• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.1
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• pp.95-101
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• 2017

In natural images, there is generally locality, and the values of adjacent pixels are similar. It is possible to estimate the curved surface characteristics of the original image using adjacent pixels having similar pixel values. In this paper, after precisely estimating the characteristics of the curved surface existing in the image, interpolation values are obtained so as to faithfully reflect the estimated characteristics of the curved surface, We propose an effective image enlarging method that generates an enlarged image using the obtained interpolation values. The image enlarged by the proposed method maintains the curved surface characteristics of the original image, and thus the image quality of the enlarged image is improved. Experimental results show that the image quality of the proposed method is superior to that of the conventional techniques.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.3 s.357
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• pp.65-71
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• 2007

We propose a pixel-level automatic calibration circuit scheme that initializes a capacitive fingerprint sensor LSI to eliminate the influence of the surface condition and environment, which is degraded by dirt during long-time use, process variation and ambient temperature. The sample chip is fabricated on $0.35{\mu}m$ standard CMOS process. The calibration is executed by optimizing the reference voltage in each pixel to make the sensor signals of all pixels the same. The calibration control circuit is composed of the sensing circuit and charge pumping circuit, and calibrates all pixels in a short time. 16-level gray scale fingerprint images can be captured to increase the accuracy of identification. This confirms that the scheme is effective for capturing consistent clear images during long-time use.

• Journal of the Optical Society of Korea
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• v.12 no.3
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• pp.126-130
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• 2008

We propose and experimentally demonstrate an effective method to reduce near-field speckle noise at the output of a 50 ${\mu}m$ graded index multimode fiber using a short cylindrical piezoelectric transducer(PZT) vibrating in the radial direction. The fiber was coiled as tightly as possible around the mandrel of the PZT and a periodic stretching effect was caused by the radial oscillations of the actuator. The output of the optical fiber using the He-Ne laser source was intensively observed by a CCD camera. By counting all the pixels corresponding to relative intensity graded into 256 levels in the selected area and by calculating standard deviation and mean value of the intensity, we could measure the speckle contrast and vibration effect quantitatively with reduction ratio of pixels and line profile of the illuminated region. It was clearly observed that the characteristics of the speckle pattern in the vibration-on state were significantly improved over that of the vibration-off state due to time-averaged smoothing.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06c
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• pp.447-451
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• 2010

In this paper, we propose a simple but effective algorithm to increase the speed of Emphysema region classification. Emphysema region classification method based on CT image consumes a lot of time because of the large number of subregions due to the large size of CT image. Some of the sub-regions contain no Emphysema and the classification of these regions is worthless. To speed up the classification process, we create an algorithm to select Emphysema region candidates and only use these candidates in the Emphysema region classification instead of all of the sub-regions. First, the lung region is detected. Then we threshold the lung region and only select the dark pixels because Emphysema only appeared in the dark area of the CT image. Then the thresholded pixels are clustered into a region that called the Emphysema pre-detected region or Emphysema region candidate. This region is then divided into sub-region for the Emphysema region classification. The experimental result shows that Emphysema region classification using predetected Emphysema region decreases the size of lung region which will result in about 84.51% of time reduction in Emphysema region classification.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.4
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• pp.548-553
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• 2010

This paper presents an effective shape image recognition method using the correlation based on 4-dimensional histogram. The histogram-based correlation is accurately applied to express the similarity by comparing the positions of a corresponding dimension between the images, which is calculated by considering 4 directions of the shape image. The correlation measure by using the normalized cross-correlation is also applied to obtain the robust recognition to the geometrical variations such as shape, position, size, and rotation. The proposed method has been applied to the problem for recognizing the 8 shape images of 64*64 pixels and the 30 shape images of 256*256 pixels. The experimental results show that the proposed method has a superior recognition performance that appears the image characters well.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.217-219
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• 2019

In response to the increased use of digital video device, more researches are actively made on the image processing technologies. Image processing is practically used on various applied fields such as medical photographic interpretation, and object recognition. The types of image noise include Gaussian Noise, Impulse Noise, and Salt and Pepper. Noise refers to the unnecessary information which damages the video and the noise is mainly removed by a filter. Typical noise removal methods are Median Filter and Average Filter. While Median Filter is effective for removing Salt and Pepper noise, the noise removal performance is relatively lower in the environment with high noise density. To address such issue, this study suggested an algorithm which utilizes neighboring pixels to remove noise.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.35-38
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• 2009

The paper presents an effective method to detect fire in video surveillance and monitoring system. The main contribution of this work is that we successfully use the Hidden Markov Models in the process of detecting the fire with a few preprocessing steps. First, the moving pixels detected from image difference, the color values obtained from the fire flames, and their pixels clustering are applied to obtain the image regions labeled as fire candidates; secondly, utilizing massive training data, including fire videos and non-fire videos, creates the Hidden Markov Models of fire and non-fire, which are used to make the final decision that whether the frame of the real-time video has fire or not in both temporal and spatial analysis. Experimental results demonstrate that it is not only robust but also has a very low false alarm rate, furthermore, on the ground that the HMM training which takes up the most time of our whole procedure is off-line calculated, the real-time detection and alarm can be well implemented when compared with the other existing methods.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.9
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• pp.13-18
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• 2015

The mutilevel holographic data storage offers considerable advantage for capacity, since it can store more than one bit per pixel. In this paper, we search the number of codewords for each code depending on three conditions: (1) the number of levels, (2) the number of pixels in a codeword, and (3) the minimum Euclidean distance of a code. Increasing the number of levels per pixel creates more capacity, while causing more errors, by reducing the noise margin. Increasing the number of pixels in a codeword can increase the code rate, which means more capacity, but increases the complexity of the encoder/decoder of the code. Increasing the minimum distance of a code reduces the detection error, while reducing the code rate of the code. In such a fashion, a system design will always have pros and cons, but our task is to find out an effective one under the given conditions for the system requirements. Therefore, the numbers we searched can provide some guidelines for effective code design.

• Journal of computational fluids engineering
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• v.22 no.1
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• pp.37-42
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• 2017

Infrared signals are frequently used to detect objects exposed to wide variety of environmental conditions. Detection by infrared signature is accomplished by distinguishing objects by using the IR radiant contrast between objects and the background. There are several methods of estimating the IR radiant contrast. The inverse distance weighting method, which is one of the IR radiant contrast estimation method using the effect of distance from objects, is known to be an effective way to analyze radiant contrast for complex backgrounds. However this method has a disadvantage of requiring a long calculation time. In this study we propose a statistical method of estimating the IR radiant contrast by using randomly selected pixels of arbitrary number among background pixels to reduce calculation time. Some measured IR images in MWIR and LWIR regions are used to test the applicability of the method proposed and we found that the proposed method is very effective in determining the IR radiant contrast showing very rapid estimation with minar accuracy loss.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.110-116
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• 2017

This paper presents an effective demosaicking algorithm for color filter array (CFA) images acquired from single-sensor devices based on directional interpolation and nonlocal properties of the image. We interpolate the G channel considering diagonal directions as well as horizontal and vertical directions, using a small number of pixels to reflect local properties of the image. Then, we overcome image degradations, such as zipper effects near edges and false colors, by applying nonlocal means (NLM) filtering to the interpolated pixels. R and B channels are reproduced by using directional interpolation with information of the reconstructed G channel and NLM filtering. Experimental results for various McMaster images with high saturation and color changes show that the proposed algorithm accomplishes high PSNR compared with conventional methods. Moreover, the proposed method demonstrates better subjective quality compared with existing methods in terms of reduction of quality degradation, like false colors, and preservation of the image structures, such as edges and textures.