• Journal of the Optical Society of Korea
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• v.14 no.3
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• pp.245-259
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• 2010

We have developed mathematically precise image-processing algorithms for extracting panoramic images from fisheye images. Furthermore, we have successfully built a DSP-based panoramic camera employing single fisheye lens.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.1
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• pp.117-121
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• 2009

The fisheye image acquired with a fisheye camera has wider field of view than a general use camera. But large distortion of the object in the image requires conversion of the fisheye image to the perspective image because of user's difficult perception. The existing Ishii's method[1] has the problem that the object can has sire and geometrical distortion in the transformed image because it uses equidistance projection. This paper presented a conversion technique of the fisheye image to the perspective image using sealing function. In the experiments, it was shown that our method reduced size and geometrical distortion by applying the scaling function.

• 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 the Institute of Electronics Engineers of Korea SP
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• v.49 no.4
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• pp.16-22
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• 2012

In this paper, we present spiral pattern which suits for optical simulator to calibrate fisheye lens and compensate geometric distortion. Using spiral pattern, we present calibration without mathematical modeling in advance. Proposed spiral pattern used to input image of optical simulator. Using fisheye lens image, we calibrate a fisheye lens by matching geometrically moved dots to corresponding original dots which leads not to need mathematical modeling. Proposed algorithm calibrates using dot matching which matches spiral pattern image dot to distorted image dot. And this algorithm does not need modeling in advance so it is effective. Proposed algorithm is enabled at processing of pattern recognition which has to get the exact information using fisheye lens for digital zooming. And this makes possible at compensation of geometric distortion and calibration of fisheye lens image applying in various image processing.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.20-30
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• 2022

Recently, as VR (Virtual Reality) technology has been in the spotlight, 360° panoramic images that can view lively VR contents are attracting a lot of attention. Image stitching technology is a major technology for producing 360° panorama images, and many studies are being actively conducted. Typical stitching algorithms are based on feature point-based image stitching. However, conventional feature point-based image stitching methods have a problem that stitching results are intensely affected by feature points. To solve this problem, deep learning-based image stitching technologies have recently been studied, but there are still many problems when there are few overlapping areas between images or large parallax. In addition, there is a limit to complete supervised learning because labeled ground-truth panorama images cannot be obtained in a real environment. Therefore, we produced three fisheye images with different camera centers and corresponding ground truth image through carla simulator that is widely used in the autonomous driving field. We propose image stitching model that creates a 360° panorama image with the produced fisheye image. The final experimental results are virtual datasets configured similar to the actual environment, verifying stitching results that are strong against various environments and large parallax.

• 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.

• Journal of the Optical Society of Korea
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• v.14 no.2
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• pp.109-120
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• 2010

We have developed mathematically precise image-processing algorithms for extracting rectilinear images from fisheye images as well as digital pan/tilt/zoom technology. Using this technology, vertical lines always appear as vertical lines in the panned and/or tilted images. Furthermore, polygonal panoramic images composed of multiple rectilinear images have been obtained using the developed digital pan/tilt technology.

• Journal of Sensor Science and Technology
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• v.22 no.6
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• pp.393-399
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• 2013

We propose a method of sensing the rotation and distance of a camera by using a fisheye lens system as a vision sensor. We estimate the rotation angle of a camera with a modified correlation method by clipping similar regions to avoid symmetry problems and suppressing highlight areas. In order to eliminate the rectification process of the distorted points of a fisheye lens image, we introduce an offline process using the normalized focal length, which does not require the image sensor size. We also formulate an equation for calculating the distance of a camera movement by matching the feature points of the test image with those of the reference image.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.10
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• pp.1021-1028
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• 2009

In this paper, a location identification for a cleaning robot using a camera shooting forward a room ceiling which kas three point landmarks is introduced. These three points are made from a laser source which is placed on an auto charger. A fisheye lens covering almost 150 degrees is utilized and the image is transformed to a camera image grabber. The widly shot image has an inevitable distortion even if wide range is coverd. This distortion is flatten using an image warping scheme. Several vision processing techniques such as an intersection extraction erosion, and curve fitting are employed. Next, three point marks are identified and their correspondence is investigated. Through this image processing and image distortion adjustment, a robot location in a wide geometrical coverage is identified.

• Journal of Conservation Science
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• v.37 no.4
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• pp.312-321
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• 2021

Underwater archaeology relies heavily on photography and video image recording during surveillances and excavations like ordinary archaeological studies on land. All underwater images suffer poor image quality and distortions due to poor visibility, low contrast and blur, caused by differences in refractive indices of water and air, properties of selected lenses and shapes of viewports. In the Yellow Sea (between mainland China and the Korean peninsula), the visibility underwater is far less than 1 m, typically in the range of 30 cm to 50 cm, on even a clear day, due to very high turbidity. For photographing 1 m x 1 m grids underwater, a very wide view angle (180°) fisheye lens with an 8 mm focal length is intentionally used despite unwanted severe barrel-shaped image distortion, even with a dome port camera housing. It is very difficult to map wide underwater archaeological excavation sites by combining severely distorted images. Development of practical compensation methods for distorted underwater images acquired through the fisheye lens is strongly desired. In this study, the source of image distortion in underwater photography is investigated. We have identified the source of image distortion as the mismatching, in optical axis and focal points, between dome port housing and fisheye lens. A practical image distortion compensation method, using customized image processing software, was explored and verified using archived underwater excavation images for effectiveness in underwater archaeological applications. To minimize unusable area due to severe distortion after distortion compensation, practical underwater photography guidelines are suggested.