• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.6
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• pp.115-123
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• 2011

Most of cameras being used in practice induce lens distortion; the amount of distortion depends on the specific applications as well as the camera cost. Up to now, many methods of lens distortion correction have relied on invariant properties of projective geometry to find distortion parameters. A common property is "the straight line in scene is straight line in image". However, if the straight lines are also parallel together, the previous works have missed this restriction in determining lens distortion parameters. In this paper, we propose a method that leads to guarantee of the restrictions simultaneously for the determination. Therefore, corrected image will close to an ideal image taken by the pinhole camera model. The effectiveness of the proposed method is verified by our experiments on both synthetic images and real images.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.179-183
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• 2002

This paper presents a new approach to the calibration of a SCARA robot orientation with a camera modeling that accounts for major sources of camera distortion, namely, radial, decentering, and thin prism distortion. radial distortion causes an inward or outward displacement of a given Image point from its ideal location. Actual optical systems are subject to various degrees of decentering, that is, the optical centers of lens elements are not strictly collinear. Thin prism distortion arises from imperfection in lens design and manufacturing as well as camera assembly It is our purpose to develop the vision system for the pattern recognition and the automatic test of parts and to apply the line of manufacturing.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.10a
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• pp.225-229
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• 1997

This paper describes the camera calibration based-neural network with a camera modeling that accounts for major sources of camera distortion, namely, radial, decentering, and thin prism distortion. Radial distortion causes and inward or outward displacement of a given image point from its ideal location. Actual optical systems are subject to various degrees of decentering, that is, the optical centers of lens elements are not strictly collinear. Thin prism distortion arises from imperfection in lens design and manufacturing as well as camera assembly. It is our purpose to develop the vision system for the pattern recognition and the automatic test of parts and to apply the line of manufacturing. The performance of proposed camera calibration is illustrated by simulation and experiment.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.10a
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• pp.65-69
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• 1997

This paper presents a new approach to the calibration of a SCARA robot orientation with a camera modeling that accounts for major sources of camera distortion, namely, radial, decentering, and thin prism distortion. Radial distortion causes an inward or outward displacement of a given image point from its ideal location. Actual optical systems are subject to various degrees of decentering, that is, the optical centers of lens elements are not strictly collinear. Thin prism distortion arises from imperfection in lens design and manufacturing as well as camera assembly. It is our purpose to develop the vision system for the pattern recognition and the automatic test of parts and to apply the line of manufacturing.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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• pp.117-121
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• 2001

This paper presents a new approach to the calibration of a SCARA robot orientation with a camera modeling that accounts for major sources of camera distortion, namely, radial, decentering, and thin prism distortion. Radial distortion causes an inward or outward displacement of a given image point from its ideal location. Actual optical systems are subject to various degrees of decentering, that is, the optical centers of lens elements are not strictly collinear. Thin prism distortion arises from imperfection in lens design and manufacturing as well as camera assembly. It is our purpose to develop the vision system for the pattern recognition and the automatic test of parts and to apply the line of manufacturing.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1090-1093
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• 2004

In this paper, a problem of geometrically distorted images is considered. In particular, the paper discusses the detection of a watermark from a photographed image of the watermarked picture. The image is possibly obtained by using a digital camera. This watermark detection problem is made difficult by various geometric distortions added to the original picture through the printing and photographing processes. In particular, the paper focuses on the geometric distortion due to a projective transformation, as part of a camera 3D-to-2D imaging process. It is well-known that a cross ratio of collinear points is invariant under a perspective projection. By exploiting this fact, a projective-invariant digital watermarking technique is developed. By detecting the picture's corners, and the image center point at the intersection of two main diagonal lines, predefined cross ratios are used to compute the watermark embedded locations. From those identified embedding pixel locations, a watermark can be detected by performing a correlation between a watermark pattern and the image over those pixels. The proposed method does not require an inverse transformation on the distorted image, thus simplifying the detection process. Performance of the proposed method has been analyzed through computer experiments

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.75-80
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• 2002

The mainly used technique to rectify satellite images with distortion is to develop a mathematical relationship between the pixel coordinates on the image and the corresponding points on the ground. By defining the relationship between two coordinate systems, a polynomial model is designed and various linear transformations are used. These GCP based geometric correction has performed overall plane to plane mapping. In the overall plane mapping, overall structure of a scene is considered, but local variation is discarded. The highly variant height of region is resampled with distortion in the rectified image. To solve this problem this paper proposed the TIN-based rectification on a satellite image. The TIN based rectification is good to correct local distortion, but insufficient to reflect overall structure of one scene. So, this paper shows the experimental result and the analysis of each rectification model. It also describes the relationship GCP distribution and rectification model. We can choose a geometric correction model as the structural characteristic of a satellite image and the acquired GCP distribution.

• Journal of Power System Engineering
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• v.15 no.4
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• pp.25-30
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• 2011

This study is made to provide with a method for correcting the geometric distortion of the digital radiography image by analytical approach based upon the inverse square law and Beer's law. This study is aimed to find out and improve a mathematic model of nonlinear type. Variations in the alignment of the X-ray source, the object, and imaging plate affect digital radiography images. A model which is expressed in parameter values; e.g, angle, position, absorption coefficient, length, width and pixel account of radiography source, is developed so as to match the sample image. For the best correction of the digital image that is the most similar to the model image, a correction technique based upon tangent is developed; then applied to the digital radiography images of steel tubes. As a result, the image correction is confirmed to be made successfully.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.2
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• pp.136-144
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• 1997

Usually triangular patches are used to transfer geometric shape in Rapid Prototyping CAM system. STL, a list of triangles, is de facto standard in RP industry. Because STL does not have topological infoma- tion, it can cause errornous results. So STL should be verified before using. After adding support structures to anchor the part to the platform and to prevent sagging or distortion, slicing and layer by layer manufactur- ing process are done. But triangular patch is surface model and cannot provide sufficient information on geometry in the above processes. So, geometric modeling is necessary in verifying STL, adding support structures and slicing. It is natural that triangle based modeling is the best when tringular patches are used as input. Considering support structures, solid and faces coexist in RP process. Therefore non-manifold modeler is required. In this study, triangle based non-manifold geometric modeling is proposed for RP sys- tem consistent with STL input.

• The Journal of the Korea Contents Association
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• v.11 no.3
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• pp.1-8
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• 2011

Automatic vehicle license plate recognition technology is widely used in gate control and parking control of vehicles, and police enforcement of illegal vehicles. However inherent geometric information of the license plate can be transformed in the vehicle images due to the slant and the sunlight or lighting environment. In this paper, a distortion invariant vehicle license plate extraction and recognition algorithm is proposed. First, a binary image reserving clean character strokes can be achieved by using a DoG filter. A plate area can be extracted by using the location of consecutive digit numbers that reserves distortion invariant characteristic. License plate is recognized by using neural networks after geometric distortion correction and image enhancement. The simulation results of the proposed algorithm show that the accuracy is 98.4% and the average speed is 0.05 seconds in the recognition of 6,200 vehicle images that are obtained by using commercial LPR system.