• KIPS Transactions on Software and Data Engineering
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• v.4 no.10
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• pp.447-454
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• 2015

This paper proposes geographical name denoising by machine learning of event detection based on twitter. Recently, the increasing number of smart phone users are leading the growing user of SNS. Especially, the functions of short message (less than 140 words) and follow service make twitter has the power of conveying and diffusing the information more quickly. These characteristics and mobile optimised feature make twitter has fast information conveying speed, which can play a role of conveying disasters or events. Related research used the individuals of twitter user as the sensor of event detection to detect events that occur in reality. This research employed geographical name as the keyword by using the characteristic that an event occurs in a specific place. However, it ignored the denoising of relationship between geographical name and homograph, it became an important factor to lower the accuracy of event detection. In this paper, we used removing and forecasting, these two method to applied denoising technique. First after processing the filtering step by using noise related database building, we have determined the existence of geographical name by using the Naive Bayesian classification. Finally by using the experimental data, we earned the probability value of machine learning. On the basis of forecast technique which is proposed in this paper, the reliability of the need for denoising technique has turned out to be 89.6%.

• Journal of the Korea Computer Graphics Society
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• v.24 no.3
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• pp.21-31
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• 2018

We introduces a system that enables fast and effective visualization of natural disaster data such as typhoons, tsunamis, floods, and flooding to help make informed decisions in disaster situations. Data containing disaster information consists of a few hundred megabytes to many tens and hundreds of gigabytes, which can not be handled by a PC. This system was implemented in the form of a client-server based service to generate and output results from high-performance servers. The server in a built-in, high-performance cluster handles client requests and sends the result of visualization to the client. Clients can receive the results in any form of images, videos, or 3D graphic model by specifying a desired time frame, effectively viewing the results with a user-friendly GUI.

• Journal of Korea Multimedia Society
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• v.11 no.3
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• pp.404-413
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• 2008

As toward a ubiquitous society, a lot of methods have been proposed to protect personal privacy. Smart Cards with CPU and Memory are widely being used to implement the methods. The use of Java Card is also gradually getting expanded into more various applications. Because there is no standards in Java Card File System, Generally, Java Card File System follows the standards of Smart Card File System. However, one of disadvantages of the Java Card File System using a standard of Smart Card File System is that inefficient memory use and increasing processing time are caused by redundancy of data and program codes. In this paper, a File Cache method and a Direct Access method are proposed to solve the problems. The proposed methods are providing efficient memory use and reduced processing time by reduce a program codes.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.2
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• pp.73-80
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• 2006

Fingerprint-based verification system has been used for a very long time. Because of their well-known uniqueness and immutability, fingerprint is one of the most widely used biometric features. However, fingerprint identification system has such a critical weakness that the performance of verification is reduced drastically for a poor input fingerprint. In this paper, an image enhancement algorithm using enhanced direction and enhanced binary and aiming image is used to mitigate the problem in the preprocessing. The goal of image enhancement is to estimate the quality of input fingerprint image and to improve the clarity of ridge and valley structures of input fingerprint image. Also, a ridge orientation extraction method using index table is proposed to improve the speed of verification. It is shown by the experiments that proposed fingerprint verification system improves the minutiae extraction accuracy and performance of verification.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.3
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• pp.138-144
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• 2019

In a modern society, people are concerned seriously about their travel destinations depending on time, economic problem. In this paper, we propose an non-hierarchical clustering based hybrid recommendation using context knowledge. The proposed method is personalized way of recommended knowledge about preferred travel places according to the user's location, place, and weather. Based on 14 attributes from the data collected through the survey, users with similar characteristics are grouped using a non-hierarchical clustering based hybrid recommendation. This makes more accurate recommendation by weighting implicit and explicit data. The users can be recommended a preferred travel destination without spending unnecessary time. The performance evaluation uses accuracy, recall, F-measure. The evaluation result was shown 0.636 accuracy, 0.723 recall, and 0.676 F-measure.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.339-345
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• 2016

In general, mosaic blocks are used to hide some specified areas, such as human faces and disgusting objects, in an input image when images are uploaded on a web-site or blog. This paper proposes a new algorithm for robustly detecting grid mosaic areas in an image based on the edge projection. The proposed algorithm first extracts the Canny edges from an input image. The algorithm then detects the candidate mosaic blocks based on horizontal and vertical edge projection. Subsequently, the algorithm obtains real mosaic areas from the candidate areas by eliminating the non-mosaic candidate regions through geometric features, such as size and compactness. The experimental results showed that the suggested algorithm detects mosaic areas in images more accurately than other existing methods. The suggested mosaic detection approach is expected to be utilized usefully in a variety of multimedia-related real application areas.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.251-256
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• 2021

Unlike general cameras, a high-speed camera capable of capturing a large number of frames per second can enable the advancement of some image processing technologies that have been limited so far. This paper proposes a method of removing undesirable noise from an high-speed input color image, and then detecting a human face from the noise-free image. In this paper, noise pixels included in the ultrafast input image are first removed by applying a bidirectional filter. Then, using RetinaFace, a region representing the person's personal information is robustly detected from the image where noise was removed. The experimental results show that the described algorithm removes noise from the input image and then robustly detects a human face using the generated model. The model-based face-detection method presented in this paper is expected to be used as basic technology for many practical application fields related to image processing and pattern recognition, such as indoor and outdoor building monitoring, door opening and closing management, and mobile biometric authentication.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.143-174
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• 2023

With the development of deep learning technologies, Artificial Intelligence powered Optical Character Recognition (AI-OCR) has evolved to read multiple languages from various forms of images accurately. For the financial industry, where a large number of diverse documents are processed through manpower, the potential for using AI-OCR is great. In this study, we present a configuration and a design of an AI-OCR modality for use in the financial industry and discuss the platform construction with application cases. Since the use of financial domain data is prohibited under the Personal Information Protection Act, we developed a deep learning-based data generation approach and used it to train the AI-OCR models. The AI-OCR models are trained for image preprocessing, text recognition, and language processing and are configured as a microservice architected platform to process a broad variety of documents. We have demonstrated the AI-OCR platform by applying it to financial domain tasks of document sorting, document verification, and typing assistance The demonstrations confirm the increasing work efficiency and conveniences.

• Journal of Internet Computing and Services
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• v.17 no.3
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• pp.87-93
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• 2016

In the current information-based society, information and communication technology(ICT) is very important for an individual, a society, and a nation. Especially, for a nation, ICT-related industries are forming an important part of a nation's economy. Also, unlike other industries, ICT-related industries do not require various infrastructures, and have an advantage of being developed with a few talented persons in a short period of time. In this sense, identification and education of gifted children in IT become an essential task of a nation's future. In the past, selection of the gifted children was based on paper tests. However, paper tests incurred various side effects such as private education. Since 2013, observation-recommendation system instead of paper tests has been fully adopted. The purpose of this paper is to analyze the validity of observation-recommendation admission system of the gifted children in IT. For this research purpose, the gifted children in gifted science education center attached in a university at Seoul become the focus of the samples. Their entrance score ranking and graduation record raking are compared for analysis of validity of admission system. After statistical analysis, there is a meaningful correlation between entrance score ranking and graduation record ranking for the gifted children in IT. It means that the higher entrance score ranking, the higher graduation record ranking. The analysis results are expected to be valuable baseline data for deciding usefulness of observation-recommendation admission system.

• Journal of the Korea Society of Computer and Information
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• v.19 no.4
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• pp.111-122
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• 2014

Legislation are social norms that give directly or indirectly, huge impact on the social or corporate, personal problems, unlike a normal document. Also, over time it has a feature constantly changing by the laws enactment and amendment, repealed. The amendment statement automatic generated system is used for purpose of proclamation to those. However, existing system is able to generate amendment statement just text body of law how compare and analyze the current legislation and amendment legislation. However, actual legislation to be created attached table of the table form in complex structure besides simple text form as body text. In this paper, we additional implement attached table processing to existing the amendment statement automatic generated system that containing the table does not handle attached table. We were analyse to the amendment statement generated grammar and table structure in attached table of the legislation for processing to attached table. Also proposed a method to compare attached table in the table. So, it is enable the automatic generation with amendment statement which various forms of legislation the documents.