• Journal of Broadcast Engineering
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• v.16 no.6
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• pp.902-915
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• 2011

Recently in the area-based stereo matching field, Adaptive Support-Weight (ASW) method that weights matching cost adaptively according to the luminance intensity and the geometric difference shows promising matching performance. However, ASW requires more computational cost than other matching algorithms do and its real-time implementation becomes impractical. By applying Integral Histogram technique after approximating to the Bilateral filter equation, the computational time of ASW can be restricted in constant time regardless of the support window size. However, Integral Histogram technique causes loss of the matching accuracy during approximation process of the original ASW equation. In this paper, we propose a novel algorithm that maintains the ASW algorithm's matching accuracy while reducing the computational costs. In the proposed algorithm, we propose Sub-Block method that groups the pixels within the support area. We also propose the method adjusting the disparity search range depending on edge information. The proposed technique reduces the calculation time efficiently while improving the matching accuracy.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.9-18
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• 2004

This paper proposes a new and simple stereo matching algorithm using the disparity space image (DSI) technique. First of all, we detect some salient feature points on each scan-line of the image pair and set the matching area using those points and define a simple cost matrix. And we take advantage of matching by pixel-by-pixel instead of using the matching window. While the pixel-by-pixel method boost up the speed of matching, because of no using neighbor information, the correctness of the matching may not be better. To cover this point, we expand the matching path using character of disparity-space-image for using neighbor information. In addition, we devise the compensated matching module using the volume of the disparity space image in order to improve the accuracy of the match. Consequently, we can reduce mismatches at the disparity discontinuities and can obtain the more detailed and correct disparity map.

• 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.

• Journal of Korea Multimedia Society
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• v.14 no.2
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• pp.288-294
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• 2011

In this paper we define the probability models for determining the disparity map given stereo images and derive the methods for solving the problem, which is proven to be equivalent to an energy-based stereo matching. Under the assumptions the difference between the pixel on the left image and the corresponding pixel on the right image and the difference between the disparities of the neighboring pixels are exponentially distributed, a recursive approach for estimating the MRF regularizing parameter is proposed. The proposed method alternates between estimating the parameters with the intermediate disparity map and estimating the disparity map with the estimated parameters, after computing it with random initial parameters. Our algorithm is applied to the stereo matching algorithms based on the dynamic programming and belief propagation to verify its operation and measure its performance.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.159-167
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• 2013

In stereo-view system, variations of target camera position or lighting conditions cause discrepancies on the luminance and chrominance components of stereo views. These discrepancies lead to inaccurate frame view prediction and low quality of 3 D video coding. In this paper, an efficient histogram interval calibration method is proposed for stereo-view coding, so as to compensate for the luminance component of target view. First the proposed method is analyzed by the histogram of the target image frame. Then, it divide two sections of histogram of that frame to correct the color discrepancies. Secondly, each section of the target frame is corrected the luminance component by identify the maximum matching region between the reference frame and the target frame. We have verified our proposed histogram matching method in comparison with the other color correction ones. Experimental results show that it can correct better luminance calibration results of PSNR(Peak Signal to Noise Ratio) and has less computation time.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.1
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• pp.112-119
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• 2010

This paper defines the probability models for determining the disparity map given stereo images and derives the methods for solving the problem, which is proven to be equivalent to an energy-based stereo matching. Under the assumptions the difference between the pixel on the left image and the corresponding pixel on the right image and the difference between the disparities of the neighboring pixels are exponentially distributed, a recursive approach for estimating the MRF regularizing parameter is proposed. Usually energy-based stereo matching methods are so sensitive to the parameter that it should be carefully determined. The proposed method alternates between estimating the parameter with the intermediate disparity map and estimating the disparity map with the estimated parameter, after computing it with random initial parameter. It is shown that the parameter estimated by the proposed method converges to the optimum and its performance can be improved significantly by adjusting the parameter and modifying the energy term.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.768-772
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• 2009

This paper proposes a method for measurement three-dimensional trajectories of bubbles generated around a swimmer's arms from stereo high-speed camera videos. This method is based on two techniques: two-dimensional trajectory estimation in single-camera images and trajectory pair matching in stereo-camera images. The two-dimensional trajectory is estimated by block matching using similarity of bubble shape and probability of bubble displacement. The trajectory matching is achieved by a consistensy test using epipolar constraint in multiple frames. The experimental results in two-dimensional trajectory estimation showed the estimation accuracy of 47% solely by the general optical flow estimation, whereas 71% taking the bubble displacement into consideration. This concludes bubble displacement is an efficient aspect in this estimation. In three-dimensional trajectory estimation, bubbles were visually captured moving along the flow generated by an arm; which means an efficient material for swimmers to swim faster.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.9
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• pp.64-75
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• 1993

This paper proposes a recovering technique of the elevation map by stereo modeling of the aerial image sequence which is transformed based on the aircraft situation. The area-based stereo matching method is simulated and the various parameters are experimentally chosen. In a depth extraction step, the depth is determined by solving the vector equation. The equation is suitable for stereo modeling of aerial images which do not satisfy the epipolar constraint. Also, the performance of the conventional feature-based matching scheme is compared. Finally, techniques analyzing the accuracy of the recovered elevation map (REM) are described. The analysis includes the error estimation for both height and contour lines, where the accuracy is based on the measurements of deviations from the estimates obtained manually. The experimental results show the efficiency of the proposed technique.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.70-74
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• 1999

Remote sensing (RS) data show the surfaces of the earth only but cannot provide the shape data of building sides. The proposed method recovers a 3D shape of building sides from stereo images. Its result shows a higher possibility for recovering a large shaped object by overcoming the difficulties of traditional stereo matching techniques. The urban area will be visualized more realistically than the current model based on graphic and vector data.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.500-503
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• 1997

In this paper, a method for recognizing 3-D objects using the 3-D Hough transform and the robust stereo vision is studied. A 3-D object is recognized through two steps; modeling step and matching step. In modeling step, features of the object are extracted by analyzing the IGES file. In matching step, the values of the sensed image are compared with those of the IGES file which is assumed to location and orientation in the 3-D Hough transform domain. Since we use the 3-D Hough transform domain of the input image directly, the sensitivity to the noise and the high computational complexity could be significantly allcv~ated. Also, the cost efficiency is improved using the robust stereo vision for obtaining depth map image which is needed for 3-D Hough transform. In order lo verify the proposed method, real telephone model is recognized. Thc results of the location and orientation of the model are presented.