• Journal of Platform Technology
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• v.12 no.3
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• pp.16-26
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• 2024

Videos shot underwater are known to have significant color distortion. Typical causes are backscattering by floating objects and attenuation of red colors in proportion to the depth of the water. In this paper, we aim to analyze color correction performance and color distortion patterns for images taken underwater. Backscattering and attenuation caused by suspended matter will be discussed in the next study. In this study, based on the DeepSeeColor model proposed by Jamieson et al., we verify color correction performance and analyze the pattern of color distortion according to changes in water depth. The input images were taken in the US Virgin Islands by Jamieson et al., and out of 1,190 images, 330 images including color charts were used. Color correction performance was expressed as angular error using the input image and the correction image using the DeepSeeColor model. Jamieson et al. calculated the angular error using only black and white patches among the color charts, so they were unable to provide an accurate analysis of overall color distortion. In this paper, the color correction error was calculated targeting the entire color chart patch, so an appropriate degree of color distortion can be suggested. Since the input image of the DeepSeeColor model has a depth of 1 to 8, color distortion patterns according to depth changes can be analyzed. In general, the deeper the depth, the greater the attenuation of red colors. Color distortion due to depth changes was modeled in the form of scale and offset movement to predict distortion due to depth changes. As the depth increases, the scale for color correction increases and the offset decreases. The color correction performance using the proposed method was improved by 41.5% compared to the conventional method.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.7
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• pp.611-617
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• 2004

This paper presents a simple method of rotational motion estimation and correction for roll axis stabilization of an image. The scheme first computes the rotation center by taking least squares of selected local velocity vectors, and the rotational angle is found from special subset of motion vectors. Roll motion correction is then performed by the nearest neighbor interpolation technique. To show the effectiveness of our approach, the synthetic and real images are evaluated, resulting in better performance than the previous ones.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.153-155
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• 2004

This paper proposes a real-time approach on the rotational motion estimation and correction for the roll stabilization of the sight system. This method first estimates a rotation center by the least-mean square algorithm based on the motion vectors of some feature points. And, then, a rotation angle is searched for a best matching block between a reference block image and seccessive input images using MPC(maximum pixel count) matching criterion. Finally, motion correction is performed by the bilinear interpolation technique. Various computer simulations show that the estimation performance is good and the proposed algorithm is a real-time implementable one to the TMS320C6415(500MHz) DSP.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.51 no.1
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• pp.46-54
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• 2002

Plasma Display Panel (PDP) is required to be both the determination of white point of each gray level and the inverse gamma correction since no-balanced RGB cell and linear property of PDP, respectively. However, these two methods cause degradation of grey level representation and undesirable false contour in the dark areas on PDP. In this paper, we implemented real time image processor of the proposed error diffusion algorithm and unsharp masking operation to protect the blurring image caused by the error diffusion. Experimental results showed drastic improvements of gray level representation and reduction of undesirable false contour.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2000.04a
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• pp.129-133
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• 2000

It is reasonable to use the stereo vision and image processing technique to digitize 3D coordinates of grid points and to evaluate surface strains on a sheet metal parts. However this method has its intrinsic problems such as the difficulty in enhancement of bad images inevitable error due to digital image resolution of camera and frame grabber unreliability of strains and thickness evaluated from coarse grid on the corner area with large curvature and the limitation of the area that can be measured at a time. Therefore it is still hard to measure strain distribution over the entire surface of a medium,- or large-sized stamped part at a time even by using an automated strain measurement system. In this study the curvature correction algorithm based on the grid refinement and the geometry assembling algorithm based on the global error minimization (GEM) scheme are suggested. Several applications are presented to show the reliability and efficiency of these algorithms.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.5
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• pp.426-431
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• 2008

In this paper, an improved AE system for digital still camera is proposed. AE system is auto exposure system to maintain optimized brightness of output image. But there is limitation for mobile devices to get high quality image with the conventional AE algorithm, because of organizational restriction of system. The conventional research has been studied only electronic shutter and AGC on the AE algorithm. In this paper, we suggest new AE algorithm included target setting, frame delay, Gamma Correction as well as electronic shutter and AGC to get high quality image. The proposed algorithm show improved result at control speed and ability of luminance expression.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.13 no.11
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• pp.901-907
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• 2000

As the minimum feature size for making ULSI approaches the wavelength of light source in optical lithography, the aerial image is so hardly distorted because of the optical proximity effect that the accurate mask image reconstruction on wafer surface is almost impossible. We applied the Optical Proximity Correction(OPC) on isolated patterns assuming Attenuated Phase Shift Mask(APSM) as well as binary mask, to correct the widening of isolated patterns. In this study, we found that applying OPC to APSM shows much better improvement not only in enhancing the resolution and fidelity of t도 images but also in enhancing the process margin than applying OPC to the binary mask. Also, we propose the OPC method of APSM for isolated patterns, the size of which is less than the wavelength of the ArF excimer laser. Finally, we predicted the resolution limit of optical lithography through the aerial image simulation.

• 한국지구물리탐사학회:학술대회논문집
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• 2006.06a
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• pp.221-224
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• 2006

seismic crosshole tomography works applying borehole deviation correction were performed at a test site to detect a small cavity. Two correction methods were applied. The one is the constant distance correction which adds constant distance to surface borehole distance and the other is the constant angle correction which considers an angle between surface borehole location and bottom borehole location. After applying the corrections, the distortions of the image diminished while its resolution improved. Though the constant angle correction is the most appropriate correction method, the constant distance correction can delineate the small cavity sufficiently.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1103-1109
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• 2014

The motion recognition system has been broadly studied in digital image and video processing fields. Recently, method using th depth image is used very useful. However, recognition accuracy of depth image based method will be loss caused by size and shape of object distorted for angle of the depth sensor. Therefore, distortion correction of depth sensor is positively necessary for distinguished performance of the recognition system. In this paper, we propose a pre-processing algorithm to improve the motion recognition system. Depth data from depth sensor converted to real world, performed the corrected angle, and then inverse converted to projective world. The proposed system make progress using the OpenCV and the window program, and we test a system using the Kinect in real time. In addition, designed using Verilog-HDL and verified through the Zynq-7000 FPGA Board of Xilinx.

• Journal of the Korea Computer Graphics Society
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• v.23 no.3
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• pp.95-103
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• 2017

Horizon correction is a crucial stage for image composition enhancement. In this paper, we propose a deep learning based method for estimating the slanted angle of a photograph and correcting it. To estimate and correct the horizon direction, existing methods use hand-crafted low-level features such as lines, planes, and gradient distributions. However, these methods may not work well on the images that contain no lines or planes. To tackle this limitation and robustly estimate the slanted angle, we propose a convolutional neural network (CNN) based method to estimate the slanted angle by learning more generic features using a huge dataset. In addition, we utilize multiple adaptive spatial pooling layers to extract multi-scale image features for better performance. In the experimental results, we show our CNN-based approach robustly and accurately estimates the slanted angle of an image regardless of the image content, even if the image contains no lines or planes at all.