• Journal of Mechanical Science and Technology
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• v.18 no.3
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• pp.443-452
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• 2004

For stereo lithography process, accuracy of prototypes is related to laser power, scan speed, scan width, scan pattern, layer thickness, resin characteristics and etc. An accurate prototype is obtained by using appropriate process parameters. In order to determine these parameters, the stereolithography (SLA) machine using neural network was developed and efficiency of the developed SLA machine was compared with that of the traditional SLA. Optimum values for scan speed, hatching spacing and layer thickness improved the surface roughness and build time for the developed SLA.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.9
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• pp.2138-2144
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• 2015

Multimodal dual camera system has a stereo-like configuration equipped with an infrared thermal and optical camera. This paper presents stereo calibration methods on multimodal dual camera system using a target board that can be recognized by both thermal and optical camera. While a typical stereo calibration method usually performed with extracted intrinsic and extrinsic camera parameter, consecutive image processing steps were applied in this paper as follows. Firstly, the corner points were detected from the two images, and then the pixel error rate, the size difference, the rotation degree between the two images were calculated by using the pixel coordinates of detected corner points. Secondly, calibration was performed with the calculated values via affine transform. Lastly, result image was reconstructed with mapping regions on calibrated image.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.1
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• pp.22-30
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• 2011

Plane detection is very important information for mission-critical of robot in 3D environment. A representative method of plane detection is Hough-transformation. Hough-transformation is robust to noise and makes the accurate plane detection possible. But it demands excessive memory and takes too much processing time. Iterative randomized Hough-transformation has been proposed to overcome these shortcomings. This method doesn't vote all data. It votes only one value of the randomly selected data into the Hough parameter space. This value calculated the value of the parameter of the shape that we want to extract. In Hough parameters space, it is possible to detect accurate plane through detection of repetitive maximum value. A common problem in these methods is that it requires too much computational cost and large number of memory space to find the distribution of mixed multiple planes in parameter space. In this paper, we detect multiple planes only via data sampling using Self Organizing Map method. It does not use conventional methods that include transforming to Hough parameter space, voting and repetitive plane extraction. And it improves the reliability of plane detection through division area searching and planarity evaluation. The proposed method is more accurate and faster than the conventional methods which is demonstrated the experiments in various conditions.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.7
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• pp.127-137
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• 1996

The 3-dimensional measurement using stereo vision system must achieve a camera calibration. So far, the 3-dimensional calibration technique that uses two-dimensional grid papar and a non-linear least square method has been developed and tested. But, this method is inefficient because it has many calculation procedure and a non-linear analysis. Therefore, this paper proposed the projective geometric method which produced the calibration parameter by vanishing point. The vanishing point is producted by a cross ratio and a parallel line pairs. The results of the computer simulation show utility of the proposed method.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.102-113
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• 2014

This paper suggests a novel hardware architecture of a real-time rectification which is to remove vertical parallax of an image occurred in the pre-processing stage of stereo matching. As an off-line step, Matlab Toolbox which was designed by J.Y Bouguet, was used to calculate calibration parameter of the image. Then, based on the Heikkila and Silven's algorithm, rectification hardware was designed. At this point, to enhance the precision of the rectified image, floating-point unit was generated by using Xilinx Core Generator. And, we confirmed that proposed hardware design had higher precision compared to other designs while having the ability to do rectification in real-time.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.27 no.6
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• pp.726-735
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• 2003

A Process of 3-D Particle image velocimetry, called here, as '3-D volume PIV' was developed for the full-field measurement of 3-D complex flows. The present method includes the coordinate transformation from image to camera, calibration of camera by a calibrator based on the collinear equation, stereo matching of particles by the approximation of the epipolar lines, accurate calculation of 3-D particle positions, identification of velocity vectors by 3-D cross-correlation equation, removal of error vectors by a statistical method followed by a continuity equation criterior, and finally 3-D animation as the post processing. In principle, as two frame images only are necessary for the single instantaneous analysis 3-D flow field, more effective vectors are obtainable contrary to the previous multi-frame vector algorithm. An Experimental system was also used for the application of the proposed method. Three analog CCD camera and a Halogen lamp illumination were adopted to capture the wake flow behind a bluff obstacle. Among 200 effective particle s in two consecutive frames, 170 vectors were obtained averagely in the present study.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.4
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• pp.1171-1187
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• 2012

A depth adjustment method for visual fatigue reduction for depth-image-based rendering (DIBR) system is proposed. One important aspect of the method is that no calibration parameters are needed for adjustment. By analyzing 3D image warping, the perceived depth is expressed as a function of three adjustable parameters: virtual view number, scale factor and depth value of zero parallax setting (ZPS) plane. Adjusting these three parameters according to the proposed parameter modification algorithm when performing 3D image warping can effectively change the perceived depth of stereo pairs generated in DIBR system. As the depth adjustment is performed in simple 3D image warping equations, the proposed method is facilitative for hardware implementation. Experimental results show that the proposed depth adjustment method provides an improvement in visual comfort of stereo pairs as well as generating comfortable stereoscopic images with different perceived depths that people desire.

• ETRI Journal
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• v.33 no.4
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• pp.506-516
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• 2011

In this paper, we develop a registration method to eliminate the geometric inconsistency between the stereo-images and light detection and ranging (LIDAR) data obtained by an airborne multisensor system. This method consists of three steps: registration primitive extraction, correspondence establishment, and exterior orientation parameter (EOP) adjustment. As the primitives, we employ object points and linked edges from the stereo-images and planar patches and intersection edges from the LIDAR data. After extracting these primitives, we establish the correspondence between them, being classified into vertical and horizontal groups. These corresponding pairs are simultaneously incorporated as stochastic constraints into aerial triangulation based on the bundle block adjustment. Finally, the EOPs of the images are adjusted to minimize the inconsistency. The results from the application of our method to real data demonstrate that the inconsistency between both data sets is significantly reduced from the range of 0.5 m to 2 m to less than 0.05 m. Hence, the results show that the proposed method is useful for the data fusion of aerial images and LIDAR data.

• Journal of Internet Computing and Services
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• v.8 no.5
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• pp.117-123
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• 2007

Catadioptric mirrors are widely used in automatic surveillance system. The major drawback of catadioptric mirror is its unequal image resolution. Equidistance catadioptric mirrir can be the solution to this problem. 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 and simple focal length finding algorithm is presented. First two object's points are selected, and the counterparts on the other stereo image are to be found using MSE criterion. Using four pixel distance from the image center, the assumed focal length is calculated. If the obtained focal length is different from the exact focal length, 24mm, the focal length value is modified by the proposed method. The method is very simple and gives the comparable results with the earlier sophisticated method.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.74-74
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• 2002

This paper describes a corner matching technique for automatic relative orientation. Automatically matched corner points from stereo aerial images are used to a data set and help to improve automation of relative orientation process. A general corner matching process of overall image to image has very heavy operation and repetitive computation, so very time-consuming. But aerial stereo images are approximately seventy percent overlapped and little rotated. Based this hypothesis, we designed a sectional corner matching technique calculating correlation section by section between stereo images. Although the overlap information is not accurate, if we know it approximately, the matching process can be lighter. Since the size of aerial image is very large, corner extraction process is performed hierarchically by creating image pyramid, and corners extracted are refined at the higher level image. Extracted corners at the final step are matched section by section. Matched corners are filtered using positional information and their relation and distribution. Filtering process is applied over several steps because the thing affecting to get good result-good relative orientation parameter- is not the number of matched corner points but the accuracy of them. Filtered data is filtered one more during the process calculating relative orientation parameters. When the process is finished, we can get the well matched corner points and the refined Von-Gruber areas besides relative orientation parameters. This sectional corner matching technique is efficient by decreasing unnecessarily repetitive operations and contributes to improve automation for relative orientation.