• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2313-2316
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• 2004

Accurate calibration effect for maladjusted stereo cameras with calibrated pixel distance parameter is presented. The camera calibration is a necessary procedure for stereo vision-based depth computation. Intra and extra parameters should be obtain to determine the relation between image and world coordination through experiment. One difficulty is in camera alignment for parallel installation: placing two CCD arrays in a plane. No effective methods for such alignment have been presented before. Some amount of depth error caused from such non-parallel installation of cameras is inevitable. If the pixel distance parameter which is one of intra parameter is calibrated with known points, such error can be compensated in some amount and showed the variable experiments for accurate effects.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.9
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• pp.53-57
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• 2009

There are technical requirements to manufacture large size functional parts with not only simple geometries like a flat or spherical surface but also sculptured geometries. In addition, the required machining accuracy for these parts is becoming more severe. In general, the form accuracy of machined parts is determined by the relative position between workpiece and tool during machining process. To improve machining accuracy the relative position errors should be maintained within the required accuracy. This study deals with the estimation and calibration of depth of cut using the AE signal in micro-machining. Also, this sensing technique can be applied to detect the initial contact between workpiece and tool.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2006.11a
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• pp.357-358
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• 2006

Accurate calibration matching for maladjusted stereo cameras with calibrated pixel distance parameter is presented. The camera calibration is a necessary procedure for stereo vision-based depth computation. Intra and extra parameters should be obtain to determine the relation between image and world coordination through experiment. One difficulty is in camera alignment for parallel installation: placing two CCD arrays in a plane. No effective methods for such alignment have been presented before. Some amount of depth error caused from such non-parallel installation of cameras is inevitable. If the pixel distance parameter which is one of Intra parameter is calibrated with known points, such error can be compensated in some amount and showed the variable experiments for accurate effects.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.171-174
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• 2003

In this paper, we propose the method of stereo images composition using adaptive dense disparity estimation. For the correct composition of stereo image and 3D virtual object, we need correct marker position and depth information. The existing algorithms use position information of markers in stereo images for calculating depth of calibration object. But this depth information may be wrong in case of inaccurate marker tracking. Moreover in occlusion region, we can't know depth of 3D object, so we can't composite stereo images and 3D virtual object. In these reasons, the proposed algorithm uses adaptive dense disparity estimation for calculation of depth. The adaptive dense disparity estimation is the algorithm that use pixel-based disparity estimation and the search range is limited around calibration object.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.6
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• pp.8-17
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• 2011

Recently, fusion camera systems that consist of depth sensors and color cameras have been widely developed with the advent of a new type of sensor, time-of-flight (TOF) depth sensor. The physical limitation of depth sensors usually generates low resolution images compared to corresponding color images. Therefore, the pre-processing module, such as camera calibration, three dimensional warping, and hole filling, is necessary to generate the high resolution depth map that is placed in the image plane of the color image. However, the result of the pre-processing step is usually inaccurate due to errors from the camera calibration and the depth measurement. Therefore, in this paper, we present a depth map upsampling method robust these errors. First, the confidence of the measured depth value is estimated by the interrelation between the color image and the pre-upsampled depth map. Then, the detailed depth map can be generated by the modified kernel regression method which exclude depth values having low confidence. Our proposed algorithm guarantees the high quality result in the presence of the camera calibration errors. Experimental comparison with other data fusion techniques shows the superiority of our proposed method.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.693-696
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• 1998

For camera calibration, this paper describes two steps to camera constants and camera parameters. The former is the radial distortion of lens, image center and focal length etc.. The latter is translation, rotation etc.. Camera calibration use tsai's algorithm. In this paper, the solutions are introduced into overdetermined system as matching points that are acquired from two CCD and measured object depth information.

• Journal of the Semiconductor & Display Technology
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• v.22 no.1
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• pp.72-77
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• 2023

In many manufacturing settings, including the semiconductor industry, products are completed by producing and assembling various components. Sorting out from randomly mixed parts and classification operations takes a lot of time and labor. Recently, many efforts have been made to select and assemble correct parts from mixed parts using robots. Automating the sorting and classification of randomly mixed components is difficult since various objects and the positions and attitudes of robots and cameras in 3D space need to be known. Previously, only objects in specific positions were grasped by robots or people sorting items directly. To enable robots to pick up random objects in 3D space, bin picking technology is required. To realize bin picking technology, it is essential to understand the coordinate system information between the robot, the grasping target object, and the camera. Calibration work to understand the coordinate system information between them is necessary to grasp the object recognized by the camera. It is difficult to restore the depth value of 2D images when 3D restoration is performed, which is necessary for bin picking technology. In this paper, we propose to use depth information of RGB-D camera for Z value in rotation and movement conversion used in calibration. Proceed with camera calibration for accurate coordinate system conversion of objects in 2D images, and proceed with calibration of robot and camera. We proved the effectiveness of the proposed method through accuracy evaluations for camera calibration and calibration between robots and cameras.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.9 s.174
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• pp.115-122
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• 2005

Errors resulting from magnification variations of a optical system are largely generated in three-dimensional shape measurements based on depth-from-focus. In the case of measuring the surface morphology of tiny objects based on DFF, images are acquired with a very small interval so that magnification changes can be minimized. However, the magnification variations are actually existed in the acquired images and so focus measures are wrongly or ambiguously extracted. In this paper, a methodology with linear magnification calibrations, based on DFF, is proposed to make more accurate measurement in surface morphology with high depth discontinuity, compared with previous ones. Several experiments show that the proposed method outperforms existing ones without magnification calibrations.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2010.03b
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• pp.5-5
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• 2010

The depth of the object pointed by the laser beam is computed depending on the pixel position on the CCD There involved several number of internal and external parameters such as inter-pixel distance, focal length, position and orientation of the system components in the depth measurement error. In this paper, it is shown through the error sensitivity analysis of the parameters that the most important parameters in the sense of error sources are the angle of the laser beam and the inter pixel distance. Also, the calibration technique to minimize their effect for the depth computation is proposed.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.05b
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• pp.109-114
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• 2003

Depth error correction effect for maladjusted stereo cameras with calibrated pixel distance parameter is presented. The camera calibration is a necessary procedure for stereo vision-based depth computation. Intra and extra parameters should be obtain to determine the relation between image and world coordination through experiment. One difficulty is in camera alignment for parallel installation: placing two CCD arrays in a plane. No effective methods for such alignment have been presented before. Some amount of depth error caused from such non-parallel installation of cameras is inevitable. If the pixel distance parameter which is one of intra parameter is calibrated with known points, such error can be compensated in some amount. Such error compensation effect with the calibrated pixel distance parameter is demonstrated with various experimental results.