• The KIPS Transactions:PartB
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• v.10B no.2
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• pp.179-188
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• 2003

In content-based image retrieval, the query is an image itself and the retrieval process is the process that seeking the similar images to the given query image. In this way of retrieval, the user has to know the basic physical features of target images that he wants to retrieve. But it has some restriction because to retrieve the target image he has to know the basic physical feature space such as color, texture, shape and spatial relationship. In this paper, we propose an emotion-based retrieval system. It uses the emotion that color images have. It is different from past emotion-based image retrieval in point of view that it uses relevance feedback to estimate the users intend and it is easily combined with past content-based image retrieval system. To test the performance of our proposed system, we use MPEG-7 color descriptor and emotion language such as "warm", "clean", "bright" and "delight" We test about 1500 wallpaper images and get successful result.lpaper images and get successful result.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.7C
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• pp.719-725
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• 2003

The content-based image retrieval system extracts features of color, shape and texture from raw images, and builds the database with those features in the indexing process. The search in the whole retrieval system is defined as a process which finds images that have large similarity to query image using the feature database. This paper proposes a new two-stage search method in the content-based image retrieval system. The method is that the features are condensed and stored by the property of Cauchy-Schwartz inequality in order to reduce the similarity computation time which takes a mostly response time from entering a query to getting retrieval results. By the extensive computer simulations, we have observed that the proposed two-stage search method successfully reduces the similarity computation time while maintaining the same retrieval relevance as the conventional exhaustive search method. We also have observed that the method is more effective as the number of images and dimensions of the feature space increase.

• Journal of Convergence for Information Technology
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• v.9 no.10
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• pp.154-162
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• 2019

Despite the development of information and communication technology, which has a great impact on society and culture, there is no platform that provides a systematic classification and state-of-the-art information retrieval system on the traditional culture. Therefore, this paper developed a traditional culture retrieval system capable of convergence services with systematic classification and retrieval based on automatically generate and visualize the 3D timeline. This system provides the function of collecting traditional culture contents, classifying and storing collected traditional culture contents, and automatically generating 3D digital timeline based on stored traditional culture contents. In addition, a system satisfaction questionnaire was developed to evaluate the usability of the system, and 19 students participated in verifying the system. As a result of the experiment, the satisfaction of the system showed that all items were 'satisfied' on average.

• The Transactions of the Korea Information Processing Society
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• v.4 no.6
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• pp.1418-1432
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• 1997

Most general content_based image retrieval techniques use color and texture as retrieval indices. In color techniques, color histogram and color pair based color retrieval techniques suffer from a lack of spatial information and text. And This paper describes the design and implementation of content_based image retrieval system using color space and keywords. The preprocessor for image retrieval has used the coordinate system of the existing HSI(Hue, Saturation, Intensity) and preformed to split One image into chromatic region and achromatic region respectively, It is necessary to normalize the size of image for 200*N or N*200 and to convert true colors into 256 color. Two color histograms for background and object are used in order to decide on color selection in the color space. Spatial information is obtained using a maximum entropy discretization. It is possible to choose the class, color, shape, location and size of image by using keyword. An input color is limited by 15 kinds keyword of chromatic and achromatic colors of the Korea Industrial Standards. Image retrieval method is used as the key of retrieval properties in the similarity. The weight values of color space ${\alpha}(%)and\;keyword\;{\beta}(%)$ can be chosen by the user in inputting the query words, controlling the values according to the properties of image_contents. The result of retrieval in the test using extracted feature such as color space and keyword to the query image are lower that those of weight value. In the case of weight value, the average of te measuring parameters shows approximate Precision(0.858), Recall(0.936), RT(1), MT(0). The above results have proved higher retrieval effects than the content_based image retrieval by using color space of keywords.

• The Journal of the Acoustical Society of Korea
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• v.23 no.6
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• pp.488-496
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• 2004

This paper describes a music information retrieval system which uses humming as the key for retrieval Humming is an easy way for the user to input a melody. However, there are several problems with humming that degrade the retrieval of information. One problem is a human factor. Sometimes people do not sing accurately, especially if they are inexperienced or unaccompanied. Another problem arises from signal processing. Therefore, a music information retrieval method should be sufficiently robust to surmount various humming errors and signal processing problems. A retrieval system has to extract pitch from the user's humming. However pitch extraction is not perfect. It often captures half or double pitches. even if the extraction algorithms take the continuity of the pitch into account. Considering these problems. we propose a system that takes multiple pitch candidates into account. In addition to the frequencies of the pitch candidates. the confidence measures obtained from their powers are taken into consideration as well. We also propose the use of an algorithm with three dimensions that is an extension of the conventional DP algorithm, so that multiple pitch candidates can be treated. Moreover in the proposed algorithm. DP paths are changed dynamically to take deltaPitches and IOIratios of input and reference notes into account in order to treat notes being split or unified. We carried out an evaluation experiment to compare the proposed system with a conventional system. From the experiment. the proposed method gave better retrieval performance than the conventional system.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.5
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• pp.510-521
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• 2001

Image retrieval system should be construct for searching fast, efficient image be extract the accurate feature information of image with more massive and more complex characteristics. Image retrieval system are essential differences between image databases and traditional databases. These differences lead to interesting new issues in searching of image, data modeling. So, cause us to consider new generation method of database, efficient retrieval method of image. In this paper, To extract feature information of edge using in searching from input image, we was performed to extract the edge by convolution Laplacian mask and input image, and we implemented the annotation-based and content-based image retrieval system for searching fast, efficient image by generation image database from extracting feature information of edge and metadata. We can improve the performance of the image contents retrieval, because the annotation-based and content-based image retrieval system is using image index which is made up of the content-based edge feature extract information represented in the low level of image and annotation-based edge feature information represented in the high level of image. As a conclusion, image retrieval system proposed in this paper is possible the accurate management of the accumulated information for the image contents and the information sharing and reuse of image because the proposed method do construct the image database by metadata.

• The Korean Journal of Archival Studies
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• no.19
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• pp.57-102
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• 2009

Recently, distribution of record via web and coefficient of utilization are increase. so, Archival information service using website becomes essential part of record center. The main point of archival information service by website is making record information retrieval easy. It has need of matching user's request and representation of record resources correctly to making archival information retrieval easy. Archivist and record manager have used various information representation tools from taxonomy to recent thesaurus, still, the accuracy of information retrieval has not solved. This study constructed record retrieval system based on Topic Map by modeling record resources which focusing on description metadata of the records to improve this problem. The target user of the system is general web users and its range is limited to the president related sources in the National Archives Portal Service. The procedure is as follows; 1) Design an ontology model for archival information service based on topic map which focusing on description metadata of the records. 2) Buildpractical record retrieval system with topic map that received information source list, which extracted from the National Archives Portal Service, by editor. 3) Check and assess features of record retrieval system based on topic map through user interface. Through the practice, relevance navigation to other record sources by semantic inference of description metadata is confirmed. And also, records could be built up as knowledge with result of scattered archival sources.

• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.25-34
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• 2009

As the trend of the Web is changing toward 'Web 2.0', OpenAPIs, Web 2.0's core technology, are used in many web sites. In the past, services in websites are used in its own, but recently it is possible to use services in other websites by using OpenAPI. In u-GIS many vendors also can provide combined service by using OpenAPI. There are already lots of OpenAPIs and the numer of OpenAPI increases very fast. So it is difficult to find a service that we want to use, and also difficult to find services for mashup. In this paper, we developed retrieval methods for OpenAPIs and mashup capable services based on similarity. First we define the integrated service information model to cover various protocols of OpenAPI, then developed a retrieval methods based on it. By implementing system according these methods by using relational database and JSP, we prove that the system can provide an ranked result sets based on similarity, OpenAPI's integration retrieval results and mashup capable service retrieval results.

• Journal of Broadcast Engineering
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• v.9 no.2
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• pp.151-163
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• 2004

In this paper, we propose a content-based video indexing and retrieval system using MPEG-7 standard to retrieve and manage videos efficiently. The proposed system consists of video indexing module for a video DB and video retrieval module to allow various query methods on a web environment. Video indexing module stores metadata such as manually typed in keywords, automatically recognized character names, and MPEG-7 visual descriptors extracted by indexing module into a DB in a sever side. A user can access to retrieval module by a web and retrieve desired videos through various query methods like keywords, faces, example and sketch. For this retrieval system, we propose ATC(Adaptive Twin Comparison) as a cut detection method for efficient video indexing and QBME(Query By Modified Example) as an improved content-based query method for the convenience of users. Experimental results show that the proposed ATC method detects cuts well and the proposed QBME method provides the conveniences better than existing query methods such as QBE(Query By Example) and QBS(Query By Sketch).

• Journal of Korea Multimedia Society
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• v.13 no.8
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• pp.1245-1255
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• 2010

In current Web 2.0 environment, one of the most core technology is social bookmarking which users put tags and bookmarks to their interesting Web pages. The main purpose of social bookmarking is an effective information service by use of retrieval, grouping and share based on user's bookmark information and tagging result of their interesting Web pages. But, current social bookmarking system uses the number of bookmarks and tag information separately in information retrieval, where the number of bookmarks stand for user's degree of interest on Web contents, information retrieval, and classification serve the purpose of tag information. Because of above reason, social bookmarking system does not utilize effectively the bookmark information and tagging result. This paper proposes a Web contents ranking algorithm combining bookmarks and tag information, based on preceding research on associative tag extraction by tag clustering. Moreover, we conduct a performance evaluation comparing with existing retrieval methodology for efficiency analysis of our proposed algorithm. As the result, social bookmarking system utilizing bookmark with tag, key point of our research, deduces a effective retrieval results compare with existing systems.