• Journal of the Korea Society of Computer and Information
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• v.12 no.6
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• pp.97-104
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• 2007

This paper presents the problem of the feature extraction techniques that has been used a content-based analysis, classification and retrieval in audio data and proposes a course of the preprocessing for a new contents-based retrieval methods. Because the feature vector according to sampling value changes, the existing audio data analysis is problem that same music is appraised by other music. Therefore, we propose waveform information extraction method of PCM data for retrieval audio data of various format to contents-based. If this method is used. we can find that audio datas that get into sampling in various format are same data. And it may be applied in contents-based music retrieval system. To verity the performance of the method, an experiment was done feature extraction using STFT and waveform information extraction using PCM data. As a result, we could know that the method to propose is effective more.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1309-1312
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• 1993

We present a flexible retrieval system of face photographs based on their linguistic descriptions in terms of fuzzy perdicates. While natural for describing a face, linguistic expressions are also subjective, which affects the retrieval result. Thus, the capability of a retrieval system to adjust to different users becomes very important. In this research we use fuzzy logic techniques, for describing image data, inference for retrieval and adjustment to a new user. Experimental results of the adjustment are also included.

• Journal of KIISE:Databases
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• v.30 no.3
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• pp.237-251
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• 2003

In this paper, we propose a video retrieval system to search logical structure and semantic contents of video data efficiently. The proposed system employs a layered modelling method that orBanifes video data in raw data layer, content layer and key frame layer. The layered modelling of the proposed system represents logical structures and semantic contents of video data in content layer. Also, the proposed system supports various types of searches such as text search, visual feature based similarity search, spatio-temporal relationship based similarity search and semantic contents search.

• Journal of the Semiconductor & Display Technology
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• v.7 no.2
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• pp.69-76
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• 2008

Recently, as the multimedia processing application increases rapidly by going on increasing multimedia data, the efficient retrieval method of image information is required in many fields of application and becoming the matter of major concern. Furthermore, in the last few years rapid improvements in hardware technology have made it possible to process, store and retrieve huge amounts of data in a multimedia format. As a result, Content-Based Image Retrieval (CBIR) has been receiving widespread interest during the last decade. This paper propose the content-based retrieval system as a method for performing image retrieval through the effective feature analysis of the object of significant meaning by using YCbCr channel merging on the basis of the characteristics of man's visual system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.450-470
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• 2023

Traditional cloud computing faces some challenges such as huge energy consumption, network delay and single point of failure. Edge computing is a typical distributed processing platform which includes multiple edge servers closer to the users, thus is more robust and can provide real-time computing services. Although outsourcing data to edge servers can bring great convenience, it also brings serious security threats. In order to provide image retrieval while ensuring users' data privacy, a privacy preserving image retrieval scheme in edge environment is proposed. Considering the distributed characteristics of edge computing environment and the requirement for lightweight computing, we present a privacy-preserving image retrieval scheme in edge computing environment, which two or more "honest but curious" servers retrieve the image quickly and accurately without divulging the image content. Compared with other traditional schemes, the scheme consumes less computing resources and has higher computing efficiency, which is more suitable for resource-constrained edge computing environment. Experimental results show the algorithm has high security, retrieval accuracy and efficiency.

• The Transactions of the Korea Information Processing Society
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• v.6 no.8
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• pp.2031-2041
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• 1999

In this paper, we present the HVIS (Hybrid Video Information System) which bolsters up meaning retrieval of all the various users by integrating feature-based retrieval and annotation-based retrieval of unformatted formed and massive video data. HVIS divides a set of video into video document, sequence, scene and object to model the metadata and suggests the Two layered Hybrid Object-oriented Metadata Model(THOMM) which is composed of raw-data layer for physical video stream, metadata layer to support annotation-based retrieval, content-based retrieval, and similarity retrieval. Grounded on this model, we presents the video query language which make the annotation-based query, content-based query and similar query possible and Video Query Processor to process the query and query processing algorithm. Specially, We present the similarity expression to appear degree of similarity which considers interesting of user. The proposed system is implemented with Visual C++, ActiveX and ORACLE.

• 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.

• Proceedings of the IEEK Conference
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• 2000.11c
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• pp.129-132
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• 2000

In this paper, a multimedia database retrieval system is proposed using MPEG-7 meta data. Multimedia content based retrieval system is implemented with the MPEG-7 meta data extraction and matching technique. MPEG-7 descriptors and descriptor schemes are stored into the database with other meta data. When a query image is given, the descriptors and descriptor schemes of the query image are extracted and compared with the descriptors and descriptor schemes in the database. Finally, images having more similarity are retrieved.

• 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.

• KIISE Transactions on Computing Practices
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• v.21 no.1
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• pp.58-63
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• 2015

In this work, we present a novel fountain code-based hybrid P2P storage system that combines cloud storage with P2P storage. The proposed hybrid storage system minimizes data transmission time while guaranteeing high data retrieval and data privacy. In order to guarantee data privacy and storage efficiency, the user transmits encoded data after performing fountain code-based encoding. Also, the proposed algorithm guarantees the user's data retrieval by storing the data while considering each peer's survival probability. The simulation results show that the proposed algorithm enables fast completion of the upload transmission while satisfying the required data retrieval and supporting the privacy of user data under the system parameters.