• Journal of the Korean Society for Precision Engineering
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• v.23 no.10
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• pp.22-29
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• 2006

This paper considers the lens distortions such as a fisheye distortion and a perspective distortion. While a fisheye lens has a wide field-of-view, it causes a large distortion to the images. Regardless of a fisheye lens or a rectilinear lens, a lens generates perspective distortion in a vertical direction when the lens views in an upward direction or downward direction. These distortions deform images differently from human visual functions. Therefore, this paper presents a method to correct the distortions, and whereby, the research in this paper enlarges choices of images to image processing algorithm that may select the distorted images and the corrected images depending on applications. An infinite polynomial model is employed in the fisheye radial distortion correction, and the vertical perspective distortion correction is done by using a vanishing point. The methods introduced in this paper are implemented on the images captured by a rear-view camera installed on a vehicle and showed their robustness of the correction.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.4
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• pp.55-63
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• 2011

Having a wide angle of view, a fisheye lens is useful for obtaining images of the inside wall of a tunnel. A circular fisheye tunnel image can be transformed into a familiar rectangular image by applying the concept of cylindrical projection. This projection transformation causes several types of distortions in the projected image. This paper discusses the distortion on the boundary lines between smoothly curved wall and flat ground. We analyzed the cause of this boundary distortion, developed transformation model, and derived a correction formular. A distortion correction software programmed in Visual C++ applied to projected image. Consequently, boundary-corrected image could be obtained. Research into other distortions of projected image will helpful in obtaining tunnel image that resembles real tunnel from fisheye tunnel image.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.6
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• pp.339-344
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• 2013

This paper presents an automatic focal length estimation method to correct the fisheye lens distortion in a spatially adaptive manner. The proposed method estimates the focal length of the fisheye lens by generating two reference focal lengths. The distorted fisheye lens image is finally corrected using the orthographic projection model. The experimental results showed that the proposed focal length estimation method is more accurate than existing methods in terms of the loss rate.

• Journal of Korea Multimedia Society
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• v.23 no.3
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• pp.395-401
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• 2020

In this paper, a motion-based ROI extraction algorithm from a high resolution fisheye image is proposed for multi-view monitoring systems. Lately fisheye cameras are widely used because of the wide angle-of-view and they basically provide a lens correction functionality as well as various viewing modes. However, since the distortion-free angle of conventional algorithms is quite narrow due to the severe distortion ratio, there are lots of unintentional dead areas and they require much computation time in finding undistorted coordinates. Thus, the proposed algorithm adopts an image decimation and a motion detection methods, that can extract the undistorted ROI image with a standard angle-of-view for the fast and intelligent surveillance system. In addition, a mesh-type ROI is presented to reduce the lens correction time, so that this independent ROI scheme can parallelize and maximize the processor's utilization.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.281-284
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• 2007

A realization for image distortion correction processing system with DSP processor is presented in this paper. The image distortion correcting algorithm is realized by DSP processor for focusing on more real time processing than image quality. The lens and camera distortion coefficients are processed by YCbCr Lookup Tables and the correcting algorithm is applied to reverse mapping method for geometrical transform. The system experimentation results in the processing time about 34.6 msec on $720{\times}480$ curved image at 150 degree visual range.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.2
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• pp.177-182
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• 2015

General method for correcting the distortion caused by the characteristic of the fish-eye lens may be classified in two ways. The first method is a calibration method using a mathematical model taking into account the characteristics of the lens, the second method is a method using only the distortion correction image, regardless of the lens. When considering the characteristics of the lens, calibration equation can be calculated geometrically from the relationship between the three-dimensional real-world coordinates and two-dimensional image coordinates and the parameters of lens. However, it is not suitable for ellipsoid type lens, because of existing research papers have been corrected on the spherical-type fisheye lens. In this paper, we propose a method for correcting geometrically using fish-eye lens as an ellipsoid model. Through a calibration picture, it can be seen that the proposed method is valid.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.7
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• pp.181-190
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• 2013

We propose an interpolation method considering barrel distortion of fisheye lens using nearest pixels on a corrected image. The correction of barrel distortion comprises coordinate transformation and interpolation. This paper focuses on interpolation. The proposed interpolation method uses nearest four coordinates on a corrected image rather than on a distorted image unlike existing techniques. Experimental results show that both subjective and objective image qualities are improved.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.11
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• pp.2116-2120
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• 2007

A realization for image distortion correction processing system with DSP processor is presented in this paper. The image distortion correcting algorithm is realized by DSP processor for focusing on more real time processing than image quality. The lens and camera distortion coefficients are processed by the Lookup Tables and the correcting algorithm is applied to reverse mapping method for geometrical transform. The system experimentation results in the processing time about 31.3 msec $720{\times}480$ wide range image, and the image is stable and spontaneous to be about 8.3% average PSNR variation with changing a wide angle.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.601-605
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• 2009

Due to the fact that fish-eye lens can provide super wide angles with the minimum number of cameras, field-of-view over 180 degrees, many vehicles are attempting to mount the camera system. Camera calibration should be preceded, and geometrical correction on the radial distortion is needed to provide the images for the driver's assistance. However, vehicle fish-eye cameras have diagonal output images rather than circular images and have asymmetric distortion beyond the horizontal angle. In this paper, we introduce a camera model and metric calibration method for vehicle cameras which uses feature points of the image. And undistort the input image through a perspective projection, where straight lines should appear straight. The method fitted vehicle fish-eye lens with different field of views.

• Journal of the Korea Society for Simulation
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• v.19 no.1
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• pp.23-31
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• 2010

Due to the fact that fisheye lens can provide super wide angles with the minimum number of cameras, field-of-view over 180 degrees, many vehicles are attempting to mount the camera system. Not only use the camera as a viewing system, but also as a camera sensor, camera calibration should be preceded, and geometrical correction on the radial distortion is needed to provide the images for the driver's assistance. In this thesis, we introduce a geometric correction technique to minimize the loss of the image data from a vehicle fish-eye lens having a field of view over $180^{\circ}$, and a asymmetric distortion. Geometric correction is a process in which a camera model with a distortion model is established, and then a corrected view is generated after camera parameters are calculated through a calibration process. First, the FOV model to imitate a asymmetric distortion configuration is used as the distortion model. Then, we need to unify the axis ratio because a horizontal view of the vehicle fish-eye lens is asymmetrically wide for the driver, and estimate the parameters by applying a non-linear optimization algorithm. Finally, we create a corrected view by a backward mapping, and provide a function to optimize the ratio for the horizontal and vertical axes. This minimizes image data loss and improves the visual perception when the input image is undistorted through a perspective projection.