• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2015.11a
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• pp.169-172
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• 2015

영상회의 장치에서 눈맞춤 영상을 생성하기 위해 어파인 변환(affine transformation)을 이용하면 반올림 오차(round-off error) 때문에 홀이 발생한다. 이러한 홀을 채우려면 홀 영역을 가리키는 홀 채움 마스크가 필요하다. 홀 채움은 보통 홀 채움 마스크를 참조하여 홀이 아닌 이웃 화소값들을 기반으로 손상된 영상을 복원하는 작업이다. 따라서 홀 영역을 정확히 검출하고 적당한 개수의 이웃 화소값을 참조해야 자연스러운 홀 채움 영상을 생성할 수 있다. 한편, 눈맞춤 영상을 생성할 때 얼굴 특징점을 이용해 얼굴 변환 마스크를 만들고, 얼굴 변환 마스크에만 어파인 변환을 수행한다. 이 논문에서는 얼굴 특징점에도 어파인 변환을 수행하고 수정된 얼굴 변환 마스크를 획득하여 정확한 홀 채움 마스크를 구한다. 또한, 홀 채움 마스크에서 레이블링을 수행하여 큰 홀 영역을 제거한다. 마지막으로, 어파인 변환을 수행할 때 기존 영상의 좌표값을 이용하여 자연스러운 홀 채움 영상을 생성한다. 제안하는 방법으로 홀 채움을 수행한 결과, 연속적인 눈맞춤 동영상에서 이웃값들을 참조하여 홀 채움을 수행한 영상보다 자연스러움을 확인했다.

• Journal of the Semiconductor & Display Technology
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• v.12 no.3
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• pp.59-64
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• 2013

Accurate and robust image registration is important task in many applications such as image retrieval and computer vision. To perform the image registration, essential required steps are needed in the process: feature detection, extraction, matching, and reconstruction of image. In the process of these function, feature extraction not only plays a key role, but also have a big effect on its performance. There are two representative algorithms for extracting image features, which are scale invariant feature transform (SIFT) and speeded up robust feature (SURF). In this paper, we present and evaluate two methods, focusing on comparative analysis of the performance. Experiments for accurate and robust feature detection are shown on various environments such like scale changes, rotation and affine transformation. Experimental trials revealed that SURF algorithm exhibited a significant result in both extracting feature points and matching time, compared to SIFT method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.1
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• pp.153-158
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• 2017

This paper investigates a robust low-complexity design problem for tracking control of uncertain switched pure-feedback systems in the presence of unknown control direction. The completely unknown non-affine nonlinearities are assumed to be arbitrarily switched. By combining the nonlinear error transformation technique and Nussbaum-type functions, a robust tracking controller is designed without using any adaptive function approximators. Thus, compared with existing results, the proposed control scheme has the low-complexity property. From Lyapunov stability theory, it is shown that the tracking error remains within the preassigned transient and steady-state error bounds.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.750-752
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• 2003

The objective of this investigation is to compare the geometric precision of Rigorous Sensor Model and Rational Function Model for QuickBird images. In rigorous sensor model, we use the on-board data and ground control points to fit an orbit; then, a least squares filtering technique is applied to collocate the orbit. In rational function model, we first use the rational polynomial coefficients provided by the satellite company. Then the systematic bias of the coefficients is compensated by an affine transformation using ground control points. Experimental results indicate that, the RFM provides a good approximation in the position accuracy.

• Journal of Korea Multimedia Society
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• v.14 no.5
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• pp.642-649
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• 2011

Among the various aspects of offline handwritten character patterns, it is the great variety of writing styles and variations that renders the task of computer recognition very hard. The immense variety of character shape has been recognized but rarely studied during the past decades of numerous research efforts. This paper tries to address the problem of measuring image distortions and handwritten character patterns with respect to reference patterns. This work is based on mass-spring mesh model with the introduction of simulated electric charge as a source of the external force that can aid decoding the shape distortion. Given an input image and a reference image, the charge is defined, and then the relaxation procedure goes to find the optimum configuration of shape or patterns of least potential. The relaxation process is based on the fourth order Runge-Kutta algorithm, well-known for numerical integration. The proposed method of modeling is rigorous mathematically and leads to interesting results. Additional feature of the method is the global affine transformation that helps analyzing distortion and finding a good match by removing a large scale linear disparity between two images.

• Journal of Multimedia Information System
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• v.8 no.1
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• pp.45-56
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• 2021

This document traces the new technologies development based on a deep classical Hill method improvement. Based on the chaos, this improvement begins with the 256 element body construction, which is to replace the classic ring used by all encryption systems. In order to facilitate the application of algebraic operators on the pixels, two substitution tables will be created, the first represents the discrete logarithm, while the second represents the discrete exponential. At the same time, a large invertible matrix whose structure will be explained in detail will be the subject of the advanced classical Hill technique improvement. To eliminate any linearity, this matrix will be accompanied by dynamic vectors to install an affine transformation. The simulation of a large number of images of different sizes and formats checked by our algorithm ensures the robustness of our method.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.1166-1169
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• 2011

In this paper, we design a Circle dot Code, In our scheme, we design a dot patterns for increasing maximum capacity and also for increasing robustness to Affine Transformation. Our code Can be extended according number of data circle. We use three data circle vision code. In this type code, after acquiring camera images for the Circle dot Codes, and perform error correction decoding using four position symbols and six CRC symbols. We perform graph based dot code analysis which determines the topological distance between dot pixels. Our code can be bridged the real world and ubiquitous computing environment.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.28 no.2
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• pp.59-70
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• 2024

In this paper we present the approximation method of the circular helix by G² cubic polynomial curves. The approximants are G¹ Hermite interpolation of the circular helix and their approximation order is four. We obtain numerical examples to illustrate the geometric continuity and the approximation order of the approximants. The method presented in this paper can be extended to approximating the elliptical helix. Using the property of affine transformation invariance we show that the approximant has G² continuity and the approximation order four. The numerical examples are also presented to illustrate our assertions.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.3
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• pp.156-163
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• 2003

Most watermarking techniques insert watermarks into transform coefficients in the frequency domain because we can consider robust or imperceptible frequency bands against malicious attacks to remove them. However, parameterization of 3-D data is not easy because of irregular attribution of connectivity information, while 1-I) or 2-D data is regular. In this paper we propose a new watermarking scheme for 3-D polygonal mesh models in the DCT domain. After we generate triangle strips by traversing the 3-D model and transform its vertex coordinates into the DCT domain, watermark signals are inserted into mid-frequency bands of AC coefficients for robustness and imperceptibility. We demonstrate that our scheme is robust against additive random noise, the affine transformation, and geometry compression by the MPEG-4 SNHC standard.

• Journal of Biomedical Engineering Research
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• v.23 no.1
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• pp.39-47
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• 2002

The objective of this study is to provide a Precise form of spatial normalization with affine transformation. The quantitative comparison of the brain architecture across different subjects requires a common coordinate system. For the common coordinate system, not only global brain but also a local region of interest should be spatially normalized. Registration using mutual information generally matches the whose brain well. However. a region of interest may not be normalized compared to the feature-based methods with the landmarks. The hybrid method of this Paper utilizes feature information of the local region as well as intensity similarity. Central gray nuclei of a brain including copus callosum, which is used for feature in Schizophrenia detection, is appropriately normalized by the hybrid method. In the results section. our method is compared with mutual information only method and Talairach mapping with schizophrenia Patients. and is shown how it accurately normalizes feature .