• 한국정보과학회논문지:시스템및이론
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• 제31권11호
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• pp.611-616
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• 2004

본 논문은 극소 원자블록(ultra small atomic block)에 공간예측(spatial prediction)을 적용하여 프랙탈(fractal) 영상압축의 압축시간을 획기적으로 향상시키고 화질/압축률을 향상시키는 방법을 제안한다. 본 방법은 치역(range block)의 크기가 아주 작으면 아주 적은 탐색범위 내에서 변환계수(transformation parameter)들의 값을 극히 제한하더라도 유사한 정의역(domain block)을 쉽게 찾을 수 있고 변환계수들이 좋은 상호관계를 유지함을 이용하여 변환계수 예측으로 화질/압축률을 향상시킨다. 특히, 본 방법은 탐색범위를 극히 제한하기 때문에 기존의 프랙탈 압축방법들 보다 압축시간을 획기적으로 향상시킨다.

• 한국측량학회지
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• 제37권5호
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• pp.331-341
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• 2019

With the popularity of sensor-rich environments, smartphones have become one of the major platforms for obtaining and sharing information. Since it is difficult to utilize GNSS (Global Navigation Satellite System) inside the area with many buildings, the localization of smartphone in this case is considered as a challenging task. To resolve problem of localization using smartphone a four step image-based localization method and procedure is proposed. To improve the localization accuracy of smartphone datasets, MMS (Mobile Mapping System) and Google Street View were utilized. In our approach first, the searching for candidate matching image is performed by the query image of smartphone's using GNSS observation. Second, the SURF (Speed-Up Robust Features) image matching between the smartphone image and reference dataset is done and the wrong matching points are eliminated. Third, the geometric transformation is performed using the matching points with 2D affine transformation. Finally, the smartphone location and attitude estimation are done by PnP (Perspective-n-Point) algorithm. The location of smartphone GNSS observation is improved from the original 10.204m to a mean error of 3.575m. The attitude estimation is lower than 25 degrees from the 92.4% of the adjsuted images with an average of 5.1973 degrees.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2008년도 춘계종합학술대회 A
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• pp.302-305
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• 2008

For an complete image composition to be stitched on several mosaic images, tracing displacement of direction and distance between successive images are important parameters. The input image is modeled by using a general second order two-dimensional Taylor-series and then converting it to a $3{\times}3$ correlation block and storing the data. A moving factor and coordinate is calculated by comparing the continuous correlation blocks. The experimentation result has a success rate of 85% for moving path tracing as continuous images are moved to 10% of image central position.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -1
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• pp.141-144
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• 2002

In this paper, we propose a new object tracking algorithm using deformed template and Level-Set theory, which is robust against background variation, object flexibility and occlusion. The proposed tracking algorithm consists of two steps. The first step is an estimation of object shape and location, on the assumption that the transformation of object can be approximately modeled by the affine transform. The second step is a refinement of the object shape to fit into the real object accurately, by using the potential energy map and the modified Level Set speed function. Experimental results show that the proposed algorithm can track non-rigid objects with large variation in the backgrounds.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 추계종합학술대회 논문집(4)
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• pp.195-198
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• 2000

Fractal image compression can reduce the size of image data by contractive mapping of original image. The mapping is affine transformation to find the block(called range block) which is the most similar to the original image. Fractal is very efficient way to reduce the data size. However, it has high distortion rate and requires long encoding time. In this paper, we present the simulation result of fractal and VQ hybrid systems which use different clustering algorithms, normal and improved competitive learning SOFM. The simulation results showed that the VQ hybrid fractal using improved competitive learning SOFM has better distortion rate than the VQ hybrid fractal using normal SOFM.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2000년도 추계학술대회 학술발표 논문집
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• pp.81-84
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• 2000

Fractal image compression can reduce the size of image data by contractive mapping of original image. The mapping is affine transformation to find the block(called range block) which is the most similar to the original image. Fractal is very efficient way to reduce the data size. However, it has high distortion rate and requires long encoding time. In this paper, we present the simulation result of fractal and VQ hybrid systems which use different clustering algorithms, normal and improved competitive learning SOFM. The simulation results showed that the VQ hybrid fractal using improved competitive learning SOFM has better distortion rate than the VQ hybrid fractal using normal SOFM.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2003년도 추계종합학술대회 논문집
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• pp.271-275
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• 2003

본 논문은 기하학적으로 왜곡된 입 모양을 보정하는 기법을 제안한다. 제안한 기법은 특징추출 단계와 보정 단계로 구성된다. 특징추출 단계에서는 원영상과 목적영상의 입술모델에 따라 각각의 특징과 특징점을 찾고 보정 단계에서는 부분 영상의 사상위치를 결정하고 어파인 변환을 적용하여 입의 왜곡을 보정한다. 여러 형태의 입모양을 실험한 결과, 많은 부분에 존재하는 왜곡이 보정된 것으로 나타났다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.945-946
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• 2008

Feature matching is often used for image alignment. It, however, isconsidered as motion estimation problem in case of video. In that case we need only a motion vector in an image. Then we can compute the distance between two images although the images are far away each other. So we propose affine transformation from camera motion for spatial positioning of frames and aligning those frames. The data from this method can be useful for calculating the distance, stabilizing video, photographing panorama and so on.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 26-27 Oct. 1990
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• pp.1027-1031
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• 1990

In this paper, we propose a model-based method of estimating the velocity of a moving object from a series of images. The proposed method utilizes Kalman filtering technique. Assuming that the motion is described by an affine transformation, we construct a discrete-time state variable model of the motion based on the dynamic motion imagery modeling technique proposed by Schalkoff. Using this state variable model, we derive a Kalman filter algorithm. Some simulation results are presented to show that the proposed Kalman filter algorithm is superior to a simple least square method without a model.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 추계종합학술대회 논문집
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• pp.621-624
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• 1999

This paper describes a distance estimation method of object's motion in soccer image sequence by tracking field features. And we quantitatively evaluate the estimation accuracy We suppose that the input image sequence is taken with a camera on static axis and includes only zooming and panning transformation between frames. Adaptive template matching is adopted for non-rigid object tracking. For background compensation, feature templates selected from reference frame image are matched in following frames and the matched feature point pairs are used in computing Affine motion parameters. A perspective displacement field model is used for estimating the real distance between two position on Input Image. To quantitatively evaluate the accuracy of the estimation, we synthesized a 3 dimensional virtual stadium with graphic tools and experimented on the synthesized 2 dimensional image sequences. The experiment shows that the average of the error between the actual moving distance and the estimated distance is 1.84%.