• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.6B
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• pp.840-847
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• 2001

본 논문에서는 클럭 동기 회로에 사용되는 다차 함수 형태의 결합 필터를 선형 근사화 하는 알고리즘을 제안하고 이를 하드웨어로 구현한다. 정합 필터와 보간필터에 의한 클럭 동기회로는 수신기를 전 디지털 회로를 구현하기 위해 선호되지만 계산량이 증가하는 단점이 있다. 본 논문에서는 정합 필터의 임펄스 응답을 갖는 결합 보간 필터를 구현하고, base 함수의 적용을 선형 근사화 하여 필터의 계산량을 감소시켰다. 본 논문에서는 선형 근사화된 결합 보간 필터의 동작을 Matlab을 통한 시뮬레이션과 ALTERA Chip으로 테스트하였다.

• Proceedings of the Korea Multimedia Society Conference
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• 2004.05a
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• pp.285-288
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• 2004

온라인 필기체 한자는 동일인의 동일 문자조차도 회수, 획순 및 형태의 변화가 다양할 뿐만 아니라 인식 대상이 방대하여 인식이 매우 어렵다. 또한 한자는 기본 자소의 조합에 의한 글자가 아닌 각각의 글자가 독립적으로 이루어져 있어 연속된 획들 간의 관련도를 파악하기 어렵고 획수도 1획에서 28획까지 다양하게 분포를 한다. 따라서 본 연구에서는 대분류 단계로 시작획 비교를 하고 이어진 세분류 단계에서 문자의 특징으로 방향코드와 특이점을 추출해내고 획수를 고려하여 DP 정합을 하는 2단계 인식 시스템을 제안하였다. 이로써 최적의 속도로 입력한 문자를 찾아낼 수 있도록 하였다.

• Journal of Biomedical Engineering Research
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• v.20 no.1
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• pp.59-68
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• 1999

In this paper, we propose an algorithm to locate the corpus callosum automatically from midsagittal brain MR images using the statistical characteristics and shape information of the corpus callosum. In the proposed algorithm, we first extract regions satisfying the statistical characteristics of the corpus callosum and then find a region matching the shape information. In order to match the shape information, a new directed window region-growing algorithm is proposed instead of using conventional contour matching algorithms. Using the proposed algorithm, we adaptively relax the statistical requirement until we find a region matching the shape information. Experiments show promising results.

• Journal of KIISE:Software and Applications
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• v.26 no.12
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• pp.1482-1496
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• 1999

기존의 스테레오 정합 알고리즘은 크게 명암기반기법과 특징기반기법의 두 가지로 나눌 수 있다. 그리고, 각 기법은 그들 나름대로의 장단점을 갖는다. 본 논문은 이 두 기법을 결합하는 새로운 알고리즘을 제안한다. 본 논문에서는 물체모델링을 목적으로 하기 때문에 배경을 제거하여 정합하는 방법을 사용한다. 이를 위해, 정합요소들과 정합유사함수가 정의되고, 정합유사함수는 두 기법사이의 장단점을 하나의 인수에 의해 조절한다. 그 외에도 거리차 지도의 오류를 제거하는 coarse-to-fine기법, 폐색문제를 해결하는 다중윈도우 기법을 사용하였고, 물체의 표면형태를 알아내기 위해 morphological closing 연산자를 이용하여 물체와 배경을 분리하는 방법을 제안하였다. 이러한 기법들을 기반으로 하여 여러가지 영상에 대해 실험을 수행하였으며, 그 결과들은 본 논문이 제안하는 기법의 효율성을 보여준다. 정합의 결과로 만들어지는 거리차 지도는 3차원 모델링을 통해 가상공간상에서 보여지도록 하였다.Abstract Classical stereo matching algorithms can be classified into two major areas; intensity-based and feature-based stereo matching. Each technique has advantages and disadvantages. This paper proposes a new algorithm which merges two main matching techniques. Since the goal of our stereo algorithm is in object modeling, we use images for which background is removed. Primitives and a similarity function are defined. The matching similarity function selectively controls the advantages and disadvantages of intensity-based and feature-based matching by a parameter.As an additional matching strategy, a coarse-to-fine method is used to remove a errorneous data on the disparity map. To handle occlusions, multiple windowing method is used. For finding the surface shape of an object, we propose a method that separates an object and the background by a morphological closing operator. All processes have been implemented and tested with various image pairs. The matching results showed the effectiveness of our method. From the disparity map computed by the matching process, 3D modeling is possible. 3D modeling is manipulated by VRML(Virtual Reality Manipulation Language). The results are summarized in a virtual reality space.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.519-525
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• 2006

The traditional area-based matching or efficient matching methods using epipolar geometry and height restriction of stereo images, which have a confined search space for image matching, have still some disadvantages such as mismatching and timeconsuming, especially in the dense metropolitan city that very high and similar buildings exist. To solve these problems, a new image matching method through building recognition has been presented. This paper described building recognition in color stereo images using edge and color information as a elementary study of new matching scheme. We introduce the modified Hausdorff distance for using edge information, and the modified color indexing with 3-D RGB histogram for using color information. Color information or edge information alone is not enough to find conjugate building pairs. For edge information only, building recognition rate shows 46.5%, for color information only, 7.1%. However, building recognition rate distinctly increase 78.5% when both information are combined.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
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• 2000.11a
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• pp.328-332
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• 2000

본 논문에서는 기생 패치 구조와 적층 구조의 광대역 마이크로스트립 안테나에 평행 결합 선로 형태의 광대역 임피던스 정합 회로를 결합하여 쉽게 추가적인 임피던스 대역폭 개선을 얻을 수 있음을 제안하였다. 평행 결합 선로 형태의 광대역 임피던스 정합 회로 설계를 위하여 분포 회로 방식의 반복적인 방법을 제시하였고. 설계\ulcorner제작 결과 기생 패치 구조와 적층 구조에서 각각 56.23%와 16.45%의 추가적인 임피던스 대역폭 개선을 이룰 수 있었다. 그리고 방사 패턴과 측정된 이득을 보면 평행 결합 선로의 결합으로 인한 방사 패턴에서의 큰 변화는 보이지 않았고, 이득에서는 평행 결합 선로 부분의 커플링 손실로 인해 최대 이득이 약 1 dB 정도 감소하는 것을 확인할 수 있었다.

• The KIPS Transactions:PartA
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• v.11A no.5
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• pp.391-400
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• 2004

Within multimodal medical image registration techniques, which correlate different images and Provide integrated information, surface registration methods generally minimize the surface distance between two modalities. However, the features of two modalities acquired from one subject are similar. So, it can improve the accuracy of registration result to match two images based on optimization of both surface distance and shape feature. This research proposes a registration method which optimizes surface distance and surface curvature of two brain modalities. The registration process has two steps. First, surface information is extracted from the reference images and the test images. Next, the optimization process is performed. In the former step, the surface boundaries of regions of interest are extracted from the two modalities. And for the boundary of reference volume image, distance map and curvature map are generated. In the optimization step, a transformation minimizing both surface distance and surface curvature difference is determined by a cost function referring to the distance map and curvature map. The applying of the result transformation makes test volume be registered to reference volume. The suggested cost function makes possible a more robust and accurate registration result than that of the cost function using the surface distance only. Also, this research provides an efficient means for image analysis through volume visualization of the registration result.

• Journal of Korea Multimedia Society
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• v.16 no.8
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• pp.927-933
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• 2013

Face detection algorithm of OpenCV recognizes the faces by Haar matching between input image and Haar features which are learned through a set of training images consisting of many front faces. Therefore the face detection method by Haar matching yields a high face detection rate for the front faces but not in the case of the pan and deformed faces. On the assumption that distributional characteristics of color histogram is similar even if deformed or side faces, a face detection method using the histogram pattern matching is proposed in this paper. In the case of the missed detection and false detection caused by Haar matching, the proposed face detection algorithm applies the histogram pattern matching with the correct detected face area of the previous frame so that the face region with the most similar histogram distribution is determined. The experiment for evaluating the face detection performance reveals that the face detection rate was enhanced about 8% than the conventional method.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.5
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• pp.61-66
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• 2010

A stereo vision, which is based on two or more images taken from different view points, is able to build three dimensional maps of its environment having various applications including robots and home networks. SAD algorithm, which is based on area-based correlation, is widely used since its regular structure provide abundant parallelism. In this paper, we present heuristic designs of SAD algorithm to meet the demands on accuracy and resource usages in various applications. The disparity abridgement and the window abridgement algorithms can be used for vision systems in low cost and small size. The window shape algorithm can be applicable when object are in specific shapes. The adaptive window algorithm work well when accuracy is the primary concern.

• Korean Journal of Cognitive Science
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• v.3 no.2
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• pp.271-289
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• 1992

In this paper,a cursive on-line Hangul recognition system which permits cursive writing between graphemes is presented.In general,the recognition of cursive Hangul writing has a difficulty of graheme segmentation and a complexity in matching procedure due to the increasing number of character candidates.To manage efficiently these problems,we propose a double segmentation method.Based on this segmentation,a recognition algorithm based on the line segment matching is proposed.Through the experimental result,it is show that the proposed recognition method is suitable for the cursive Hangul writings.