• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1998.06a
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• pp.321-324
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• 1998

Pixel-Design Array Simulation Tool(PDAST) was used to profoundly the gate signal distortion and pixel changing capability, which are the most critical limiting factors for high-quality TFT-LCDs. Since PDAST can simulate the gate, data and pixel voltages of a certain pixel on TFT array at any time and at any location on an array, the effect of the resistivity of gate line material on the pixel operations can be effectively analyzed. The gate signal delay, pixel charging ratio, level-shift of the pixel voltage were simulated with varying the resis5tivity of the gate line material. The information obtained from this study could be utilized to design the larger area and finer image quality panel.

• Proceedings of the KOSOMBE Conference
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• v.1994 no.12
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• pp.47-51
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• 1994

In this paper we propose an algorithm to extract connected boundary with one-pixel thickness of chromosome, which has advantages as follows: easy to implement, low computational complexities, and ability to extract the boundary with either 4-pixel connectivity or 8-pixel connectivity

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.39 no.2
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• pp.92-98
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• 2003

The quantification of fish school abundance was carried out by using luminance of pixel on scanning sonar image, and compared with the indices of fish school abundance e.g. school number, school area and weighted school area. The survey was carried out in Funka Bay off southern Hokkaido, Japan using research vessel Ushio-Maru during December 1999. A 180-degree scanning sonar with a frequency of 164kHz was used. The school number was counted both left and right 40-degree radial lines from the center of own vessel mark on a scanning image. The school area was measured approximately as an ellipse from the school length and width. The weighted school area was calculated by multiplying school area and average value of inner pixel luminance. A quantification of pixel luminance was also measured to integrate squared pixel luminance value on these lines. Fish school and school bottom were discriminated by the produced sonar echogram using pixel luminance value on these lines. The relationships between the quantified luminance value and other abundance indices such as school area and weighted school area revealed a good correlation. Therefore, the quantified luminance is a useful method in estimating fish school abundance in the acoustic survey using sonar.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.482-485
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• 2004

We fabricated a hybrid bulk/fully depleted silicon on insulator (FDSOI) complementary metal oxide semiconductor (CMOS) active pixel image sensor. The active pixel is comprised of reset and source follower transistors on the SOI seed wafer, while the pinned photodiode and readout gate and floating diffusion are fabricated on the SOI handle wafer after the removal of the buried oxide. The source of dark current is eliminated by hybrid bulk/FDSOI pixel structure between localized oxidation of silicon (LOCOS) and photodiode(PD). By using the low noise hybrid pixel structure, dark currents qm be suppressed significantly. The pinned photodiode can also be optimized for quantum efficiency and reduce the noise of dark current. The spectral response of the pinned photodiode on the SOI handle wafer is very flat between 400 nm and 700 nm and the dark current that is higher than desired is about 10 nA/cm2 at a $V_{DD}$ of 2 V.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.1
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• pp.120-127
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• 2010

This paper presents a SR method using adaptive interpolation based on local gradient features to obtain a high quality SR image. In this method, the distance between the interpolated pixel and the neighboring valid pixel is considered by using local gradient properties. The interpolation coefficients take the local gradient of the LR images into account. The smaller the local gradient of a pixel is, the more influence it should have on the interpolated pixel. And the median filter is finally applied to reduce the blurring and noise of the interpolated HR image. Experiment results show the effectiveness of the proposed method in comparison with other methods, especially in the edge areas of the images.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.787-789
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• 2017

Edge detection is used in many applications such as image analysis, pattern recognition and computer vision. Existing edge detection methods, there is such Sobel, Prewitt, Roberts, and LoG(Laplacian of Gaussian). In the conventional edge detection method, edge detection is insufficient because the change of the pixel brightness is small when the original image is in low illumination. Therefore, in this paper, we proposed a function to convert the pixel brightness of low illumination image to solve this problem. And it was compared by applying the conventional methods Sobel, Prewitt, Roberts, LoG(Laplacian of Gaussian) to determine the performance of the pixel brightness transform function.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.681-684
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• 2015

Magnetization is very important in the ferro-magnetic physics and provides useful informations in the application field of magnetic devices. Generally, the only first acquired domain pattern is not helpful to recognize domain pattern. Many images are needed to visualize domain pattern through image processing. These images were obtained a 8-bit digital camera. The operation was the subtraction of pixel values of multi domain imanges from the images with 255 of pixel value, which was obtained in the saturated state of magnetic materials. The magnetic domain images was visualized gradually with increasing the number of subtracion operation. LABVIEW was used as an image processing tool and the optic microscope with a polarizer was used in this experiment.

• Proceedings of the KOSOMBE Conference
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• v.1990 no.11
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• pp.42-47
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• 1990

In this paper, a new adaptive image processing method based on human visual system has been presented. The basic idea behind the proposed method is to improve the efficiency of the information transfer channel regionally by manipulating the displayed image in order to compensate the regional inefficiency of the information transfer channel. The proposed method consists of two parts; the first part reallocates pixel values corresponding to high X-ray attenuation to that of more intense X-ray exposure by multiplying the pixel values with the local adaptive multiplcation factor, and the second part adjusts the pixel values of dark area of displayed image such as overexposed lung area to be more bright. The processed image with the proposed method shows significantly increased visibility of mediastinal and subdiaphramatic area, and also the lung area of over exposed case without any artifact.

• Journal of the Korean Magnetics Society
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• v.27 no.1
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• pp.35-40
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• 2017

Kerr microscopy was assembled to observe magnetic domain image of ultra thin 3 %Si-Fe by using parts of an optical microscope. Digital images were obtained from CCD camera attached to the microscopy. A method was suggested to decide a boundary between magnetic domain regions in this study. The method was using some operations such as subtraction, integration and least mean square approximation for pixel values in the digital image. The method has a strong point that high priced image processor is not needed in the Kerr microscopy system. From the results that three different domain walls were observed and magnetic flux density of 0.085 [T], this method could be applied in the magnetic domain regions having a straight $180^{\circ}$ domain wall.

• Structural Monitoring and Maintenance
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• v.9 no.3
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• pp.289-303
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• 2022

In this study, the impact of assigned pixel labels on the accuracy of crack image identification of steel structures is examined by using an atrous separable convolution neural network (ASCNN). Firstly, images containing fatigue cracks collected from steel structures are classified into four datasets by assigning different pixel labels based on image features. Secondly, the DeepLab v3+ algorithm is used to determine optimal parameters of the ASCNN model by maximizing the average mean-intersection-over-union (mIoU) metric of the datasets. Thirdly, the ASCNN model is trained for various image sizes and hyper-parameters, such as the learning rule, learning rate, and epoch. The optimal parameters of the ASCNN model are determined based on the average mIoU metric. Finally, the trained ASCNN model is evaluated by using 10% untrained images. The result shows that the ASCNN model can segment cracks and other objects in the captured images with an average mIoU of 0.716.