• Journal of KIISE:Software and Applications
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• v.34 no.1
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• pp.1-10
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• 2007

This paper proposes a new indexing mechanism for MPEG-7 visual descriptors, especially Dominant Color and Contour Shape descriptors, that guarantees an efficient similarity search for the multimedia database whose visual meta-data are represented with MPEG-7. Since the similarity metric used in the Dominant Color descriptor is based on Gaussian mixture model, the descriptor itself could be transform into a color histogram in which the distribution of the color values follows the Gauss distribution. Then, the transformed Dominant Color descriptor (i.e., the color histogram) is indexed in the proposed indexing mechanism. For the indexing of Contour Shape descriptor, we have used a two-pass algorithm. That is, in the first pass, since the similarity of two shapes could be roughly measured with the global parameters such as eccentricity and circularity used in Contour shape descriptor, the dissimilar image objects could be excluded with these global parameters first. Then, the similarities between the query and remaining image objects are measured with the peak parameters of Contour Shape descriptor. This two-pass approach helps to reduce the computational resources to measure the similarity of image objects using Contour Shape descriptor. This paper also proposes two integration schemes of visual descriptors for an efficient retrieval of multimedia database. The one is to use the weight of descriptor as a yardstick to determine the number of selected similar image objects with respect to that descriptor, and the other is to use the weight as the degree of importance of the descriptor in the global similarity measurement. Experimental results show that the proposed indexing and integration schemes produce a remarkable speed-up comparing to the exact similarity search, although there are some losses in the accuracy because of the approximated computation in indexing. The proposed schemes could be used to build a multimedia database represented in MPEG-7 that guarantees an efficient retrieval.

• The Transactions of the Korea Information Processing Society
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• v.7 no.5
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• pp.1570-1578
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• 2000

Object motion is an important feature of content in video sequences. By now, various methods to exact feature about the object motion have been reported[1,2]. However they are not suitable to index video using the motion, since a lot of bits and complex indexing parameters are needed for the indexing [3,4] In this paper, we propose object motion map which could provide efficient indexing method for object motion. The proposed object motion map has both global and local motion information during an object is moving. Furthermore, it requires small bit of memory for the indexing. to evaluate performance of proposed indexing technique, experiments are performed with video database consisting of MPEG-1 video sequence in MPEG-7 test set.

• The KIPS Transactions:PartB
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• v.11B no.5
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• pp.587-596
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• 2004

During recent years, a new framework, which aims to bring a unified and global approach in indexing, browsing and querying various digital multimedia data such as audio, video and image has been developed. This new system partitions each media stream into smaller units based on actual physical events. These physical events within oath media stream can then be effectively indexed for retrieval. In this paper, we present a new approach that exploits audio, image and video features to segment and analyze the audio-visual data. Integration of audio and visual analysis can overcome the weakness of previous approach that was based on the image or video analysis only. We Implement a web-based multi media data retrieval system called XCRAB and report on its experiment result.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05c
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• pp.1543-1546
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• 2003

최근에는 GPS(Global Positioning System)와 무선 데이터 전송 능력이 있는 휴대용 전화기의 보급 및 이동/무선 컴퓨팅 기술의 발달로 인해 이를 이용한 응용 서비스에 대한 관심이 고조되고 있다. 특히, 이동 차량, PDA, 휴대용 전화기, 노트북 컴퓨터 등을 이용한 위치기반서비스(LBS: Location Based Services)가 무선 인터넷 시장의 중요한 이슈가 되고 있다. 위치 정보를 기반으로 다양한 위치기반서비스를 제공할 수 있는 플랫폼은 향후 무선 인터넷 응용의 핵심기술이므로, 모바일 환경에서는 이러한 이동 객체들의 위치정보를 효과적으로 관리할 수 있어야 한다. 따라서 이 논문에서는 현재 모바일 환경에서 위치기반서비스 관리 및 제공과정에서 얻어지는 데이터 형태를 살펴보고, 기존의 이동 객체 색인들을 이용하여 실세계에서 얻어지는 데이터를 처리하였을 때의 문제점들을 검토한다. 피리고 이러한 문제를 해결할 수 있는 색인방법으로 동일한 시공간 정보를 갖는 이동 객체들을 블록단위로 저장하는 색인 구조를 제시함으로써 전체 색인 크기를 줄여 중복검색을 해결하고 디스크 I/O수를 줄이도록 설계한다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.4
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• pp.29-34
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• 2000

This paper presents a new indexing technique, for the fast content-based image browsing and retrieval in a database. By applying the rosette pattern that has more sample lines in the vicinity of center than those m the outer parts, we can get global gray distribution features as well as local positional information. These features are transformed into histogram and used as database indices. From the simulation results, the proposed method clearly shows the validity and the efficiency in respect of memory space as well as a good retrieval performance.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.4
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• pp.333-337
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• 2002

A content-based image retrieval method using color, texture, and shape features is proposed in this paper. A region segmentation technique using PIM(Picture Information Measure) entropy is used for similarity indexing. For segmentation, a color image is first transformed to a gray image and it is divided into n$\times$n non-overlapping blocks. Entropy using PIM is obtained from each block. Adequate variance to perform good segmentation of images in the database is obtained heuristically. As variance increases up to some bound, objects within the image can be easily segmented from the background. Therefore, variance is a good indication for adequate image segmentation. For high variance image, the image is segmented into two regions-high and low entropy regions. In high entropy region, hue-saturation-intensity and canny edge histograms are used for image similarity calculation. For image having lower variance is well represented by global texture information. Experiments show that the proposed method displayed similar images at the average of 4th rank for top-10 retrieval case.

• Journal of Korean Institute of Industrial Engineers
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• v.26 no.4
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• pp.363-375
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• 2000

In this paper we propose a content-based image retrieval method that can search large image databases efficiently by color, texture, and shape content. Quantized RGB histograms and the dominant triple (hue, saturation, and value), which are extracted from quantized HSV joint histogram in the local image region, are used for representing global/local color information in the image. Entropy and maximum entry from co-occurrence matrices are used for texture information and edge angle histogram is used for representing shape information. Relevance feedback approach, which has coupled proposed features, is used for obtaining better retrieval accuracy. Simulation results illustrate the above method provides 77.5 percent precision rate without relevance feedback and increased precision rate using relevance feedback for overall queries. We also present a new indexing method that supports fast retrieval in large image databases. Tree structures constructed by k-means algorithm, along with the idea of triangle inequality, eliminate candidate images for similarity calculation between query image and each database image. We find that the proposed method reduces calculation up to average 92.9 percent of the images from direct comparison.

• Journal of KIISE:Databases
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• v.30 no.2
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• pp.125-133
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• 2003

In this paper we propose an efficient content-based image retrieval method using the color and wavelet based texture features. The color features are obtained from soft-color histograms of the global image and the wavelet-based texture features are obtained from the invariant moments of the high-pass sub-band through the spatial-frequency analysis of the wavelet transform. The proposed system, called a color and texture based two-step retrieval(CTBTR), is composed of two-step query operations for an efficient image retrieval. In the first-step matching operation, the color histogram features are used to filter out the dissimilar images quickly from a large image database. The second-step matching operation applies the wavelet based texture features to the retained set of images to retrieve all relevant images successfully. The experimental results show that the proposed algorithm yields more improved retrieval accuracy with computationally efficiency than the previous methods.

• Journal of Korean Medical Science
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• v.33 no.48
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• pp.305.1-305.5
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• 2018

Background: In 1997 the Korean Association of Medical Journal Editors (KAMJE) instituted a program to evaluate member journals. Journals that passed the initial evaluation were indexed in the KoreaMed. Here, we report changes in measures of quality of the KAMJE member journals during the last 20 years. Methods: Quality measures used in the study comprised 3 assessment categories; self-assessment by journal editors, assessment of the journals by KAMJE reviewers, and by Korean health science librarians. Each used detailed criteria to score the journals on a scale of 0 to 5 or 6 in multiple dimensions. We compared scores at baseline evaluation and those after 7 years for 129 journals and compared improvements in journals indexed vs. not-indexed by the Web of Science (Science Citation Index Expanded; SCIE). Results: Among 251 KAMJE member journals at the end of 2015, 227 passed evaluation criteria and 129 (56%) had both baseline and 7-year follow-up assessment data. The journals showed improvement overall (increase in median [interquartile range; IQR] score from baseline, 0.47 [0.64]; 95% confidence interval [CI], 0.44-0.61; P < 0.001) and within each category (median [IQR] increase by editor's assessment, 0.17 [0.83]; 95% CI, 0.04-0.26; P = 0.007; by reviewer's, 0.45 [1.00]; 95% CI, 0.29-0.57; P < 0.001; by librarian's, 1.75 [1.08]; 95% CI, 1.77-2.18, P < 0.001). Before the foundation of KAMJE in 1996, there were only 5 Korean medical journals indexed in the MEDLINE and none in SCIE, but 24 journals in the MEDLINE and 34 journals in SCIE were indexed by 2016. Conclusion: The KAMJE journal evaluation program successfully contributes improving the quality of the member journals.