• 한국정보디스플레이학회:학술대회논문집
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• 2003.07a
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• pp.68-71
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• 2003

To be able to show moving images without visual problems like blurring and tailing, the response time of liquid crystal display (LCDs) must be improved. In this paper we will discuss our progress in improving the response time by optimizing the cell configuration and the use of new liquid crystal mixtures. A 20.1inch diagonal UXGA IPS TFT-LCD has been developed having a response time as fast as l-frame time (16msec) for white-black operation and less than 16msec in all gray levels without applying ODC (Over Driving Circuit). This is very important because one of the technology to reduce motion blurring, the use of scanning backlight is conditioned by 16msec for all grays. The excellent gray-to-gray response can be explained by virtue of fundamental characteristics of S-IPS mode and makes a good contrast with the results of VA mode.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2005.05a
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• pp.115-124
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• 2005

This paper analyzes the problems that occurred in the magnification process for a fine input image and investigates a method to improve the problems. This paper applies a curve interpolation algorithm in CAD/CAM for the same test images with the existing image algorithm in order to improve the problems. As a result. the nearest neighbor interpolation. which is the most frequently applied algorithm for the existing image interpolation algorithm. shows that the identification of a magnified image is not possible. Therefore. this study examines an interpolation of gray-level data by applying a low-pass spatial filter and verifies that a bilinear interpolation presents a lack of property that accentuates the boundary of the image where the image is largely changed. The periodic B-spline interpolation algorithm used for curve interpolation in CAD/CAM can remove the blurring but shows a problem of obscuration, and the Ferguson's curve interpolation algorithm shows a more sharpened image than that of the periodic B-spline algorithm. For the future study, hereafter. this study will develop an interpolation algorithm that has an excel lent improvement for the boundary of the image and continuous and flexible property by using the NURBS. Ferguson's complex surface. and Bezier surface used in CAD/CAM engineering based on. the results of this study.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.9
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• pp.66-75
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• 1999

Image segmentation is the process where an image is segmented into regions that are set of homogeneous pixels. The result has a ciritical effect on accuracy of image understanding. In this paper, an Markov random field (MRF) image segmentation is proposed using genetic algorithm(GA). We model an image using MRF which is resistant to noise and blurring. While MRF based methods are robust to degradation, these require accurate parameter estimation. So GA is used as a segmentation algorithm which is effective at dealing with combinatorial problems. The efficiency of the proposed method is shown by experimental results with real images and application to automatic vehicle extraction system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.825-828
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• 2006

The most commonly used techniques for image magnification are interpolation based. However, the magnified images produced by this technique often appear blocking and blurring phenomenon when the image is enlarged. In this paper, we enhanced image magnification algorithm using edge information. The proposed algorithm not used interpolation based but by using sub-band of input image in extrapolation. According to mapping relationship in pyramid, we calculated up-band information to magnify. In experiments, the proposed model shows solved the problem of image loss like the blocking and blurring phenomenon. As the result, it is faster and higher resolution than traditional magnification algorithms.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.207-209
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• 2021

In recent years, with the development of artificial intelligence and IoT technology, automation and unmanned technology are in progress in various fields, and the importance of image processing such as object tracking, medical images and object recognition, which are the basis of this, is increasing. In particular, in systems requiring detailed data processing, noise reduction is used as a pre-processing step, but the existing algorithm has a disadvantage that blurring occurs in the filtering process. Therefore, in this paper, we propose a filter algorithm using modified spatial weights to minimize information loss in the filtering process. The proposed algorithm uses mask matching to remove AWGN, and obtains the output of the filter by adding or subtracting the output of the modified spatial weight. The proposed algorithm has superior noise reduction characteristics compared to the existing method and reconstructs the image while minimizing the blurring phenomenon.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.5
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• pp.9-20
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• 2000

In this paper we compare two frequency domain digital watermarking methods for digital Images, namely DCT(Discrete Cosine Transform) based and DFT(Discrete Fourier Transform) based methods. Unlike DCT coefficients, which always have real values, DFT coefficients normally have complex values Therefore, the DFT coefficients have amplitude and phase components Among them, the phase components are known to carry more Important information for the Images. So, we insert the watermark to the phase of the DFT coefficients only This DFT watermarking method is compared with the conventional DCT based watermarking method for the object-based watermarking problem. Experimental results show that the DFT-phase based method IS more robust to general Image processing attacks including resize, lossy compression(JPEG), blurring and median filtering. On the other hand, the DCT based method is more robust to the malicious attack which inserts different watermarks.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.3
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• pp.249-255
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• 2013

In this paper, we propose an algorithm to detect scale invariant object from IR image obtained in the sea environment. We create horizontal edge (HL), vertical edge (LH), diagonal edge (HH) of images through 2-D discrete Haar wavelet transform (DHWT) technique after noise reduction using morphology operations. Considering the sea environment, Gaussian blurring to the horizontal and vertical edge images at each level of wavelet is performed and then saliency map is generated by multiplying the blurred horizontal and vertical edges and combining into one image. Then we extract object candidate region by performing a binarization to saliency map. A small area in the object candidate region are removed to produce final result. Experiment results show the feasibility of the proposed algorithm.

• Journal of Broadcast Engineering
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• v.9 no.2
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• pp.131-141
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• 2004

Current binocular stereoscopic displays cause visual discomfort when objects with large disparities are present in the scene. One solution for improving visual comfort is synthetic depth-of-field processing, which simulates the characteristics of a human visual system. With this technique, visual comfort is improved by blurring portions of the background and/or foreground in the scene. However, this technique has the drawback of degrading overall image quality because the blurring is typically applied to both left and right images. To alleviate the visual discomfort, we propose a novel disparity-based asymmetrical filtering technique. Proposed technique applies the filtering to the image of one eye only, and controls the blur level according to the disparity information between stereoscopic images. We investigate the effects of this technique on stereoscopic video by measuring visual comfort and apparent sharpness. Our results indicate that disparity-based asymmetrical filtering can improve visual comfort of stereoscopic video while it maintains apparent sharpness if unfixated regions with large disparities are blurred under the appropriate filtering condition.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.4
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• pp.833-838
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• 2003

This paper presents novel methods of recognizing license plates of passing vehicles outdo(n. In particular, the proposed method is much robust for inclined plates caused by the changes of camera placement. To acquire fine images of quickly passing vehicles under a wide range of illumination conditions, we developed a sensing system having superb characteristics. We expanded the dynamic range and eliminated the blurring of images of fast moving vehicles by synthesizing a pair of synchronized images with different intensities. furthermore, to extend the flexibility of the positioning of the TV camera, we propose a recognition algorithm that can be applied to inclined plates. The performance of the integrated system was investigated on real images of vehicles captured under various illumination conditions. The recognition rates of over 99% (conventional plates) and over 97% (highly inclined plates) shows that the developed system is effective for license plate recognition.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.72-83
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• 2011

In this paper, we propose a method to detect and recover the occluded parts of face images using the correlation between pairs of pixels. In a training stage, correlation coefficients between every pairs of pixels are calculated using the occlusion-free face images. Once a new occluded face image is shown, the occluded area is detected and recovered using the correlation coefficients obtained in the training stage. We compare the performance of the proposed method with the conventional method based on PCA. The results show that the proposed method detects and recovers occluded area with much smaller noises than the conventional PCA based method. Moreover, recovered images by the proposed method were more smooth with reduced blurring effect.