• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.08a
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• pp.73-76
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• 2008

We present a area-based method for stereo matching using varying weights. A central problem in a area-based stereo matching is different result from selecting a window size. Most of the previous window-based methods iteratively update windows. However, the iterative methods very sensitive the initial disparity estimation and are computationally expensive. To resolve this problem, we proposed a new function to assign weights to pixels using features. To begin with, we extract features in a given stereo images based on edge. We adjust the weights of the pixels in a given window based on correlation of the stereo images. Then, we match pixels in a given window between the reference and target images of a stereo pair. The proposed method is compared to existing matching strategies using both synthetic and real images. The experimental results show the improved accuracy of the proposed method.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.5
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• pp.485-491
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• 2008

LiDAR systems are usually incorporated a laser scanner and GPS/INS modules with a digital aerial camera. LiDAR point clouds and digital aerial images acquired by the systems provide complementary spatial information on the ground. In addition, some of laser scanners provide intensity, radiometric information on the surface of the earth. Since the intensity is unnecessary of registration and provides the radiometric information at a certain wavelength on the location of LiDAR point, it can be a valuable ancillary information but it does not deliver sufficient radiometric information compared with digital images. This study utilize the LiDAR points as ground control points (GCPs) to adjust exterior orientations(EOs) of the stereo images. It is difficult to find exact point of LiDAR corresponding to conjugate points in stereo images, but this study used intensity of LiDAR as an ancillary data to find the GCPs. The LiDAR points were successfully used to adjust EOs of stereo aerial images, therefore, successfully provided the prerequisite for the precise registration of the two data sets from the LiDAR systems.

• Journal of Broadcast Engineering
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• v.7 no.3
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• pp.229-237
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• 2002

Natural synthesis of real and virtual images is a key technology in mixed reality. For this purpose, we propose an efficient dense disparity estimation algorithm and a synthesis algorithm considering features of stereo images. Dense disparities are estimated hierarchically from the low to high resolution images. In the process, the region-dividing-bidirectional-matching algorithm makes matching process efficient and keeps the reliability of the estimated disparities, and dense disparities are assigned considering edge information. finally, mixed reality stereo images are synthesized by comparing depth data of real and virtual Images. Computer simulation shows that the proposed algorithms estimate very stable disparity vectors with sharp edge and synthesize natural stereo mixed reality images.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.5
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• pp.383-389
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• 2000

This paper presents a stereo camera system that provides a Pair of stereo images using a Biprism. The equivalent of a stereo Pair of images is formed as the left and right halves of a single CCD image. The system is therefore cheap and extremely easy to calibrate since it requires only one CCD camera. An additional advantage of the geometrical set-up is that corresponding features lie on the same scanline automatically, The single camera and Biprism have led to a simple stereo system for which correspondence is very easy and which is accurate for nearby objects in a small field of view. Since we use only a single lens, calibration of the system is greatly simplified. Given the parameters in the Biprism-stereo camera system, we can reconstruct the 3-D structure using only the disparity between the corresponding points.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1843-1844
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• 2008

In this paper, the distance from the camera to the object is measured by using stereo camera. The stereo camera acquires two images which have a disparity from left and right camera. The disparity could be calculated by stereo matching of two images and using the disparity, the distance was calculated by triangular method. The distance estimation was carried out as widen the distance from the camera to the object with several operation methods of stereo matching. The result of experiment was under 10 percent error compared with the real distance. Therefore, by using this result, stereo camera would be adapt to the object tracking robot research or any other related area.

• Journal of Korea Society of Digital Industry and Information Management
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• v.4 no.1
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• pp.25-31
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• 2008

In this paper, we propose a new method that separates background and foreground from stereo images. This method can be improved automatic target tracking system by using disparity map of the stereo vision system and background-separating mask, which can be obtained camera configuration parameters. We use disparity map and camera configuration parameters to separate object from background. Disparity map is made with block matching algorithm from stereo images. A morphology filter is used to compensate disparity error that can be caused by occlusion area. We could obtain a separated object from background when the proposed method was applied to real stereo cameras system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.4A
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• pp.371-382
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• 2002

A camera model with optical axes parallel has been widely used for stereo vision applications. A pair of input ages are obtained from a convergent-looking stereo camera model based on the human visual system in this per, and each image is divided into quadrant regions with respect to the fixation point. The reasoning of quadrant partitions is based on the human visual system and is proven by a geometrical method. Image patches : constructed from the right and left stereo images. A modified cepstrum filter is applied to the patches and disparity vectors are determined by peak detection algorithm. The three-dimensional information for synthetic ages is obtained from the measured disparity and the convergent stereo camera model. It is shown that the experimental results of the proposed method for various stereo images are accurate around the fixation point like the human visual system.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.3
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• pp.121-128
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• 2014

This study investigated the accuracy of DEM generated by heterogeneous stereo satellite images based on RPC. Heterogeneous sensor images with different spatial resolution are SPOT-5 panchromatic and IKONOS images. For the accuracy evaluation of the DEM, we compared the DEMs generated from two kinds of sensors and that produced using homogeneous SPOT-5 and IKONOS stereo images. As results of the evaluation, accuracy of 3D positioning by heterogeneous images was substantially similar to that of homogeneous stereo images for exact conjugate points. But, in terms of quality of the DEM, DEM generated by heterogeneous sensor showed a lower accuracy about twice in RMSE and about 3 times in LE90 than that of homogeneous sensors. As a result, DEM can be generated by using heterogenous satellite imagery. But if we use a stereo image with different spatial resolution, the performance of image matching was very important factor for the production of high-quality DEM.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.5
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• pp.471-478
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• 2016

This paper proposes the results of analysis of correlation between satellite geometry elements for an effective use of satellite images. To achieve accurate positional information, stereo images have normal range of convergence and BIE (BIsector Elevation) angles which are greatly influenced by azimuth and elevation angle of individual image. In this paper, the variations of convergence and BIE angles are estimated according to azimuth angle differences between two images and each elevation angle. The analysis provided strong support for predicting stereo geometry without complex analysis of epiploar geometry or mathematics. The experiment results showed that more than 150°, 130°, and 100° azimuth angle differences need to be constructed when elevation angle of two images is 50°, 60°, and 70°, respectively, in order to make the convergence and BIE angle within normal range. The results are expected to be fully used for various application using stereo images.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.1
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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.