• Journal of Korea Multimedia Society
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• v.7 no.5
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• pp.648-657
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• 2004

A method of extracting central objects in color images without any prior-knowledge is proposed in this paper, which uses basically information of significant color distribution. A central object in an image is defined as a set of regions that lie around center of the image and have significant color distribution against the other surround (or background) regions. Significant colors in an image are first defined as the colors that are distributed more densely around center of the image than near borders. Then core object regions (CORs) are selected as the regions a lot of pixels of which have the significant colors. Finally, the adjacent regions to the CORs are iteratively merged if they are similar to the CORs but not to the background regions in color distribution. The merging result is accepted as the central object that may include differently color-characterized regions and/or two or more objects of interest. Usefulness of the significant colors in extracting the central object was verified through experiments on several kinds of test images. We expect that central objects shall be used usefully in image retrieval applications.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.91-97
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• 2009

This paper proposes novel FE-CBIRS that finds best position of a cut to be retrieved based on color feature distribution in digital contents of IPTV. Conventional CBIRS have used a method that utilizes both color and shape information together to classify images, as well as a method that utilizes both feature information of the entire region and feature information of a partial region that is extracted by segmentation for searching. Also, in the algorithm, average, standard deviation and skewness values are used in case of color features for each hue, saturation and intensity values respectively. Furthermore, in case of using partial regions, only a few major colors are used and in case of shape features, the invariant moment is mainly used on the extracted partial regions. Due to these reasons, some problems have been issued in CBIRS in processing time and accuracy so far. Therefore, in order to tackle these problems, this paper proposes the FE-CBIRS that makes searching speed faster by classifying and indexing the extracted color information by each class and by using several cuts that are restricted in range as comparative images.

• Journal of the Korea Society of Computer and Information
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• v.13 no.3
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• pp.15-25
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• 2008

Recently, with the growing use of e-learning, instructors develop new online courses using a variety of contents and then store the results on their computers. These contents should be updated with new information as time goes on, and a new content also can be produced by reusing these ones. However, a lot of time will be needed for instructors to search, edit, and manage various contents stored from place to place on their computers. Currently, the development of the e-learning content management tool. which performs efficiently these functions on the PC environment, leaves much to be desired. Therefore, in this paper, we proposed an e-learning content creation and management system which can manage efficiently a variety of contents stored from different locations on an instructor's computer and can develop easily new online courses. The proposed system can be used widely to develop contents for instructors based on the PC environment. For performance evaluation, this paper compared the proposed system with the previous system according to the retrieval time of content keyword, and the experiment showed that our system is much better than the previous one.

• Journal of IKEEE
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• v.13 no.2
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• pp.159-166
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• 2009

So far, many researches have been done to retrieve music information using static classification descriptors such as genre and mood. Since static classification descriptors are based on diverse content-based musical features, they are effective in retrieving similar music in terms of such features. However, human emotion or mood transition triggered by music enables more effective and sophisticated query in music retrieval. So far, few works have been done to evaluate the effect of human mood transition by music. Using formal representation of such mood transitions, we can provide personalized service more effectively in the new applications such as music recommendation. In this paper, we first propose our Emotion State Transition Model (ESTM) for describing human mood transition by music and then describe a music classification and recommendation scheme based on the ESTM. In the experiment, diverse content-based features were extracted from music clips, dimensionally reduced by NMF (Non-negative Matrix Factorization, and classified by SVM (Support Vector Machine). In the performance analysis, we achieved average accuracy 67.54% and maximum accuracy 87.78%.

• Convergence Security Journal
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• v.10 no.1
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• pp.49-53
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• 2010

Recently multimedia has been formed, provided, and shared enough not to compare with the past, due to the proliferation of Internet and the development of hardware relating to multimedia. Accordingly to internationally give a proper expression to metadata of multimedia, the standard of MPEG-7 has been established, and researches for image search among various data of multimedia using MPEG-7 are going on. Thus there are meaning-based search. In the former there is a merit that search speed is fast, but technology and accuracy by technical knowledge on the image. In the latter the accuracy of search is decreasing because of not understanding the meaning about image and the internet of users. In this study to solve these problems a search system has been designed by combining the two methods. Also the search and manage image data by handheld devices such as portable PDA or smart phone, a system. Once this is used, multimedia data can be efficiently searched and utilized by handheld devices.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.1071-1092
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• 2014

Annotating images with tags that describe the content of the images facilitates image retrieval. However, this task is challenging for both humans and computers. In response, a new approach has been proposed that converts the manual image annotation task into CAPTCHA challenges. However, this approach has not been widely used because of its weak security and the fact that it can be applied only to annotate for a specific type of attribute clearly separated into mutually exclusive categories (e.g., gender). In this paper, we propose a novel image annotation CAPTCHA scheme, which can successfully differentiate between humans and computers, annotate image content difficult to separate into mutually exclusive categories, and generate verified test images difficult for computers to identify but easy for humans. To test its feasibility, we applied our scheme to annotate images of human faces with their age groups and conducted user studies. The results showed that our proposed system, called AgeCAPTCHA, annotated images of human faces with high reliability, yet the process was completed by the subjects quickly and accurately enough for practical use. As a result, we have not only verified the effectiveness of our scheme but also increased the applicability of image annotation CAPTCHAs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.1
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• pp.213-231
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• 2014

Existing image search systems allow users to search images by keywords, or by example images through content-based image retrieval (CBIR). On the other hand, users might learn more relevant textual information about an image from its text captions or surrounding contexts within documents or Web pages. Without such contexts, it's difficult to extract semantic description directly from the image content. In this paper, we propose an annotation watermarking system for users to embed text descriptions, and retrieve more relevant textual information from similar images. First, tags associated with an image are converted by two-dimensional code and embedded into the image by discrete wavelet transform (DWT). Next, for images without annotations, similar images can be obtained by CBIR techniques and embedded annotations can be extracted. Specifically, we use global features such as color ratios and dominant sub-image colors for preliminary filtering. Then, local features such as Scale-Invariant Feature Transform (SIFT) descriptors are extracted for similarity matching. This design can achieve good effectiveness with reasonable processing time in practical systems. Our experimental results showed good accuracy in retrieving similar images and extracting relevant tags from similar images.

• Journal of the Korean Society for Library and Information Science
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• v.40 no.2
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• pp.299-314
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• 2006

This study suggests evaluation criteria for the web-based question-answer databases provided by major Korean search portals. In particular, this study suggests evaluation criteria for the relevance of question titles, entire questions, and answer's. The evaluation criteria for the qualify of answers are also developed. Based on these criteria. evaluation of documents from Naver Knowledge-in are performed. The results of this study can be implemented to the development of test collection of question-answer databases. The implications for system designers and web content providers are discussed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.6
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• pp.1354-1359
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• 2013

With the development of multimedia and network technology, the production of multimedia contents is rapidly increasing. Meanwhile, the technology to search and use the contents is still insufficient. There are standards for multimedia contents to address the problem, but they cannot fully support diverse multimedia data types or ensure their interoperability. In this paper, an ontology-based content search system is proposed to ensure the interoperability of multimedia contents. The ontology is configured by presenting the rules for it using the schema structure of the multimedia description scheme (MDS) of MPEG-7. Based on this ontology, This paper extend multimedia relationship based on ontology, thus established the semantic retrieval system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2840-2861
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• 2020

The purpose of this survey-based study is to make an analysis of search engine users' behaviors on the Search Engine Results Pages (SERPs) based on the three demographic characteristics gender, age, and program studying. In this study, a questionnaire was designed with 12 closed-ended questions. Remaining questions other than the demographic characteristic related ones were about "tab", "advertisement", "spelling suggestion", "related query suggestion", "instant search suggestion", "video result", "image result", "pagination" and the amount of clicking results. The questionnaire was used and the data collected were analyzed with the descriptive statistics as well as the inferential statistics. 84.2% of the study population was reached. Some of the major results are as follows: Most of each demographic characteristic category (i.e. female, male, under-20, 20-24, above-24, English computer engineering, Turkish computer engineering, software engineering) have rarely or more click for tab, spelling suggestion, related query suggestion, instant search suggestion, video result, image result, and pagination. More than 50.0% of female category click advertisement rarely; however, for the others, 50.0% or more never click advertisement. For every demographic characteristic category, between 78.0% and 85.4% click 10 or fewer results. This study would be the first attempt with its complete content and design. Search engine providers and researchers would gain knowledge to user behaviors about the usage of the SERPs based on the demographic characteristics.