• Journal of the Korea Society of Computer and Information
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• v.6 no.1
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• pp.31-37
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• 2001

Human psychovisual phenomena involved in extracting features is more sensitive in dark regions than in bright regions Therefore, feature extracting operators should be considered local intensities in order to perceive objects analogous to human vision system. Generally, conventional feature extracting operators have some handicaps like an computational complexity or multivariable needs. In this paper a novel feature extracting operator is proposed to overcome these demerits. This operator could be implemented very simply and be proved good performances through experiments applied to synthetic and real images.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.931-956
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• 2019

Documents contain information that can be used for various applications, such as question answering (QA) system, information retrieval (IR) system, and recommendation system. To use the information, it is necessary to develop a method of extracting such information from the documents written in a form of natural language. There are several kinds of the information (e.g., temporal information, spatial information, semantic role information), where different kinds of information will be extracted with different methods. In this paper, the existing studies about the methods of extracting the temporal information are reported and several related issues are discussed. The issues are about the task boundary of the temporal information extraction, the history of the annotation languages and shared tasks, the research issues, the applications using the temporal information, and evaluation metrics. Although the history of the tasks of temporal information extraction is not long, there have been many studies that tried various methods. This paper gives which approach is known to be the better way of extracting a particular part of the temporal information, and also provides a future research direction.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.151-154
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• 2008

In this paper, this program which is Retrieval System using Image Gray-scale histogram and Edge features is used to reduce the errors incurred by inputting methods which are used in a current Retrieval System. The Retrieval Algorithm is proceeding with several steps which are extracting features of images quality, extracting edge features and refining images, analysing extracted features, retaining important information from analyzed features, retrieving retained information from database, extracting and comparing among images from retrieved database. The proposed Retrieval System is used for a fast retrieval with accuracy and it is confirmed through simulations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.13 no.2
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• pp.127-137
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• 1988

In this paper, the extracting method for the control subcode in digital audio systems is pressented. And also the subcode format to display on the screen and a extracting method of the control signals within the DAS information are described. The extracted control signal from DAS is analyzed in the microprocessor systems and the microprocessor systems generate the screen information and then transmit to the CRT controller by the proposed protool.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.8
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• pp.147-159
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• 1994

The performance of the improvement method of spatial resolution for satellite images based on the generalized inverse matrix is superior to the conventional methods. But, this method calculates the coefficient values for extracting the spatial information from the relation between a small pixel and large pixels. Accordingly it has the problem of remaining the blocky patterns at the result image. In this paper, a new generalized inverse matrix method is proposed which is different in the calculation method of coefficient values for extracting the spatial information. In this proposed metod, it calculates the coefficient values for extracting the spatial information from the relation between a small pixel and small pixels. Consequently it can improve the spatial resolution more efficiently without remaining the blocky patterns at the result image. The effectiveness of the proposed method is varified by simulation experiments with real TM image data.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.4
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• pp.35-45
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• 2018

Users are sharing many of contents such as text, image, video, and so on in SNS. There are various information as like as personal interesting, opinion, and relationship in social media contents. Therefore, many of recommendation systems or search systems are being developed through analysis of social media contents. In order to extract subject-related topics of social context being collected from social media channels in developing those system, it is necessary to develop ontologies for semantic analysis. However, it is difficult to develop formal ontology because social media contents have the characteristics of non-formal data. Therefore, we develop a social topic system based on semantic and subject correlation. First of all, an extracting system of social topic based on semantic relationship analyzes semantic correlation and then extracts topics expressing semantic information of corresponding social context. Because the possibility of developing formal ontology expressing fully semantic information of various areas is limited, we develop a self-extensible architecture of ontology for semantic correlation. And then, a classifier of social contents and feed back classifies equivalent subject's social contents and feedbacks for extracting social topics according semantic correlation. The result of analyzing social contents and feedbacks extracts subject keyword, and index by measuring the degree of association based on social topic's semantic correlation. Deep Learning is applied into the process of indexing for improving accuracy and performance of mapping analysis of subject's extracting and semantic correlation. We expect that proposed system provides customized contents for users as well as optimized searching results because of analyzing semantic and subject correlation.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.65-68
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• 2000

This paper describes an approach for extracting invariant features using a view-based representation and recognizing an object with a high speed search method in FLIR. In this paper, we use a reformulated eigenspace technique based on robust estimation for extracting features which are robust for outlier such as noise and clutter. After extracting feature, we recognize an object using a partial distance search method for calculating Euclidean distance. The experimental results show that the proposed method achieves the improvement of recognition rate compared with standard PCA.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.9
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• pp.1081-1090
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• 1988

A series of procedures using image processing techniques is presented for extracting layout information fast and automatically from chip images. CIF (caltech intermediate form) is chosen for representing such information. First, line-edges are extracted using a line-edge detector. Then, thinning and noise removal procedures follow. Subsequent procedures are vertex extraction and vertex grouping. Finally, CIF is extracted from the coordinates of the grouped vertices. In this paper, the final process is applied to only metal layer. In experiments, this processing scheme is shown to be very effective in extracting CIF.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2287-2312
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• 2018

Extracting key visual information from images containing natural scene is a challenging task and an important step for the visually impaired to recognize information based on tactile graphics. In this study, a novel method is proposed for extracting salient regions based on global contrast enhancement and saliency cuts in order to improve the process of recognizing images for the visually impaired. To accomplish this, an image enhancement technique is applied to natural scene images, and a saliency map is acquired to measure the color contrast of homogeneous regions against other areas of the image. The saliency maps also help automatic salient region extraction, referred to as saliency cuts, and assist in obtaining a binary mask of high quality. Finally, outer boundaries and inner edges are detected in images with natural scene to identify edges that are visually significant. Experimental results indicate that the method we propose in this paper extracts salient objects effectively and achieves remarkable performance compared to conventional methods. Our method offers benefits in extracting salient objects and generating simple but important edges from images containing natural scene and for providing information to the visually impaired.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.5
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• pp.559-565
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• 1988

A new valley operator is presented for extracting sketch features which contain valleys and edges subject to local intensities. It is a very simple operator using the local probablities in a 3x3 local window. Experimental results show its excellent performance over the existing valley or edge operators.