• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.8
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• pp.1907-1917
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• 2010

It is much needed research for ocean scientists to implement a digitizing system that effectively extracts and digitializes sea level records accumulated from the past. The main difficulty of such a system is huge anount of data to be processed. In this paper, we implement a digitizing system to handle such mass-data of sea level records. This system consists of a pre-process step, a digitizing step and a post-process step. In pre-process step, the system adjusts skewnesses of scanned images and normalizes the size of images automatically. Then, it extracts a graph area from images and thins the graph area in digitizing step. Finally, in the post-process step, the system tests the reliability. It is cost-effective and labour-reducing software for scientists not wasting their time to such boring manual digitizing jobs.

• The Journal of the Convergence on Culture Technology
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• v.4 no.4
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• pp.361-366
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• 2018

For each character constituting learning data, different fonts are added in pixel unit to create MASK, and then pixel values belonging to the MASK are divided into three groups. The experimental data are modified into skeletal forms, and then regional boundary operation is used to create a boundary that distinguishes the background region adjacent to the skeleton of the character from the background of the modified experimental data. Discordance values between the modified experimental data and the MASKs are calculated, and then the MASK with the minimum value is found. This MASK is selected as a finally recognized result for the given experiment data. The recognition algorithm using skeleton of the character and the regional boundary operation can easily extend the learning data set by adding new fonts to the given learning data, and also it is simple to implement, and high character recognition rate can be obtained.

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.375-382
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• 2002

Handwritten character recognition is classified into on-line handwritten character recognition and off-line handwritten character recognition. On-line handwritten character recognition has made a remarkable outcome compared to off-line hacdwritten character recognition. This method can acquire the dynamic written information such as the writing order and the position of a stroke by means of pen-based electronic input device such as a tablet board. On the contrary, Any dynamic information can not be acquired in off-line handwritten character recognition since there are extreme overlapping between consonants and vowels, and heavily noisy images between strokes, which change the recognition performance with the result of the preprocessing. This paper proposes a method that effectively extracts the stroke including dynamic information of characters for off-line Korean handwritten character recognition. First of all, this method makes improvement and binarization of input handwritten character image as preprocessing procedure using watershed algorithm. The next procedure is extraction of skeleton by using the transformed Lu and Wang's thinning: algorithm, and segment pixel array is extracted by abstracting the feature point of the characters. Then, the vectorization is executed with a maximum permission error method. In the case that a few strokes are bound in a segment, a segment pixel array is divided with two or more segment vectors. In order to reconstruct the extracted segment vector with a complete stroke, the directional component of the vector is mortified by using right-hand writing coordinate system. With combination of segment vectors which are adjacent and can be combined, the reconstruction of complete stroke is made out which is suitable for character recognition. As experimentation, it is verified that the proposed method is suitable for handwritten Korean character recognition.

• Journal of Korea Multimedia Society
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• v.21 no.2
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• pp.147-157
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• 2018

Alzheimer's disease has the significant factors for the both specific and characteristic features according to the disease progressing that are the volumetry and surface area by the brain hippocampus shrinking and thinning. However, we have suggested a shape analysis to calculate the variance by the roughness, coarseness or uneven surface on 3D MR images. For the reasons we have presented two methods: the first method is the distance calculation from major axis to edge points and the second method is the distance calculation from centroidal point to edge points on a coronal plane. Then we selected the shortest distance and the longest distance in each slice and analyzed the ANOVA and average distances. Consequently we obtained the available and great results by the longest distance of the axial and centroidal point. The results of average distances were 44.85(AD), 45.04(MCI) and 49.31(NC) from the axial points and 39.30(AD), 39.58(MCI) and 44.78(NC) from centroidal points respectively. Finally the distance variations for the easily recognized visualization were shown by the color mapping. This research could be provided an indicator of biomarkers that make diagnosis and prognosis the Alzheimer's diseases in the future.

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.369-374
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• 2002

In this paper, we propose the react-time car license plate recognition algorithm using intensity variation and geometric pattern vector. Generally, difference of car license plate region between character and background is more noticeable than other regions. And also, car license plate region usually shows high density values as well as constant intensity variations. Based on these characteristics, we first extract car license plate region using intensity variations. Secondly, lightness compensation process is performed on the considerably dark and brightness input images to acquire constant extraction efficiency. In the proposed recognition step, we first pre-process noise reduction and thinning steps. And also, we use geometric pattern vector to extract features which independent on the size, translation, and rotation of input values. In the experimental results, the proposed method shows better computation times than conventional circular pattern vector and better extraction results regardless of irregular environment lighting conditions as well as noise, size, and location of plate.

• Journal of the Korean Society of Fashion and Beauty
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• v.1 no.1 s.1
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• pp.105-118
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• 2003

The purpose of this study was to analyze entertainer Byeon Jeong-su's hair styles and thereby, apply the results to models. For the applications, models' hair styles were bisected into two sections, and thereby, the edges of the outsides were cut into solid points, and thereupon, into diverse bases by using vertical section, Perpendicular direction and square angles. On the other hand, the insides were cut in the same way of the outside bases by using radial section, varied combing and $45{\sim}90$ degree head angles. In addition, tops and sides were arranged in their corners, while a graduation technique was used to express a natural difference of levels. The fringes were cut by using free-hand and slicing techniques. furthermore, the quantity and mass of the hairs were treated with such techniques as thinning, swing, effect, rolling, slide and slicing, while a bridge product was used for coloring together with a highlight technique. The hair styles were rendered for straight and wave by using an magic iron machine. It was confirmed through this study that the same cutting techniques would result in different images depending on individuals' physical shapes, facial shapes, head skeletons and types of hairs. Thus, it is required of the hair designers to suggest their own custom hair designs adequate to individuals' images through continued image-wise hair design practices.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.4
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• pp.249-256
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• 2015

Shadow is a common physical phenomenon in natural images and may cause problems in computer vision tasks. Therefore, shadow removal is an essential preprocessing process for effective moving object tracking in video image. In this paper, we proposed the method of shadow removal algorithm using chromaticity, brightness distortion and direction of shadow candidate. The proposed method consists of two steps. First, removal process of primary shadow candidate region by using chromaticity, brightness and distortion. The second stage applies the final shadow candidate region to obtain a direction feature of shadow which is estimated by the thinning algorithm after calculating the lowest pixel position of the moving object. To verify the proposed approach, some experiments are conducted to draw a compare between conventional method and that of proposed. Experimental results showed that proposed methodology is simple, but robust and well adaptive to be need to remove a shadow removal operation.

• Honam Mathematical Journal
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• v.36 no.3
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• pp.695-706
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• 2014

Various properties of digital covering spaces have been substantially used in studying digital homotopic properties of digital images. In particular, these are so related to the study of a digital fundamental group, a classification of digital images, an automorphism group of a digital covering space and so forth. The goal of the present paper, as a survey article, to speak out utility of digital covering theory. Besides, the present paper recalls that the papers [1, 4, 30] took their own approaches into the study of a digital fundamental group. For instance, they consider the digital fundamental group of the special digital image (X, 4), where X := $SC^{2,8}_4$ which is a simple closed 4-curve with eight elements in $Z^2$, as a group which is isomorphic to an infinite cyclic group such as (Z, +). In spite of this approach, they could not propose any digital topological tools to get the result. Namely, the papers [4, 30] consider a simple closed 4 or 8-curve to be a kind of simple closed curve from the viewpoint of a Hausdorff topological structure, i.e. a continuous analogue induced by an algebraic topological approach. However, in digital topology we need to develop a digital topological tool to calculate a digital fundamental group of a given digital space. Finally, the paper [9] firstly developed the notion of a digital covering space and further, the advanced and simplified version was proposed in [21]. Thus the present paper refers the history and the process of calculating a digital fundamental group by using various tools and some utilities of digital covering spaces. Furthermore, we deal with some parts of the preprint [11] which were not published in a journal (see Theorems 4.3 and 4.4). Finally, the paper suggests an efficient process of the calculation of digital fundamental groups of digital images.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.901-905
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• 2005

Monte Carlo localization is known to be one of the most reliable methods for pose estimation of a mobile robot. Much research has been done to improve performance of MCL so far. Although MCL is capable of estimating the robot pose even for a completely unknown initial pose in the known environment, it takes considerable time to give an initial estimate because the number of random samples is usually very large especially for a large-scale environment. For practical implementation of the MCL, therefore, a reduction in sample size is desirable. This paper presents a novel approach to reducing the number of samples used in the particle filter for efficient implementation of MCL. To this end, the topological information generated off- line using a thinning method, which is commonly used in image processing, is employed. The topological map is first created from the given grid map for the environment. The robot scans the local environment using a laser rangefinder and generates a local topological map. The robot then navigates only on this local topological edge, which is likely to be the same as the one obtained off- line from the given grid map. Random samples are drawn near the off-line topological edge instead of being taken with uniform distribution, since the robot traverses along the edge. In this way, the sample size required for MCL can be drastically reduced, thus leading to reduced initial operation time. Experimental results using the proposed method show that the number of samples can be reduced considerably, and the time required for robot pose estimation can also be substantially decreased.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.10
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• pp.2317-2328
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• 1997

The objective of this paper is to develop an algorithm for a real-time automatic fingerprint recognition system. The algorithm employs the wavelet transform(WT) and the dominat local orientation that derived from the gradient Gaussian(GoG) and coherence in determining the directions of ridges in fingerprint images. By using the WT, the algorithm does not require conventional preprocessing procedures such as smothing, binarization, thining and restoration. For recognition, two fingerprint images are compared in three different ST domains;one that represents the original image compressed to quarter(LL), another that shows vertical directional characteristic(LH), and third as the block that contains horizontal direction(HL) in WT domain. Each block has dominat local orientation that derived from the GoG and coherence. The proposed algorithm is imprlemented on a SunSparc-2 workstation under X-window environment. Our simulation results, in real-time have shown that while the rate of Type II error-Incorrect recognition of two identical fingerprints as the identical fingerprints-is held at 0%, the rate of Type I error-Incorrect recognitionof two identical fingerprints as the different ones-is 2.5%.