• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.1
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• pp.44-52
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• 2010

In this paper, we propose a novel method for face recognition which uses polar coordinate instead of conventional cartesian coordinate. Among the central area of a face, we select a point as a pole and make a polar image of a face by evenly sampling pixels in each direction of 360 degrees around the pole. By applying conventional feature extraction methods to the polar image, the recognition rates are improved. The polar coordinate delineates near-pole area more vividly than the area far from the pole. In a face, important regions such as eyes, nose and mouth are concentrated on the central part of a face. Therefore, the polar coordinate of a face image can achieve more vivid representation of important facial regions compared to the conventional cartesian coordinate. The proposed polar coordinate transform was applied to Yale and FRGC databases and LDA and NLDA were used to extract features afterwards. The experimental results show that the proposed method performs better than the conventional cartesian images.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.9 no.2
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• pp.81-91
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• 1991

This thesis aims to improve the analysis accuracy of remotely sensed digital imagery, and the improvement is achieved by considering the weight factors(a priori probabilities) of Bayesian MLC in the classification stage. To be concrete, Bayesian decision theory is studied from remote sensing field of view, and the equations in the n-dimensional form are derived from normal probability density functions. The amount of the misclassified pixels is extracted from probability function data using the thres-holding, and this is a basis of evaluating the classification accuracy. The results indicate that 5.21% of accuracy improvement was carried out. The data used in this study is LANDSAT TM(1985.10.21 ; 116-34), and the study area is within the administrative boundary of Seoul.

• Journal of Broadcast Engineering
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• v.12 no.3
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• pp.278-288
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• 2007

We propose the fast full search algorithm that reduces the computational load of the block matching algorithm which is used for a motion estimation in the video coding. Since the conventional spiral search method starts searching at the center of the search window and then moves search point to estimate the motion vector pixel by pixel, it is good for the slow motion picture. However we proposed the efficient motion estimation method which is good for the fast and slow motion picture. Firstly, when finding the initial threshold value, we use the expanded predictor that can approximately calculate minimum threshold value. The proposed algorithm estimates the motion in the new search order after partitioning the search window and adapt the directional search order in the re-divided search window. At the result, we can check that the proposed algorithm reduces the computational load 94% in average compared to the conventional spiral full search algorithm without any loss of image quality.

• Journal of the Korea Society of Computer and Information
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• v.13 no.3
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• pp.179-187
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• 2008

In this paper, we apply a set of algorithms to classily normal and cancer nucleus from uterine cervical pap-smear images. First, we use lightening compensation algorithm to restore color images that have defamation through the process of obtaining $1{\times}400$ microscope magnification. Then, we remove the background from images with the histogram distributions of RGB regions. We extract nucleus areas from candidates by applying histogram brightness, Kapur method, and our own 8-direction contour tracing algorithm. Various binarization, cumulative entropy, masking algorithms are used in that process. Then, we are able to recognize normal and cancer nucleus from those areas by using three morphological features - directional information, the size of nucleus, and area ratio - with fuzzy membership functions and deciding rules we devised. The experimental result shows our method has low false recognition rate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.9
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• pp.1689-1696
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• 2017

In the process of obtaining and transmitting image, there is degradation of image due to various noise, and there have been many active studies ongoing to remove the noise added on the images. This thesis has proposed a switching filter processing by the types of noise in order to remove the complex noise added on images. When the center value of local mask is damaged by AWGN based on the noise judgment, the threshold value is applied on standard deviation of local mask to process by applying different weight of weighted mask, and if the image is damaged by the salt and pepper noise, the local mask is subdivided into 4 directions, and processed by applying cubic spine interpolation in the direction with the least slat and pepper noise. Also, in order to evaluate the performance of proposed filter algorithm, the study conducted comparison among the existing methods and proposed filter using PSNR.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.1C
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• pp.9-15
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• 2007

We propose the fast full search algorithm that reduces the computation of the block matching algorithm which is used for motion estimation of the video coding. Since the conventional spiral search method starts searching at the center of the search window and then moves search point to estimate the motion vector pixel by pixel, it is good for the slow motion pictures. However the proposed method is good for the fast and slow motion because it estimates the motion in the new search order after partitioning the search window. Also, when finding the motion vector, this paper presents the method that reduces the complexity by computing the matching error in the order which is determined by local image complexity. The proposed algorithm reduces the computation up to 99% for block matching error compared with the conventional spiral full search algorithm without any loss of image quality.

• The KIPS Transactions:PartB
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• v.18B no.3
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• pp.139-146
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• 2011

The color correction is the important process of influencing on the picture quality of the 3D stereoscopic images. Existing colorcorrecting methods handle the processing intensifying a correspondence among a left and right image using a histogram based on any one side. In case of color correction based on a histogram, it is difficult to correct tone of image, because the color temperature is not converted enough. And in this paper, the color temperature correction and color consistency correction is proposed without using histogram. The proposed color correction method by color temperature gives 3 in CIE-${\Delta}E$ for each pixel on the images captured with same illuminants and the conventional gives similar results. For color consistency, the proposed gives 9 in CIE-${\Delta}E$ on the images captured with different illuminants while the conventional gives 18. The proposed method shows better results than the conventional in color consistency processing.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.2
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• pp.475-481
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• 2014

As the society develops to advanced digital information times, many studies are underway about digital video processing technology areas such as image restoration. There are typical methods to restore the image which have been damaged by the impulse noise like SM(standard median) filter and CWM(center weighted median) filter. These filters show excellent noise reduction capabilities in low noise density areas, but in high noise density areas, noise reduction capabilities are not sufficient. In this paper, in order to restore the degraded images in impulse(Salt & Pepper) noise environment, the image restoration filter algorithm was suggested which expands and subdivide the mask focusing on damaged pixels. And to demonstrate the superiority of the proposed algorithm used PSNR (peak signal to noise ratio) as the standard of judgement.

• Journal of KIISE:Software and Applications
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• v.31 no.2
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• pp.213-223
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• 2004

In this paper, we propose a new face detection method for real-time applications. It is based on the template-matching and appearance-based method. At first, we apply Min-max normalization with histogram equalization to the input image according to the variation of intensity. By applying the PCA transform to both the input image and template, PC components are obtained and they are applied to the LDA transform. Then, we estimate the distances between the input image and template, and we select one region which has the smallest distance. SVM is used for final decision whether the candidate face region is a real face or not. Since we detect a face region not the full region but within the $\pm$12 search window, our method shows a good speed and detection rate. Through the experiments with 6 category input videos, our algorithm shows the better performance than the existing methods that use only the PCA transform. and the PCA and LDA transform.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.1
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• pp.1-7
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• 2022

It has been found through physiological experiments that the visual neurons constituting the human visual cortex do not respond to all visual stimuli, but to a visual stimuli with specific conditions. In order to interpret such physiological experiments, a model that can simulate the firing characteristics of neurons including a linear filter with random gain was proposed. It has been proven through experiments that subspaces are formed. To verify the validity of the implemented model, the distribution of values for two pixels randomly extracted from four different visual stimulus data was observed. The difference between the two distributions was confirmed by extracting the central coordinate value, that is, the coordinate value with the most values, from the distribution of the total stimulus data and the spike ignition stimulus data. In the case of the entire set, it was verified through experiments that the stimulus data generating spikes is a subset or subspace of the entire stimulus data. This study can be used as a basic study related to the mechanism of spikes in response to visual stimuli.