• International Journal of Quality Innovation
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• v.5 no.1
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• pp.68-84
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• 2004

The measured values of a same object should remain constant regardless of the object's position in the image. In other words, its measured values should not vary as its position in the image changes. However, lens' image distortion, heterogeneous light source, varied angle between the measuring apparatus and the object, and different surroundings where the testing is set up will all cause variation in the measurement of the object when the object's position in the image changes. This research attempts to compensate the machine vision image distortion caused by the object's position in the image by developing the compensation table. The compensation is accomplished by facilitating users to obtain the correcting object and serves the objective of improving the precision of measurement.

• 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.

• Journal of Conservation Science
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• v.38 no.1
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• pp.14-32
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• 2022

Underwater photographing and image recording are essential for pre-excavation survey and during excavation in underwater archaeology. Unlike photographing on land, all underwater images suffer various quality degradations such as shape distortions, color shift, blur, low contrast, high noise levels and so on. Outcome is very often heavily photographing equipment and photographer dependent. Excavation schedule, weather conditions, and water conditions can put burdens on divers. Usable images are very limited compared to the efforts. In underwater archaeological study in very turbid water such as in the Yellow Sea (between mainland China and the Korean peninsula), underwater photographing is very challenging. In this study, off-site image distortion and color compensation techniques using an image processing/analysis software is investigated as an alternative image quality enhancement method. As sample images, photographs taken during the excavation of 800-year-old Taean Mado Shipwrecks in the Yellow Sea in 2008-2010 were mainly used. Significant enhancement in distortion and color compensation of archived images were obtained by simple post image processing using image processing/analysis software (PicMan) customized for given view ports, lenses and cameras with and without optical axis offsets. Post image processing is found to be very effective in distortion and color compensation of both recent and archived images from various photographing equipment models and configurations. Merits and demerit of in-situ, distortion and color compensated photographing with sophisticated equipment and conventional photographing equipment, which requires post image processing, are compared.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.5
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• pp.999-1004
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• 2012

In this paper, camera modules and lens's images were analyzed for the compensation of distortion image by wide angle lens based WDR(Wide Dynamic Range) with high resolution sensor(2-Mega CMOS Image sensor). Due to wide angle ($176^{\circ}$) of designed wide angle camera modules, the compensation result of distorted image was analyzed, and the application of these modules was proposed for smart NUX(Natural User eXprience).

• 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.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.167-170
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• 2000

In this paper, we propose the edge compensation algorithm which connects the adjacent edges without losing the information of the skeletons on the edge image. The proposed edge compensation algorithm is composed of succeeding two steps. In the first step, the uplifted image is obtained by applying the uplifting process to the edge image. The next step is to extract the edge image from the uplifted image using the skeleton extraction algorithm. Experimental results show that the proposed method connects the adjacent edges without the distortion of the original edge information compared to the traditional method

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.9
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• pp.2299-2311
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• 2013

As portable multimedia devices become more popular and smaller, the use of portable projectors is also rapidly increasing. However, when portable projectors are used in mobile environments in which a dedicated planar screen is not available, the problem of geometric distortion of the projected image often arises. In this paper, we present a geometric image compensation method for portable projectors to compensate for geometric distortions of images projected on various types of planar or nonplanar projection surfaces. The proposed method is based on extraction of the two-dimensional (2D) geometric information of a projection area, setting of the compensation area, and prewarping using 2D homography. The experimental results show that the proposed method allows effective compensation for waved and arbitrarily shaped projection areas, as well as tilted and bent surfaces that are often found in the mobile environment. Furthermore, the proposed method is more computationally efficient than conventional image compensation methods that use 3D geometric information.

• The Transactions of the Korea Information Processing Society
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• v.5 no.4
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• pp.1044-1047
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• 1998

Non-destructive x-ray inspection system needs image intensifier to obtain the x-ray image. Captured image from image intensifier is distorted because the input plate of image intensifier has a spherical surface. In the research, in order to compensate this image distortion, we created the model of image intensifier and show mathematically that the image distortion was compensated. To show the performance of the proposed method, experiment was performed in real x-ray inspection system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.5
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• pp.2209-2213
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• 2011

When taking PET/CT, the distortion of the image happens due to the movement of a lesion with respiration. In this study, the experiment was conducted to see if the change in SUV value and distortion of the image could be somewhat corrected by comparing the image which was not compensated with that of the region of lung nodule, compensated with respiration compensation Plumonary Toolkit possessed by this hospital. The records of 17 patients with Lung cancer between May and August 2008. As the result of the experiment, Max SUV value increased by from 4.08% minimum to 43.10% maximum, and the average Max SUV value of lung nodule increased from 6.07 to 7.00(12.16%). In the case of respiration compensation PET/CT, the distortion of the image improved. As there was no significance in the comparison of SCC and Adenocarcinom respectively, though there was a statistically significant level(P<0.05) before and after respiration compensation in SCC-Adenocarcinoma, there was an effect in respiration compensation regardless of Cell types. As the result of the experiment, it was found out that the distortion of standard intake coefficient value and the image was compensated Therefore, the diagnosis of lung cancer and follow up will be able to help.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.6
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• pp.675-683
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• 2001

In this paper, we propose the edge compensation algorithm which connects the adjacent edges without losing the information of the skeletons on the edge image. The proposed edge compensation algorithm is composed of succeeding two steps. In the first step, the uplifted image is obtained by uplifting the edge image repeatedly. The next step is to extract the edge image from the uplifted image using the skeleton extraction algorithm. Experimental results show that the proposed method connects the adjacent edges without the distortion of the original edge information compared to the traditional method.