• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.669-672
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• 2001

We propose an efficient algorithm for an interactive content-based image retrieval using relevance feedback. In the proposed algorithm, a new query feature vector first is yielded from the average feature vector of the relevant images that is fed back from the result images of the previous retrieval. Each component weight of a feature vector is computed from an inverse of standard deviation for each component of the relevant images. The updated feature vector of the query and the component weights are used in the iterative retrieval process. In addition, the irrelevant images are excluded from object images in the next iteration to obtain additional performance improvement. In order to evaluate the retrieval performance of the proposed method, we experiment for three image databases, that is, Corel, Vistex, and Ultra databases. We have chosen wavelet moments, BDIP and BVLC, and MFS as features representing the visual content of an image. The experimental results show that the proposed method yields large precision improvement.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.8
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• pp.1176-1189
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• 1993

This paper presents the Multiple Keyword Retrieval Method under the Object-Oriented Multimedia Database Model. The multiple keyword registration and retrieval algorithms are developed to reduce the partial matching problem in multimedia data retrieval. For this, proper storage structures of the lookup tables are designed. And also, in order to maintain the constant retrieval time, media data files are organized with B+ tree structure.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.3
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• pp.59-65
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• 2004

This paper explores an image segmentation and representation method using Vector Quantization(VQ) on color and texture for content-based image retrieval system. The basic idea is a transformation from the raw pixel data to a small set of image regions which are coherent in color and texture space. These schemes are used for object-based image retrieval. Features for image retrieval are three color features from HSV color model and five texture features from Gray-level co-occurrence matrices. Once the feature extraction scheme is performed in the image, 8-dimensional feature vectors represent each pixel in the image. VQ algorithm is used to cluster each pixel data into groups. A representative feature table based on the dominant groups is obtained and used to retrieve similar images according to object within the image. The proposed method can retrieve similar images even in the case that the objects are translated, scaled, and rotated.

• Journal of Korean Library and Information Science Society
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• v.40 no.2
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• pp.139-159
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• 2009

This study is to develop knowledge base system for query extension to the user oriented information retrieval. This study has survey the theories of the concept-based information retrieval method and statistic based information retrieval method. In the construction method of knowledge base, the common hypothesis is that the emergence of related term is the frequency of simultaneous emergence of a set of documents. Using the subject index file algorithms and the 'and' operator of boolean logic based on this hypothesis, this study builds the knowledge base. In this research experiment, a subject of knowledge base is education. Using the book of the Introduction to Education, two experimental knowledge base systems is constructed by the different indexing method. One system has constructed by controlled language indexing method, and another system has constructed by natural language indexing method. The performance of two knowledge base system is evaluated.

• The Transactions of the Korea Information Processing Society
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• v.6 no.6
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• pp.1458-1467
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• 1999

Existing index structures such as extendable hashing and B+-tree do not support partial string searches perfectly. The inverted file method and the signature file method that are used in the web retrieval engine also have problems that they do not provide partial string searches and suffer from serious retrieval performance degradation respectively. In this paper, we propose an efficient index method that supports partial string searches and achieves good retrieval performance. The proposed index method is based on the Inverted file structure. It constructs the index file with patterns that result from dividing terms by two syllables to support partial string searches. We analyze the characteristics of our proposed method through simulation experiments using wide range of parameter values. We analyze the derive analytic performance evaluation models of the existing inverted file method, signature file method and the proposed index method in terms of retrieval time and storage overhead. We show through performance comparison based on analytic models that the proposed method significantly improves retrieval performance over the existing method.

• Journal of Korea Society of Industrial Information Systems
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• v.8 no.3
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• pp.61-68
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• 2003

In this paper, a representation method for structure information retrieval without schema and DTD of XML documents is presented. While existing researches have used DTD or schema to extract structure information, we extract structure information directly from XML documents. Especially the well-formed XML documents are only required to retrieve documents in the proposed method. Thus it can retrieve more general and various documents easily compared to the existing XML retrieval systems requiring DTD or schema. Experimental result indicates that the proposed method retrieves effectively structure information of XML documents independently to DTD information.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.3
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• pp.379-384
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• 2006

The paper describes a method of user feedback in order to enhance the retrieval effectiveness. In this paper, to overcome a weak point of the existing feedback function adapting fuzzy technique, we proposed the interaction function using gaussian function that gives different learning rate according to choice of components with same function. And, we grade degree that the user opinion is reflected to a system by applying user profile to the feedback function. User retrieval feedback method is adaptive retrieval method that makes a slow change for a long time using feedback function adapting gaussian function and user profile.

• Journal of the Optical Society of Korea
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• v.12 no.3
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• pp.186-191
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• 2008

A phase retrieval method using an error reduction algorithm is developed for reconstructing a wavefront aberration of an 100-TW Ti:sapphire laser pulse from the measurement of a focal spot. The phase retrieval method can successfully reconstruct a wavefront aberration of a 100-TW Ti:sapphire laser pulse, and the reconstructed wavefront aberration shows a good agreement with the wavefront aberration measured with a wavefront sensor. The effect of the dynamic range and the intensity noise on the reconstruction is also investigated in reconstructing a wavefront aberration of an 100-TW Ti:sapphire laser pulse.

• Journal of the Semiconductor & Display Technology
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• v.7 no.4
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• pp.57-62
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• 2008

Image retrieval is one of the most exciting and rapidly growing research issues in the field of multimedia technology. This paper proposes a new method that performs search the relevant images by using query-by-example. The proposed method for search and retrieval of images utilizes the location information where the image had been taken. The system associates the photo images with their corresponding GPS coordinates that are used as metadata for searching. Experimental results show that the proposed method demonstrates better performance improving up to 59% of average recall and 49% of average precision. Moreover, we learned from the experimental results geo-location information embedded within the image header is more effective and positive on the search and storage.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.9 no.2
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• pp.73-79
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• 2010

The most popular technique for image retrieval in a heterogeneous collection of color images is the comparison of images based on their color histogram. The color histogram describes the distribution of colors in the color space of a color image. In the most image retrieval systems, the color histogram is used to compute similarities between the query image and all the images in a database. But, small changes in the resolution, scaling, and illumination may cause important modifications of the color histogram, and so two color images may be considered to be very different from each other even though they have completely related semantics. A new method of color feature representation based on the 3-dimensional RGB color map is proposed to improve the defects of the color histogram. The proposed method is based on the three 2-dimensional projection map evaluated by projecting the RGB color space on the RG, GB, and BR surfaces. The experimental results reveal that the proposed is less sensitive to small changes in the scene and that achieve higher retrieval performances than the traditional color histogram.