wireless networks. So some routing protocols such as SSA and ABR are considering the link stability and try finding more stable route. In this paper we propose a new routing algorithm considering utilization metric based on SSA routing algerian in Ad-Hoc networks. To reduce the bottleneck by specific metric of SSA, proposed scheme makes load balancing in networks by distributing the connections to several routes. For the evaluation of the performance we compare our scheme with existent routing protocol AODV and SSA. And the results, obtained using the ns-2 network simulation platform, show good performance that reduced the number of reconstructions remarkably by distributing the whole traffic to several routes when there are several stable routes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.9
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• pp.3856-3863
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• 2012

A 3D reconstruction technique from stereo images that requires minimal intervention from the user has been developed. The reconstruction problem consists of three steps of estimating specific geometry groups. The first step is estimating the epipolar geometry that exists between the stereo image pairs which includes feature matching in both images. The second is estimating the affine geometry, a process to find a special plane in the projective space by means of vanishing points. The third step, which includes camera self-calibration, is obtaining a metric geometry from which a 3D model of the scene could be obtained. The major advantage of this method is that the stereo images do not need to be calibrated for reconstruction. The results of camera calibration and reconstruction have shown the possibility of obtaining a 3D model directly from features in the images.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.2
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• pp.367-374
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• 2022

A sampling set selection algorithm is proposed to reconstruct original graph signals from the sampled signals generated on the nodes in the sampling set. Instead of directly minimizing the reconstruction error, we focus on minimizing the upper bound on the reconstruction error to reduce the algorithm complexity. The metric is manipulated by using QR factorization to produce the upper triangular matrix and the analytic result is presented to enable a greedy selection of the next nodes at iterations by using the diagonal entries of the upper triangular matrix, leading to an efficient sampling process with reduced complexity. We run experiments for various graphs to demonstrate a competitive reconstruction performance of the proposed algorithm while offering the execution time about 3.5 times faster than one of the previous selection methods.

• Nuclear Engineering and Technology
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• v.55 no.12
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• pp.4591-4596
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• 2023

Single-photon emission computed tomography SPECT image reconstruction methods have a significant influence on image quality, with filtered back projection (FBP) and ordered subset expectation maximization (OSEM) being the most commonly used methods. In this study, we proposed newly-designed adaptive non-blind deconvolution with a structural similarity (SSIM) index that can take advantage of the FBP and OSEM image reconstruction methods. After acquiring brain SPECT images, the proposed image was obtained using an algorithm that applied the SSIM metric, defined by predicting the distribution and amount of blurring. As a result of the contrast to noise ratio (CNR) and coefficient of variation evaluation (COV), the resulting image of the proposed algorithm showed a similar trend in spatial resolution to that of FBP, while obtaining values similar to those of OSEM. In addition, we confirmed that the CNR and COV values of the proposed algorithm improved by approximately 1.69 and 1.59 times, respectively, compared with those of the algorithm involving an inappropriate deblurring process. To summarize, we proposed a new type of algorithm that combines the advantages of SPECT image reconstruction techniques and is expected to be applicable in various fields.

• Korean Journal of Optics and Photonics
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• v.19 no.4
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• pp.270-275
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• 2008

This paper addresses occluded object reconstruction and recognition with computational integral imaging (II). Integral imaging acquires and reconstructs target information in the three-dimensional (3D) space. The reconstruction is performed by averaging the intensities of the corresponding pixels. The distance to the object is estimated by minimizing the sum of the standard deviation of the pixels. We adopt principal component analysis (PCA) to classify occluded objects in the reconstruction space. The Euclidean distance is employed as a metric for decision making. Experimental and simulation results show that occluded targets are successfully classified by the proposed method.