• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.119-122
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• 2011

The Stereo vision using belief propagation algorithm that has been studied recently yields good performance in disparity extraction. In this paper, BP algorithm is proved theoretically to high precision for a stereo matching algorithm. We derive disparity map from stereo image by using Belief Propagation (BP) algorithm and area-based matching algorithm. Two algorithms are compared using stereo images provided by Middlebury web site. Disparity map error rate decreased from 52.3% to 2.3%.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.26 no.2
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• pp.223-229
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• 2017

Recently, robotic bin-picking tasks have drawn considerable attention, because flexibility is required in robotic assembly tasks. Generally, stereo camera systems have been used widely for robotic bin-picking, but these have two limitations: First, computational burden for solving correspondence problem on stereo images increases calculation time. Second, errors in image processing and camera calibration reduce accuracy. Moreover, the errors in robot kinematic parameters directly affect robot gripping. In this paper, we propose a method of correcting the bin-picking error by using trinocular vision system which consists of two stereo cameras andone hand-eye camera. First, the two stereo cameras, with wide viewing angle, measure object's pose roughly. Then, the 3rd hand-eye camera approaches the object, and corrects the previous measurement of the stereo camera system. Experimental results show usefulness of the proposed method.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.5
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• pp.134-140
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• 2017

Shape-from-shading (SFS) or stereo vision algorithms can be utilized to measure the shape of an object with imaging techniques for effective sensing in non-contact measurements. SFS algorithms could reconstruct the 3D information from a 2D image data, offering relatively comprehensive information. Meanwhile, a stereo vision algorithm needs several feature points or lines to extract 3D information from two 2D images. However, to measure the size of an object with a freeform surface, the two algorithms need some additional information, such as boundary conditions and grids, respectively. In this study, a stereo vision scheme using the depth information obtained by shape-from-shading as patterns was proposed to measure the size of an object with a freeform surface. The feasibility of the scheme was proved with an experiment where the images of an object were acquired by a CCD camera at two positions, then processed by SFS, and finally by stereo matching. The experimental results revealed that the proposed scheme could recognize the size and shape of freeform surface fairly well.

• Journal of Advanced Navigation Technology
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• v.17 no.3
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• pp.354-360
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• 2013

A stereo vision analysis was performed for motion and depth control of unmanned vehicles. In stereo vision, the depth information in three-dimensional coordinates can be obtained by triangulation after identifying points between the stereo image. However, there are always triangulation errors due to several reasons. Such errors in the vision triangulation can be alleviated by careful arrangement of the camera position and orientation. In this paper, an approach to the determination of the optimal position and orientation of camera is presented for unmanned vehicles.

• Korean Journal of Remote Sensing
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• v.31 no.5
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• pp.421-432
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• 2015

There are significant differences in geometric property and stereo model accuracy between single-sensor stereo that uses two images taken by stereo acquisition mechanism within identical sensor and dual-sensor stereo that randomly combines two images taken from two different sensors. This paper compares the two types of stereo pairs thoroughly. For experiment, two single-sensor stereo pairs and four dual-sensor stereo pairs were constituted using SPOT-5 stereo and KOMPSAT-2 stereo covering same area. While the two single-sensor stereos have stable geometry, the dual-sensor stereos produced two stable and two unstable geometries. In particular, the unstable geometry led to a decrease in stereo model accuracy of the dual-sensor stereos. The two types of stereo pairs were also compared under the stable geometry. Overall, single-sensor stereos performed better than dual-sensor stereos for vertical mapping, but dual-sensor stereos was more accurate for horizontal mapping. This paper has revealed the differences of two types of stereos with their geometric properties and positioning accuracies, suggesting important considerations for handling satellite stereo images, particularly for dual-satellite stereo images.

• Journal of Internet Computing and Services
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• v.6 no.6
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• pp.149-161
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• 2005

Catadioptric mirrors are widely used in automatic surveillance system. The major drawback of catadioptric mirror is its unequal image resolution. Equidistance catadioptric mirror can be the solution to this problem. Even double panoramic structure can generate stereo images with single camera system. So two images obtained from double panoramic equidistance catadioptric mirror can be used in finding the depth and height values of object's points. But compared to the single catadioptric mirror. the image size of double panoramic system is relatively small. This leads to the severe accuracy problem in estimation. The exact axial alignment and the exact mount of mirror are the sources that can be avoided but the focal length variation is inevitable. In this paper, the effects of focal length variation on the computation of depth and height of object' point are explained and the effective focal length finding algorithm, using the assumption that the object's viewing angles are almost same in stereo images, is presented.

• The KIPS Transactions:PartB
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• v.11B no.7 s.96
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• pp.769-778
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• 2004

Object segmentation is a challenging Problem when the background is cluttered and the objects are overlapped one another. Recent develop-ment using snake algorithms proposed to segment objects from a 2-D Image presents a higher possibilityfor getting better contours. However, the performance of those snake algorithms degrades rapidly when the background is cluttered and objects are overlapped one another, Moreover, the initial snake point placement is another difficulty to be resolved. Here, we propose a novel snake algorithm for object segmentation using disparity information taken from a set of stereo images. By applying our newly designed snake energy function defined in the disparity space, our algorithmeffectively circumvents the limitations found in the previous methods. The performance of the proposed algorithm has been verified by computer simulation using various stereo image sets. The experiment results have exhibited a better performance over the well-known snake algorithm in terms of segmentation accuracy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.2A
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• pp.137-145
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• 2002

In the method of 3D modeling, stereo matching method which obtains three dimensional depth information from the two images is taken from the different view points. In general, it is very essential work for the 3D modeling from 2D stereo images to estimate the exact disparity through fading the conjugate pair of pixel from the left and right image. In this paper to solve the problems of the stereo image disparity estimation, we introduce a novel approach method to improve the exactness and efficiency of the disparity. In the first place, we perform a wavelet transformation of the stereo images and set the reference points in the image by the feature-based matching method. This reference points have very high probability over 95 %. In the base of these reference points we can decide the size of the variable block searching windows for estimating dense disparity of area based method and perform the ordering constraint to prevent mismatching. By doing this, we could estimate the disparity in a short time and solve the occlusion caused by applying the fried-sized windows and probable error caused by repeating patterns.

• Steel and Composite Structures
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• v.23 no.6
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• pp.727-736
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• 2017

The application of carbon fiber reinforced polymer (CFRP) in steel structures primarily includes two categories, i.e., the bond-critical application and the contact-critical application. Debonding failure and buckling failure are the main failure modes for these two applications. Conventional electrometric techniques may not provide precise results because of the limitations associated with single-point contact measurements. A nondestructive full-field measurement technique is a valuable alternative to conventional methods. In this study, the digital image correlation (DIC) technique was adopted to investigate the bond behavior and buckling behavior of CFRP-steel composite members. The CFRP-to-steel bonded joint and the CFRP-strengthened square hollow section (SHS) steel column were tested to verify the suitability of the DIC technique. The stereo-DIC technique was utilized to measure continuous deformation. The bond-slip relationship of the CFRP-to-steel interface was derived using the DIC data. Additionally, a multi-camera DIC system consisting of four stereo-DIC subsystems was proposed and applied to the compressive test of CFRP-strengthened SHS steel column. The precise buckling location and CFRP delamination of the CFRP-strengthened SHS steel column were identified. The experimental results confirm that the stereo-DIC technique can provide effective measurements for investigating the behaviors of CFRP-steel composite members.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.5
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• pp.1217-1230
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• 2010

The dynamic programming based methods, a kind of globally optimizing stereo matching methods, has the inherent advantage that the occlusion regions can be found during the process. But it also has a serious drawback of streaking phenomena. This paper focuses on reducing the streaking phenomena by adjusting the penalties in calculating the cost matrix and re-establishing the optimal path in the back-tracing process using the boundary information of the image. Especially we use a pixel expansion method in re-establishing the path, which is the results from expanding the pixel information of the ones just left the boundaries. Experiments with the four image pairs provided by the Middlebury site showed the results that the proposed method has the disparity error ratio of 6.33% and the rank is 29, which is competitive to the best method among the previously published dynamic programming based methods.