• Journal of Digital Convergence
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• v.14 no.2
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• pp.183-190
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• 2016

This paper proposes algorithm to reduce the computing time in a neural network that reduces transmission of data for tracking mobile objects in surveillance networks in terms of detection and communication load. Object Detection can be defined as follows : Given image sequence, which can forom a digitalized image, the goal of object detection is to determine whether or not there is any object in the image, and if present, returns its location, direction, size, and so on. But object in an given image is considerably difficult because location, size, light conditions, obstacle and so on change the overall appearance of objects, thereby making it difficult to detect them rapidly and exactly. Therefore, this paper proposes fast and exact object detection which overcomes some restrictions by using neural network. Proposed system can be object detection irrelevant to obstacle, background and pose rapidly. And neural network calculation time is decreased by reducing input vector size of neural network. Principle Component Analysis can reduce the dimension of data. In the video input in real time from a CCTV was experimented and in case of color segment, the result shows different success rate depending on camera settings. Experimental results show proposed method attains 30% higher recognition performance than the conventional method.

• Progress in Medical Physics
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• v.26 no.1
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• pp.52-58
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• 2015

The automated dental cavity detection program for a new concept intra-oral dental x-ray imaging device, an auxiliary diagnosis system, which is able to assist a dentist to identify dental caries in an early stage and to make an accurate diagnosis, was to be developed. The primary theory of the automatic dental cavity detection program is divided into two algorithms; one is an image segmentation skill to discriminate between a dental cavity and a normal tooth and the other is a computational method to analyze feature of an tooth image and take an advantage of it for detection of dental cavities. In the present study, it is, first, evaluated how accurately the DRLSE (Direct Regularized Level Set Evolution) method extracts demarcation surrounding the dental cavity. In order to evaluate the ability of the developed algorithm to automatically detect dental cavities, 7 tooth phantoms from incisor to molar were fabricated which contained a various form of cavities. Then, dental cavities in the tooth phantom images were analyzed with the developed algorithm. Except for two cavities whose contours were identified partially, the contours of 12 cavities were correctly discriminated by the automated dental caries detection program, which, consequently, proved the practical feasibility of the automatic dental lesion detection algorithm. However, an efficient and enhanced algorithm is required for its application to the actual dental diagnosis since shapes or conditions of the dental caries are different between individuals and complicated. In the future, the automatic dental cavity detection system will be improved adding pattern recognition or machine learning based algorithm which can deal with information of tooth status.

• Journal of the Korean Data and Information Science Society
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• v.7 no.1
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• pp.113-118
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• 1996

Principal component analysis(PCA) is an essential technique for data compression and feature extraction, and has been widely used in statistical data analysis, communication theory, pattern recognition, and image processing. Oja(1992) found that a linear neuron with constrained Hebbian learning rule can extract the principal component by using stochastic gradient ascent method. In practice real data often contain some outliers. These outliers will significantly deteriorate the performances of the PCA algorithms. In order to make PCA robust, Xu & Yuille(1995) applied statistical physics to the problem of robust principal component analysis(RPCA). Devlin et.al(1981) obtained principal components by using techniques such as M-estimation. The propose of this paper is to investigate from the statistical point of view how Xu & Yuille's(1995) RPCA works under the same simulation condition as in Devlin et.al(1981).

• Archives of design research
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• v.18 no.2 s.60
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• pp.133-142
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• 2005

Recently, on-line users prefer image and sense that are deviated from standardization pattern. Also, they need instant and mutual exchangeable communication forms. Developing the various Avatars is required to apply it to various situations. It is due to that the Avatar is used as a card in the on-line communication to represent the user's character visually. The Avatar in the on-line game, such as poker or go-stop which are the most popular nowadays, does not have different character from general community site. Therefore, it dose not satisfy owner who needs sensitive and various character of the Avatar. In this paper, we will be analysis the card game Avatar service, character and desire of the user in existing game petal sites. Also, we'll provide service method which can satisfy the user's requirements. For this, we survey recognition and design preference of users on the card game Avatar.

• Journal of Internet Computing and Services
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• v.6 no.4
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• pp.93-102
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• 2005

In Recent times, Netizens have frequently use virtual character 'Avatar' schemes in order to present their own identity, there is a strong need for avatars to resemble the user. This paper proposes an extraction technique for facial region and features that are used in generating the avatar automatically. For extraction of facial feature component, the method uses ACM and edge information. Also, in the extraction process of facial region, the proposed method reduces the effect of lights and poor image quality on low resolution pictures. this is achieved by using the variation of facial area size which is employed for external energy of ACM. Our experiments show that the success rate of extracting facial regions is $92{\%}$ and accuracy rate of extracting facial feature components is $83.4{\%}$, our results provide good evidence that the suggested method can extract the facial regions and features accurately, moreover this technique can be used in the process of handling features according to the pattern parts of automatic avatar generation system in the near future.

• Journal of Korea Multimedia Society
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• v.17 no.3
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• pp.364-372
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• 2014

This research enables the user to have access to the desired service which is on the multi-platform display device by establishment customized Digital Signage System using the SaaS method. This system is significantly favorable due to the following points: the expandibility and portability is outstanding compared with the existing signage system, establishment expenses may be reduced because the platform can be established in various configurations independently, maintenance and management, and the strong point of the system is that costs can be reduced due to the fact that the electric power can be controlled according to environmental situations. Various researches should be conducted simultaneously such as researches on automatic pattern recognition technologies which recognizes the sex, age, location among other data of the user and various methods of image processing for the production of contents to elaborate lively contents to provide diverse experience and enjoyable configurations for the future generation.

• Journal of Digital Convergence
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• v.16 no.3
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• pp.303-309
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• 2018

Computer vision technology is a component inspection to obtain a video image from the camera to the machine to perform the capabilities of the human eye with a field of artificial intelligence, and then analyzed by the algorithm to determine to determine the good and bad of production parts It is widely applied. Shape inspection method was used as how to identify the location of the start point and the end point of the search range, measure the height to the line scan method, in such a manner as to determine the presence or absence of the bolt tabs average brightness of the inspection area in a circular scan type value And the degree of similarity was calculated. The total time it takes to test in the test performance tests of two types of bolts tab enables test 300 min, and demonstrated the accuracy and efficiency of the inspection on the production line represented a complete inspection accuracy.

• The KIPS Transactions:PartB
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• v.13B no.5 s.108
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• pp.541-546
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• 2006

Data Mining is the process of finding hidden patterns inside a large data set. Cluster analysis has been used as a popular technique for data mining. It is a fundamental process of data analysis and it has been Playing an important role in solving many problems in pattern recognition and image processing. If fuzzy cluster analysis is to make a significant contribution to engineering applications, much more attention must be paid to fundamental decision on the number of clusters in data. It is related to cluster validity problem which is how well it has identified the structure that Is present in the data. In this paper, we design an adaptive data mining model using fuzzy performance measures. It discovers clusters through an unsupervised neural network model based on a fuzzy objective function and evaluates clustering results by a fuzzy performance measure. We also present the experimental results on newsgroup data. They show that the proposed model can be used as a document classifier.

• Journal of the Korea Convergence Society
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• v.9 no.7
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• pp.1-7
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• 2018

Feature selection, one of data preprocessing techniques, is one of major research areas in many applications dealing with large dataset. It has been used in pattern recognition, machine learning and data mining, and is now widely applied in a variety of fields such as text classification, image retrieval, intrusion detection and genome analysis. The proposed method is based on a genetic algorithm which is one of meta-heuristic algorithms. There are two methods of finding feature subsets: a filter method and a wrapper method. In this study, we use a wrapper method, which evaluates feature subsets using a real classifier, to find an optimal feature subset. The training dataset used in the experiment has a severe class imbalance and it is difficult to improve classification performance for rare classes. After preprocessing the training dataset with SMOTE, we select features and evaluate them with various machine learning algorithms.

• Journal of Periodontal and Implant Science
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• v.47 no.3
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• pp.174-181
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• 2017

Purpose: Epitope spreading is a phenomenon in which distinct subdominant epitopes become major targets of the immune response. Heat shock protein (HSP) 60 from Porphyromonas gingivalis (PgHSP60) and peptide 19 from PgHSP60 (Pep19) are immunodominant epitopes in autoimmune disease patients, including those with periodontitis. It remains unclear whether Pep19 is a dominant epitope in subjects without periodontitis or autoimmune disease. The purpose of this study was to determine the epitope spreading pattern and verify Pep19 as an immunodominant epitope in healthy teenagers using dot immunoblot analysis. The patterns of epitope spreading in age-matched patients with type 1 diabetes mellitus (type 1 DM) and healthy 20- to 29-year old subjects were compared with those of healthy teenagers. Methods: Peptide from PgHSP60, Mycobacterium tuberculosis HSP60 (MtHSP60), and Chlamydia pneumoniae HSP60 (CpHSP60) was synthesized for comparative recognition by sera from healthy subjects and patients with autoimmune disease (type 1 DM). Dot immunoblot analysis against a panel of peptides of PgHSP60 and human HSP60 (HuHSP60) was performed to identify epitope spreading, and a densitometric image analysis was conducted. Results: Of the peptide from PgHSP60, MtHSP60, and CpHSP60, PgHSP60 was the predominant epitope and was most consistently recognized by the serum samples of healthy teenagers. Most sera from healthy subjects and patients with type 1 DM reacted more strongly with PgHSP60 and Pep19 than the other peptides. The relative intensity of antibody reactivity to Pep19 was higher in the type 1 DM group than in the healthy groups. Conclusions: Pep19 is an immunodominant epitope, not only in autoimmune disease patients, but also in healthy young subjects, as evidenced by their robust immunoreactivity. This result suggests that the Pep19-specific immune response may be an initiator that triggers autoimmune diseases.