• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 추계학술대회 논문집 학회본부 B
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• pp.836-838
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• 1999

This paper describes stereo image compression algorithm using disparity and JPEG. because similar images are images with common features, similiar pixel distributions, and similar edge distributions. Fields such as medical imaging or satellite imaging often need to store large collections of similar images. that is, a conventional stereo system with a single left-right pair needs twice data as a monoscopic imaging system. as a result we need compression method compatible stereo image, in this paper after we use JPEG in basic compression method and stereo matching using adaptiv window, we get disparity information, we restored right image using by restored left image and disparity.

• Journal of Information Display
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• 제5권1호
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• pp.41-46
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• 2004

In this paper, a new stereo 3D moving-target tracking system using the MSE (mean square error) and BPEJTC (binary phase extraction joint transform correlator) algorithms is proposed. A moving target is extracted from the sequential input stereo image by applying a region-based MSE algorithm following which, the location coordinates of a moving target in each frame are obtained through correlation between the extracted target image and the input stereo image by using the BPEJTC algorithm. Through several experiments performed with 20 frames of the stereo image pair with $640{\times}480$ pixels, we confirmed that the proposed system is capable of tracking a moving target at a relatively low error ratio of 1.29 % on average at real time.

• Journal of Information Display
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• 제5권4호
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• pp.31-37
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• 2004

In this paper, an effective method for reconstruction of stereoscopic image pair through the regularized adaptive disparity estimation is proposed. Although the conventional adaptive disparity window matching can sharply improve the PSNR of a reconstructed stereo image, but there still exist some problems of overlapping between the matching windows and disallocation of the matching windows, because the size of the matching window tend to changes adaptively in accordance with the magnitude of the feature values. In the proposed method, the problems relating to the conventional adaptive disparity estimation scheme can be solved and the predicted stereo image can be more effectively reconstructed by regularizing the extimated disparity vector with the neighboring disparity vectors. From the experimental results, it is found that the proposed algorithm show improvements the PSNR of the reconstructed right image by about 2.36${\sim}$2.76 dB, on average, compared with that of conventional algorithms.

• 전자공학회논문지
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• 제54권5호
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• pp.65-73
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• 2017

본 논문에서는 홀 영역과 시차 불연속 영역을 개선하기 위한 스테레오 정합 기법을 제안한다. 스테레오 정합 기법은 두 영상에서의 정합 점을 탐색하여 시차 지도를 추출한다. 하지만 기존의 스테레오 정합 기법들은 스테레오 영상의 베이스 라인 길이에 따라서 정확도와 정밀도가 반비례하는 문제점이 있다. 또한 영상의 폐색 영역과 특징 부족으로 인한 시차 불연속 영역이 존재한다. 제안한 기법에서는 개선된 AD-Census-Gradient 방법과 적응적 가중치 기반의 비용 결합을 통하여 불연속 영역과 오 정합 영역을 개선한 초기 시차 지도를 추출하였다. 그 후에 시차 지도 재생성 과정을 수행하여 오정합 영역을 개선함과 동시에 영상의 정밀도를 개선하였다. 실험 결과 제안하는 기법이 기존의 정합률이 높은 방법들과 비교하여 높은 수준의 정합률을 유지하면서 오정합 영역과 정밀도를 개선하였음을 보였다. 그리고 정합 오차율이 높은 영상의 경우, 최근에 발표된 스테레오 정합 방법들보다 정합 성능이 평균적으로 3.22(%)가량 증가하였다.

• 대한전기학회논문지:시스템및제어부문D
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• 제52권4호
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• pp.212-222
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• 2003

The ability to efficiently and robustly recover accurate 3D terrain models from sets of stereoscopic images is important to many civilian and military applications. A stereo matching has been an important tool for reconstructing three dimensional terrain. However, there exist many factors causing stereo matching error, such as occlusion, no feature or repetitive pattern in the correlation window, intensity variation, etc. Among them, occlusion can be only resolved by true multi-image stereo. In this paper, we present multi-image stereo method using DEM fusion as one of efficient and reliable true multi-image methods. Elevations generated by all pairs of images are combined by the fusion process which accepts an accurate elevation and rejects an outlier. We propose three fusion schemes: THD(Thresholding), BPS(Best Pair Selection) and MS(Median Selection). THD averages elevations after rejecting outliers by thresholding, while BPS selects the most reliable elevation. To determine the reliability of a elevation or detect the outlier, we employ the measure of self-consistency. The last scheme, MS, selects the median value of elevations. We test the effectiveness of the proposed methods with a quantitative analysis using simulated images. Experimental results indicate that all three fusion schemes showed much better improvement over the conventional binocular stereo in natural terrain of 29 Palms and urban site of Avenches.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1996년도 춘계학술대회
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• pp.36-40
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• 1996

There are two prevailing techniques, mechanical and optical profilometers, to measure 3-dimensional configurations of the human skin furrows. The methods have some limitations such as, accuracies or resolutions of the acquired 3-dimensional data and consistencies according to the repeated experiments. We devised an optical profilometer that is called stereo image optical profilometer (SOP) based on stereo image processing techniques. A stereo image is a pair of images that obtained from two cameras which have different angles. From the digital stereo images, the clinical informations for skin can be obtained by some signal processing techniques. In this paper, we focused on the 3-dimensional graphical visualizations of the structures and state of the skin furrows by solving the corresponding problem from the left and right pairs of the stereo images.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2002년도 학술대회지
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• pp.507-510
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• 2002

An algorithm of 3-D particle image velocimetry(3D-PIV) was developed for the measurement of 3-D velocity Held of complex flows. The measurement system consists of two or three CCD camera and one RGB image grabber. Flows size is $1500{\times}100{\times}180(mm)$, particle is Nylon12(1mm) and illuminator is Hollogen type lamp(100w). The stereo photogrammetry is adopted for the three dimensional geometrical mesurement of tracer particle. For the stereo-pair matching, the camera parameters should be decide in advance by a camera calibration. Camera parameter calculation equation is collinearity equation. In order to calculate the particle 3-D position based on the stereo photograrnrnetry, the eleven parameters of each camera should be obtained by the calibration of the camera. Epipolar line is used for stereo pair matching. The 3-D position of particle is calculated from the three camera parameters, centers of projection of the three cameras, and photographic coordinates of a particle, which is based on the collinear condition. To find velocity vector used 3-D position data of the first frame and the second frame. To extract error vector applied continuity equation. This study developed of various 3D-PIV animation technique.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.170-173
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• 2004

When the data from the artificial satellite is analyzed, recent years it is perceived to vegetation index using BRF(Bi-directional Reflectance Factor) of the observation target. To make the BRF models, it is important to measure the 3D structure of the observation target actually. In this study, it is proposed to the observation technique by using multi-angle stereo pair image, and shown the observation result in grassland area. Also, our team has been operating the radio controlled helicopter which can fly over the tall forest canopy and it can be equipped the measurement system.

• 한국측량학회지
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• 제10권2호
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• pp.25-30
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• 1992

수치사진측량에서 이용되는 대부분의 알고리즘은 수치화된 입체영상이 epipolar 기하상태를 이루고 있다는 가정을 근거로 하고 있으므로, 입체쌍의 주사선이 epipolartjs이 되어야 한다. 그러나 항공사진의 경우는 매 순간의 촬영위치에서 촬영자세가 달라지므로 epipolar 기하상태를 이루지 못한다. 본 연구에서는 한 쌍의 입체항공사진을 주사기(scanner)에 의해 수치영상으로 변환시키고, 절대표정후의 외부표정요소를 이용해 영상 재배열을 수행하는 과정에서 대해 연구하였다. 그 결과 입체수치영상으로부터 epipolar 기하상태의 영상을 생성하였다. 생성된 epipolar 영상은 영상정합 과정에 적용하기 위해 수치영상상관기법으로 영상정합을 실시하였고, 영상정합의 결과를 이용해 수치표고모형을 제작하였다. 영상정합에 의해 생성된 수치표모고형은 해석도화기에 의해 생성된 수치표고모형과 비교하였으며 그 결과 경제적인 방법으로 수치표고모형을 제작하는 방안이 제시되었다.

• 한국정밀공학회지
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• 제10권4호
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• pp.170-179
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• 1993

In this study, self-organized neural network is used to solve the vorrespondence problem of the axial stereo image. Edge points are extracted from a pair of stereo images and then the edge points of rear image are assined to the output nodes of neural network. In the matching process, the two input nodes of neural networks are supplied with the coordi- nates of the edge point selected randomly from the front image. This input data activate optimal output node and its neighbor nodes whose coordinates are thought to be correspondence point for the present input data, and then their weights are allowed to updated. After several iterations of updating, the weights whose coordinates represent rear edge point are converged to the coordinates of the correspondence points in the front image. Because of the feature map properties of self-organized neural network, noise-free and smoothed depth data can be achieved.