• Journal of the Semiconductor & Display Technology
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• v.12 no.4
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• pp.33-38
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• 2013

Image retrieval is one of the most exciting and fastest growing research fields in the area of multimedia technology. As the amount of digital contents continues to grow users are experiencing increasing difficulty in finding specific images in their image libraries. This paper proposes an efficient image descriptor which uses a local color and texture in the non-overlapped block images. To evaluate the performance of the proposed method, we assessed the retrieval efficiency in terms of ANMRR with common image dataset. The experimental trials revealed that the proposed algorithm exhibited a significant improvement in ANMRR, compared to Dominant Color Descriptor and Edge Histogram Descriptor.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.1
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• pp.122-129
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• 2007

As the availability of an image information has been significantly increasing, necessity of system that can manage an image information is increasing. Accordingly, we proposed the content-based image retrieval(CBIR) method based on an efficient combination of a color feature and an image's shape and position information. As a color feature, a HSI color histogram is chosen which is known to measure spatial of colors well. Shape and position information are obtained using Hu invariant moments in the luminance of HSI model. For efficient similarity computation, the extracted features(Color histogram, Hu invariant moments) are combined and then measured precision. As a experiment result using DB that was supported by http://www.freefoto.com, the proposed image search engine has 93% precision and can apply successfully image retrieval applications.

• The Journal of Korean Association of Computer Education
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• v.6 no.1
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• pp.9-17
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• 2003

XML(eXtensible Markup Language), next generation internet standard language has the advantage of easy re-use and re-structure in other computing environment because it has the separate data, presentation and structure. In this paper, we implement the efficient retrieval system for the general user by limiting the XML documents on the multimedia learning contents for the virtual education system. The system design is based on SCO Metadata unit defined in SCORM as the proposed virtual education standard. Each XML documents has three indexes - keyword, element and attribute. Also, it makes possible to retrieve data without previous knowledge of the DTD by making the element retrieval screen structure for the user interface. And it gives the user various result screen formats such as XML and HTML by restructuring the retrieval result through XML-QL and XSL, respectively.

• Journal of Korea Multimedia Society
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• v.10 no.11
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• pp.1398-1406
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• 2007

Providing natural and efficient access to the fast growing multimedia information is a critical aspect for content-based information system. Query by humming system allows the user to find a song by humming part of the tune form music database. Conventional music information retrieval systems use a high precision pitch extraction method. However, it is very difficult to extract true pitch perfectly. So, In this paper, we propose to use YIN parameter with applying the reliability to reduce the pitch extraction errors. And we describes developed music information retrieval method based on a query by humming system which uses reliable feature extraction. Developed system is based on a continuous dynamic programming algorithm with features including pitch, duration and energy along with their confidence measures. The experiment showed that the proposed method could reduce the errors of the top-10 7.2% and the top-1 9.1% compared with the cepsturm based multiple pitch candidate. The overall retrieval system achieved 92.8% correct retrieval in the top-10 rank list on a database of 155 songs.

• Journal of the Korea Society of Computer and Information
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• v.18 no.5
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• pp.43-52
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• 2013

In recent years, a large amount of music content is distributed in the Internet environment. In order to retrieve the music content effectively that user want, various studies have been carried out. Especially, it is also actively developing music recommendation system combining emotion model with MIR(Music Information Retrieval) studies. However, in these studies, there are several drawbacks. First, structure of emotion model that was used is simple. Second, because the emotion model has not designed for Korean language, there is limit to process the semantic of emotional words expressed with Korean. In this paper, through extending the existing emotion model, we propose a new emotion model KOREM(KORean Emotional Model) based on Korean. And also, we design and implement ontology using emotion model proposed. Through them, sorting, storage and retrieval of music content described with various emotional expression are available.

• Journal of Intelligence and Information Systems
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• v.13 no.1
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• pp.1-14
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• 2007

Character images for the background screen of cell phones are one of the fast growing sectors of the mobile content market. However, character image buyers currently experience tremendous difficulties in searching for desired images due to the awkward image search process. Content-based image retrieval (CBIR) widely used for image retrieval could be a good candidate as a solution to this problem, but it needs to overcome the limitation of the mobile Internet environment where an initial query set (IQS) cannot be easily provided as in the PC-based environment. We propose a new approach, IQS-AutoGen, which automatically generates an initial query set for CBIR on the mobile Internet. The approach applies the collaborative filtering (CF), a well-known recommendation technique, to the CBIR process by using users' preference information collected during the relevance feedback process of CBIR. The results of the experiment using a PC-based prototype system show that the proposed approach successfully satisfies the initial query requirement of CBIR in the mobile Internet environment, thereby outperforming the current image search process on the mobile Internet.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.387-388
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• 2007

In this paper, a content-based image retrieval method considering both local information and spatial correlation of image is proposed. In order to efficiently represent the spatial correlation, texture structure is classified into three kinds of pattern. In experiment result, our method improves $3.94%{\sim}11.23%$ precision rate over the existing methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.3B
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• pp.332-337
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• 2001

본 논문에서는 영상 검색 방법의 하나인 내용에 기반을 둔 검색 방법(content based retrieval)으로 주변 화소의 컬러 히스토그램(NCH)을 이용하는 방법을 제안한다. 제안한 방법은 각 화소에 대해 주변 화소의 컬러 히스토르램을 데이터베이스의 색인 정보로 정장하는 방법으로, 영상의 공간 정보와 컬러 정보를 효과적으로 결합한 방법이다. 실험결과, 제안한 방법은 히스토그램과 CCV(Color Coherence Vector)를 이용한 방법보다 검색 효율이 우수하고 카메라의 위치 및 확대, 축소에 따른 영상의 큰 변화에도 매우 강인한 것으로 나타났다.

• Journal of the Korean Society for information Management
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• v.23 no.2
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• pp.5-19
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• 2006

The purpose of this study is to observe and analyze information searching behaviors of various user groups in different access modes for designing user-centered query interface of content-based Music Information Retrieval System(MIRS). Two expert groups and two non-expert groups were recruited for this research. The data gathering techniques employed in this study were in-depth interviewing, participant observation, searching task experiments, think-aloud protocols, and post-search surveys. Expert users, especially majoring in music theory, preferred to input exact notes one by one using the devices such as keyboard and musical score. On the other hand, non-expert users preferred to input melodic contours by humming.

• Journal of KIISE:Databases
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• v.28 no.3
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• pp.406-417
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• 2001

With the advances in multimedia databases on the World Wide Web, it becomes more important to provide users with the search capability of distributed multimedia data. While there have been many studies about the database selection and the collection fusion for text databases. The multimedia databases on the Web have autonomous and heterogeneous properties and they use mainly the content based retrieval. The collection fusion problem of multimedia databases is concerned with the merging of results retrieved by content based retrieval from heterogeneous multimedia databases on the Web. This problem is crucial for the search in distributed multimedia databases, however, it has not been studied yet. This paper provides novel algorithms for processing the collection fusion of heterogeneous multimedia databases on the Web. We propose two heuristic algorithms for estimating the number of objects to be retrieved from local databases and an algorithm using the linear regression. Extensive experiments show the effectiveness and efficiency of these algorithms. These algorithms can provide the basis for the distributed content based retrieval algorithms for multimedia databases on the Web.