• Proceedings of the Korea Institute of Convergence Signal Processing
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• 한국신호처리시스템학회 2000년도 추계종합학술대회논문집
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• pp.77-80
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• 2000

In this paper, we propose a method of detecting the distance between two vehicles by computing the disparity of the close-rang vehicle stereo image using two digital cameras. The boundary(or edge) of the object considered the vehicle is obtained by using the modified wavelet transform which has multi-resolution characteristics. We analyze the histogram using the coarse-to-fine method considering a whole feature and increase the resolution to obtain the exact disparity. From the results, the distance of the close-range vehicle is detected effectively by using our proposed method.

• Journal of Broadcast Engineering
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• 제13권1호
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• pp.162-173
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• 2008

In this paper, we propose an effective stereo-view video coding method that considers stereo-view and displayer characteristics. Current many stereo video displayers are designed for not only stereo display but also conventional single view display. In these systems, the resolution of two input videos for a stereo mode is half of that of single view for compatibility with conventional single view video services. In this raper, we propose a stereo video codec to deal with both single view and stereo view services by encoding whole left image and down-sampled right image. However, direct disparity estimation is not possible between two views because the resolution of a left image is different from that of the corresponding right image. So, we propose a disparity estimation method to make use of full information of the left reference image without down-sampling. In experimental result, we achieved $0.5{\sim}0.8\;dB$ coding gain, compared with several conventional algorithms.

• Journal of Korea Multimedia Society
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• 제14권2호
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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 Engineers of Korea SP
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• 제47권1호
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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 IEEK Conference
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(4)
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• pp.206-209
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• 2000

Almost vision application systems use 2-D information by taking only one camera. Recently it arises to utilize 3-D information, which is distance from camera to object, because 2-D information is not sufficient. Therefore, we take stereo camera system. In motion detection algorithm using stereo vision, it operates like one camera system, which takes advantage of correlation, edge, and difference algorithm, when it detects any motion. At that time, to detect motion, it compares two images, which is from two cameras, to calculate disparity that contains distance information. By disparity, it can compute real distance and size of object information. We describe a motion detection algorithm which computes 3-D distance and object size in real time.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• 제8권4호
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• pp.67-73
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• 2008

In the Markov network which models disparity map with the Markov Random Field(MRF), the belief propagation algorithm is operated by message passing between nodes corresponding to each pixels. Belief propagation algorithm required much iteration for accurate result. In this paper, we propose the stereo matching algorithm using belief propagation in multi-resolution domain. Multi-resolution method based on wavelet or lifting can reduce the search area, therefore this algorithm can generate disparity map with fast speed.

• Proceedings of the IEEK Conference
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.935-936
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• 2008

Usually stereo matching methods have some limitations in finding out matching points specially at the boundaries of objects This paper proposes a new method which reduces noises incurred in the process of determining disparity with our energy-based stereo matching method. Our method exploits segmentation results so that pixels within the intra-region have similar disparity values.

• Proceedings of the IEEK Conference
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• 대한전자공학회 2000년도 ITC-CSCC -1
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• pp.421-424
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• 2000

In this paper, we propose a window warping method to solve stereo matching problems in projective distortion region. Because the projective distortion region cant t be estimated with fixed-size block matching algorithm, we use the window warping technique in block matching process. The position of a reference window to resample is obtained adaptively according to the degree of reliability in disparity estimated previously. The initial disparity and reliability are obtained by applying a well known hierarchical strategy. The experimental result shows that considerable improvement is obtained in the projective distortion region.

• Proceedings of the KIEE Conference
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.3044-3046
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• 2000

A Stereo matching has been an important tool for reconstructing three dimensional terrain. In this stereo matching process, DEM(Digitai Elevation Map) can be generated by the disparity from reference image to target image. Generally disparity map in matching process can be implemented by wraping from reference image to target image and if the role of reference and target is interchanged, the different DEM can be obtained. To evaluate the generated DEM from matching process, We adapted the Photorealistic synthetic image generator using ray tracing technique. The generator produce two simulated image from previous DEM and Ortho-image which is regard as Ground-truth. In this paper, we are concern about estimating more accurate DEM from these two DEMs. The several fusion methods of two DEMs are proposed to generate accurate DEM and compared with previous method. one of fusion methods is by using Cross-Correlation match score and the true DEM should have a high matching score.

• The Transactions of The Korean Institute of Electrical Engineers
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• 제66권1호
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• pp.107-113
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• 2017

Unlike regular images, there is no ground truth for bio surface images. Result of biosurface imaging is not only significantly affected by the environment and the condition of the bio surface, it requires more detailed expression than regular images. Therefore, unlike algorithms tested on regular images, studies on bio surface images requires a highly precise optimization process. We aim to optimize the graph cut algorithm, known to be the most outstanding among the stereo visions, by considering baseline, lambda, and disparity range. Optimal results were in the range of 1~10 for lambda. The disparity ranged from -30 to -50, indicating an optimal value in a slightly higher range. Furthermore, we verified the tested optimization data using SIFT.