• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.2
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• pp.152-157
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• 2010

The development of computer and internet has introduced various types of media - such as, image, audio, video, and voice - to the traditional text-based information. However, most of the information retrieval systems are based only on text, which results in the absence of ability to use available information. By utilizing the available media, one can improve the performance of search system, which is commonly called content-based retrieval and content-based image retrieval system specifically tries to incorporate the analysis of images into search systems. In this paper, a content-based image retrieval system using HSI color space, ART2 algorithm, and SOM algorithm is introduced. First, images are analyzed in the HSI color space to generate several sets of features describing the images and an SOM algorithm is used to provide candidates of training features to a user. The features that are selected by a user are fed to the training part of a search system, which uses an ART2 algorithm. The proposed system can handle the case in which an image belongs to several groups and showed better performance than other systems.

• Journal of the Korea Society of Computer and Information
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• v.5 no.2
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• pp.60-70
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• 2000

As a result of remarkable developments in computer technology, the image retrieval system that can efficiently retrieve image data becomes a core technology of information-oriented society. In this paper, we implemented the Hierarchical Image Retrieval System for content-based image data retrieval. At the first level, to get color information, with improving the indexing method using color distribution characteristic suggested by Striker et al., i.e. the indexing method considering local color distribution characteristics, the system roughly classifies images through the improved method. At the second level, the system finally retrieves the most similar image from the image queried by the user using the shape information about the image groups classified at the first level. To extract the shape information, we use the Improved Moment Invariants(IMI) that manipulates only the pixels on the edges of objects in order to overcome two main problems of the existing Moment Invariant methods large amount of processing and rotation sensitiveness which can frequently be seen in the Directive Histogram Intersection technique suggested by Jain et al. Experiments have been conducted on 300 automobile images And we could obtain the more improved results through the comparative test with other methods.

• The KIPS Transactions:PartB
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• v.10B no.5
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• pp.543-552
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• 2003

An increasing in quantity of multimedia data brought a new problem that expected data should be retrieved fast and exactly. The adequate representation is a key element for the efficient retrieval. For this reason, MPEG-7 standard was established for description of multimedia data in 2001. However, the content of the standard is massive and the approach method is not clear for real application system yet, because of properties of MPEG-7 standard that has to include a lot of potential cases. In this paper, we suggested implementation scheme of retrieval system with using of only visual descriptors and presented the performance results of developed system. From the result of developed system, MPEG-7 VIRS (Video/Image Retrieval System), we analyzed the retrieval results between using individual descriptor and using multiple descriptors, and showed a layout for real application system.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.677-681
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• 2006

In this paper, we suggest the GUI Management Tool, named K-Manager, for management and service of science and technology information that stored in distributed retrieval databases. Generally, it must be adapted retrieval database system for web based S&T contents service. But, It is inconvenient contents manager or the system administrator controls information easily, because it does not support the S&T information management process like TOAD, which can use for the relation database, in information retrieval database system. Using K-Manager, content manager can process the S&T content and system manager can manage the databases easily. The proposed tool active controls information effectively which is stored in the distributed retrieval database which guarantee the safety management of the contents stored in database and operate retrieval with efficient performances. Our tool consists of two sub systems, one is content manager, the other is database manager for YESKISTI based on KRISTAL-IRMS.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.3
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• pp.115-124
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• 2004

The content-based retrieval using low-level features can hardly provide the retrieval result that corresponds with conceptual demand of user for intelligent retrieval. Video includes not only moving picture data, but also audio or closed-caption data. Knowledge-based video retrieval is able to provide the retrieval result that corresponds with conceptual demand of user because of performing automatic indexing with such a variety data. In this paper, we present the knowledge-based video retrieval system using Korean closed-caption. The closed-caption is indexed by Korean keyword extraction system including the morphological analysis process. As a result, we are able to retrieve the video by using keyword from the indexing database. In the experiment, we have applied the proposed method to news video with closed-caption generated by Korean stenographic system, and have empirically confirmed that the proposed method provides the retrieval result that corresponds with more meaningful conceptual demand of user.

• Korean Journal of Construction Engineering and Management
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• v.13 no.6
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• pp.84-93
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• 2012

The information generated from large and complex construction projects transfer and evolve in long-term business cycle. Therefore, while there is any problem, such as delay, the cause of the problem might relate to the previous business process rather than where it arises. However, for complex project players and business relationships, it is unsuitable to search an information flow using traditional retrieval methods. This research addresses a relationship-based information search system to analyze the information flow in large-scale and complex construction projects. First, we identified the components of the information retrieval system customizing for a large-scale complex construction projects, and then developed the inference algorithm which define the relationship between business processes. For the validation, we applied the system on a business information system of urban regeneration projects and suggested some application using information flow retrieval system for project players and project managers. Using the system, players are easy to prepare for their work process and managers can define the causal flow of the problem.

• Bioinformatics and Biosystems
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• v.1 no.1
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• pp.46-50
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• 2006

According to the advancement of experimental techniques in molecular biology, genomic and protein sequence databases are increasing in size exponentially, and mean sequence lengths are also increasing. Because the sizes of these databases become larger, it is difficult to search similar sequences in biological databases with significant homologies to a query sequence. In this paper, we present the N-gram indexing method to retrieve similar sequences fast, precisely and comparably. This method regards a protein sequence as a text written in language of 20 amino acid codes, adapts N-gram tokens of fixed-length as its indexing scheme for sequence strings. After such tokens are indexed for all the sequences in the database, sequences can be searched with information retrieval algorithms. Using this new method, we have developed a protein sequence search system named as ProSeS (PROtein Sequence Search). ProSeS is a protein sequence analysis system which provides overall analysis results such as similar sequences with significant homologies, predicted subcellular locations of the query sequence, and major keywords extracted from annotations of similar sequences. We show experimentally that the N-gram indexing approach saves the retrieval time significantly, and that it is as accurate as current popular search tool BLAST.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.6
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• pp.111-118
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• 1996

A content-based image retrieval system is designed and implemetned using the color featurees which are histogram intersection and color pairs. The preprocessor for the image retrieval manage linearly the existing HSI(hue, saturation, saturation, intensity). Hue and intensity histogram thresholding for each color attribute is performed to split the chromatic and achromatic regions respectively. Grouping te indexes produced by the histogram intersection is used to save the retrieval times. Each image is divided into the cells of 32$\times$32 pixels, and color pairs are used to represent the query during retrievals. The recall/precision of histogram intersection is 0.621/0.663 and recall/precision of color pairs is 0.438/0.536. And recall/precision of proposed method is 0.765/0.775/. It is shown that the proposed method using histogram intersection and color pairs improves the retrieval rates.

• Proceedings of the IEEK Conference
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• summer
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• pp.427-434
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• 2004

In this paper, we present a overview of content-based image retrieval (CBIR) systems: its results and its problems. We propose our CBIR system currently based on color and texture. From the CBIR systems. we discuss the way to add semantic values in image retrieval systems. There are 3 ways for adding them: concept definition, machine learning and man-machine interaction. Along with this we introduce our preliminary results and discuss them in the goal of reaching semantic retrieval. Different result representation schemes are presented. At last, we present our work to build a complete annotated image database and our image annotaion program.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.2 s.308
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• pp.57-64
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• 2006

Tn this paper, We propose a user friendly object-based multimedia retrieval system using the HCNN(HippoCampus Neural Network. Most existing approaches to content-based retrieval rely on query by example or user based low-level features such as color, shape, texture. In this paper we perform a scene change detection and key frame extraction for the compressed video stream that is video compression standard such as MPEG. We propose a method for automatic color object extraction and ACE(Adaptive Circular filter and Edge) of content-based multimedia retrieval system. And we compose multimedia retrieval system after learned by the HCNN such extracted features. Proposed HCNN makes an adaptive real-time content-based multimedia retrieval system using excitatory teaming method that forwards important features to long-term memories and inhibitory learning method that forwards unimportant features to short-term memories controlled by impression.