• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1665-1667
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• 2007

Recently, retrieval of various video data has become an important issue as more and more multimedia content services are being provided. To effectively deal with video data, a semantic-based retrieval scheme that allows for processing diverse user queries and saving them on the database is required. In this regard, this paper proposes a semantic-based video retrieval system that allows the user to search diverse meanings of video data for electrical safetyrelated educational purposes by means of automatic annotation processing. If the user inputs a keyword to search video data for electrical safety-related educational purposes, the mobile agent of the proposed system extracts the features of the video data that are afterwards learned in a continuous manner, and detailed information on electrical safety education is saved on the database. The proposed system is designed to enhance video data retrieval efficiency for electrical safety-related educational purposes.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.3
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• pp.171-180
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• 2003

A content-based image retrieval(CBIR) system builds the image database using low-level features such as color, shape and texture and provides similar images that user wants to retrieve when the retrieval request occurs. What the user is interest in is a response time in consideration of the building time to build the index database and the response time to obtain the retrieval results from the query image. In a content-based image retrieval system, the similarity computing time comparing a query with images in database takes the most time in whole response time. In this paper, we propose the two-phase search method with the clustering technique of feature vector in order to minimize the similarity computing time. Experimental results show that this two-phase search method is 2-times faster than the conventional full-search method using original features of ail images in image database, while maintaining the same retrieval relevance as the conventional full-search method. And the proposed method is more effective as the number of images increases.

• Journal of the Semiconductor & Display Technology
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• v.18 no.4
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• pp.57-61
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• 2019

Nowadays, portable digital cameras such as smart phone cameras are being popularly used for entertainment and visual information recording. Given a database of geo-tagged images, a visual location recognition system can determine the place depicted in a query photo. One of the most common visual location recognition approaches is the bag-of-words method where local image features are clustered into visual words. In this paper, we propose a new bag-of-words-based visual location recognition algorithm using time-series streetview database. The proposed algorithm selects only a small subset of image features which will be used in image retrieval process. By reducing the number of features to be used, the proposed algorithm can reduce the memory requirement of the image database and accelerate the retrieval process.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.11-14
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• 2000

We present an image retrieval method that improves retrieval rate by using the fusion of histogram and wavelet moment features. The key idea is that images similar to a query image are selected in DB by using the wavelet moment features. Then the result images are retrieved from the selected images by using histogram method. In order to evaluate the performance of the proposed method, we use Brodatz texture database, MPEG-7 T1 database and Corel Draw photo. Experimental result shows that the proposed method is better than each of histogram method and wavelet moment method.

• Journal of Korea Multimedia Society
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• v.7 no.9
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• pp.1219-1232
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• 2004

Recently, the web sites, such as e-business sites and shopping mall sites, deal with lots of catalog image information and contents. As a result, it is required to support semantic-based image retrieval efficiently on such image data. This paper presents a semantic-based image retrieval system, which adopts XML and Fuzzy technology. To support semantic-based retrieval on product catalog images containing multiple objects, we use a multi-level metadata structure which represents the product information and semantics of image data. To enable semantic-based retrieval on such image data, we design a XML database for storing the proposed metadata and study how to apply fuzzy data. This paper proposes a system, generate the fuzzy data automatically to use the image metadata, that can support semantic-based image retrieval by utilizing the generating fuzzy data. Therefore, it will contribute in improving the retrieval correctness and the user's satisfaction on semantic-based e-catalog image retrieval.

• The Transactions of the Korea Information Processing Society
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• v.6 no.11
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• pp.2911-2921
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• 1999

We present new methods for an efficient retrieval of SGML documents. We define IDDL (index database description language) which is able to describe various information such as meta data, an indexing range, and the creation and manipulation of a database. In addition, we design IDQL (index database query language) that can deal with querying meta data as well as logical structure. Especially, the retrieval system based on IDDL and IDQL has been developed and implemented, and has been experimented on large number of documents. Experimental result shows that the proposed method provides the dynamic creation of an index database and a convenient retrieval environment.

• ETRI Journal
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• v.39 no.1
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• pp.97-107
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• 2017

A fast and accurate building-level visual place recognition method built on an image-retrieval scheme using street-view images is proposed. Reference images generated from street-view images usually depict multiple buildings and confusing regions, such as roads, sky, and vehicles, which degrades retrieval accuracy and causes matching ambiguity. The proposed practical database refinement method uses informative reference image and keypoint selection. For database refinement, the method uses a spatial layout of the buildings in the reference image, specifically a building-identification mask image, which is obtained from a prebuilt three-dimensional model of the site. A global-positioning-system-aware retrieval structure is incorporated in it. To evaluate the method, we constructed a dataset over an area of $0.26km^2$. It was comprised of 38,700 reference images and corresponding building-identification mask images. The proposed method removed 25% of the database images using informative reference image selection. It achieved 85.6% recall of the top five candidates in 1.25 s of full processing. The method thus achieved high accuracy at a low computational complexity.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.763-765
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• 2005

In the area of remote sensing, an immense number of images are continuously generated by various remote sensing systems. These images must then be managed by a database system efficient storage and retrieval. There are many types of image database systems, among which the content-based image retrieval (CBIR) system is the most advanced. CBIR utilizes the metadata of images including the feature data for indexing and searching images. Therefore, the performance of image retrieval is significantly affected by the storage method of the image metadata. There are many features of images such as color, texture, and shape. We mainly consider the shape feature because shape can be identified in any remote sensing while color does not always necessarily appear in some remote sensing. In this paper, we propose a metadata representation and storage method for image search based on shape features. First, we extend MPEG-7 to describe the shape features which are not defined in the MPEG-7 standard. Second, we design a storage schema for storing images and their metadata in a relational database system. Then, we propose an efficient storage method for managing the shape feature data using a Wavelet technique. Finally, we provide the performance results of our proposed storage method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2211-2232
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• 2018

The unstructured and semi-structured big data in social network poses new challenges in query retrieval. This requirement needs to be met by introducing quality retrieval time measures like indexing. Due to the huge volume of data storage, there originate the need for efficient index algorithms to promote query processing. However, conventional algorithms fail to index the huge amount of frequently obtained information in real time and fall short of providing scalable indexing service. In this paper, a new LIndex algorithm, which is a heuristic on Lucene is built on Neo4jHA architecture that holds the social network Big data. LIndex is a flexible and simplified adaptive indexing scheme that ascendancy decomposed shortest paths around term neighbors as basic indexing unit. This newfangled index proves to be effectual in query space pruning of graph database Neo4j, scalable in index construction and deployment. A graph query is processed and optimized beyond the traditional Lucene in a time-based manner to a more efficient path method in LIndex. This advanced algorithm significantly reduces query fetch without compromising the quality of results in time. The experiments are conducted to confirm the efficiency of the proposed query retrieval in Neo4j graph NoSQL database.

• Journal of KIISE:Databases
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• v.31 no.3
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• pp.243-251
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• 2004

Most programs of bioinformatics provide biochemists and biologists retrieve and analysis services of gene and protein database. As these services retrieve database for each arrival of user's request, it takes a long time and increases server's load and response time. In this paper. by utilizing database retrieval patterns of sequence alignment programs in bioinformatics, grouping method is proposed to share database retrieval between many requests. Carpool method is also proposed to reduce response time as well as to increase system expandability by combining new arriving requests with the previous on going requests. The performance of our two proposed schemes is verified by mathematic analysis and simulation.