• Journal of Korea Multimedia Society
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• v.15 no.4
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• pp.526-539
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• 2012

This paper proposes a high capacity data hiding method using high frequence secret data indexing algorithm. Many novel data hiding methods based on LSB and PVD methods were presented to enlarge hiding capacity and provide an imperceptible quality. In this paper, first, calculating data iteration frequency of the secret message and make up the high frequency data index matrix (HFDT) using high frequence data's location information. Next, HFDT uses to that data hiding process on the cover image and recovering process on the stego image. The experimental results demonstrate the efficiency of the proposed high frequency secret data indexing method. For the data hiding method, experiments are conducted for four cases: 2 pattern secret data (2PD), 4 pattern secret data (4PD), 8 pattern secret data (8PD) and higher pattern secret data (HPD). When comparing the proposed method with other data hiding methods, for the HPD case, the results show that the proposed method has a good PSNR and more capacity, and for the other case, the results show that the proposed method has a higher PSNR and larger capacity.

• The KIPS Transactions:PartD
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• v.16D no.6
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• pp.845-850
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• 2009

Use of XML data has been increased with growth of Web 2.0 environment. XML is recognized its advantages by using based technology of RSS or ATOM for transferring information from blogs and news feed. Bitmap clustering is a method to keep index in main memory based on Relational DBMS, and which performed better than the other XML indexing methods during the evaluation. Existing method generates too many clusters, and it causes deterioration of result of searching quality. This paper proposes k-Bitmap clustering method that can generate user defined k clusters to solve above-mentioned problem. The proposed method also keeps additional inverted index for searching excluded terms from representative bits of k-Bitmap. We performed evaluation and the result shows that the users can control the number of clusters. Also our method has high recall value in single term search, and it guarantees the searching result includes all related documents for its query with keeping two indices.

• Journal of KIISE:Databases
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• v.34 no.5
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• pp.420-436
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• 2007

The choice of an effective indexing method is crucial to guarantee the performance of the spatial join operator which is heavily used in geographical information systems. The $R^*$-tree based method is renowned as one of the most representative indexing methods. In this paper, we propose an efficient spatial join technique based on the DOT(Double Transformation) index, and compare it with the spatial Join technique based on the $R^*$-tree index. The DOT index transforms the MBR of an spatial object into a single numeric value using a space filling curve, and builds the $B^+$-tree from a set of numeric values transformed as such. The DOT index is possible to be employed as a primary index for spatial objects. The proposed spatial join technique exploits the regularities in the moving patterns of space filling curves to divide a query region into a set of maximal sub-regions within which space filling curves traverse without interruption. Such division reduces the number of spatial transformations required to perform the spatial join and thus improves the performance of join processing. The experiments with the data sets of various distributions and sizes revealed that the proposed join technique is up to three times faster than the spatial join method based on the $R^*$-tree index.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.149-152
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• 2002

Automated video segmentation is important as the first step of video indexing, video retrieval and other uses. Unlike abrupt changes that are relatively easy to detect, gradual transitions like dissolve, fade-in and fade-out are rather difficult to detect. In this paper, we propose a method for detecting gradual transitions based on local statistics and less dependent to a given threshold level. Experimental results show that the proposed method detected about 85% of gradual transitions.

• The KIPS Transactions:PartD
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• v.13D no.7 s.110
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• pp.879-888
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• 2006

Recently many researchers have focused on management of Historical trajectories of moving objects in Euclidean spaces due to numerous sizes of accumulated data over time. However, the movement of moving objects in real applications generally has some constraints, for example vehicles on roads can only travel along connected road networks. In this paper, we propose an indexing method for trajectories of moving objects on road networks in order to process the network-based spatiotemporal range query. Our method contains the connect information of road networks to use the network distance for query processing, deals with trajectories which are represented by road segments in road networks, and manages them using multiple R-trees assigned per each road segment. Furthermore, it has a structure to be able to share R-tree among several road segments in large road networks. Consequently, we show that our method takes about 30% less in node accesses for the network-based spatiotemporal range query processing than other methods based on the Euclidean distance by experiments.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.14 no.2
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• pp.23-33
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• 2004

Because of a rapid growth of internet environment, it is also fast increasing to exchange message using e-mail. But, despite the convenience of e-mail, it is rising a currently bi9 issue to waste their time and cost due to the spam mail in an individual or enterprise. Many kinds of solutions have been studied to solve harmful effects of spam mail. Such typical methods are as follows; pattern matching using the keyword with representative method and method using the probability like Naive Bayesian. In this paper, we propose a classification method of spam mails from normal mails using Support Vector Machine, which has excellent performance in pattern classification problems, to compensate for the problems of existing research. Especially, the proposed method practices efficiently a teaming procedure with a word dictionary including a generated index by the n-Gram. In the conclusion, we verified the proposed method through the accuracy comparison of spm mail separation between an existing research and proposed scheme.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.2
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• pp.74-81
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• 2005

As the multimedia data increases, various scene change detection algorithms for video indexing and sequence matching have been proposed to efficiently manage and utilize digital media. In this paper, we propose a robust scene change detection algorithm for video sequences with abrupt luminance variations. To improve the accuracy and to reduce the computational complexity of video indexing with abrupt luminance variations, the proposed algorithm utilizes edge features as well as color features, which yields a remarkably better performance than conventional algorithms. In the proposed algorithm first we extract the candidate shot boundaries using color histograms and then determine using edge matching and luminance compensation if they are shot boundaries or luminance changes. If the scene contains trivial brightness variations, the edge matching and luminance compensation are performed only for shot boundaries. In experimental results, the proposed method gives remarkably a high performance and efficiency than the conventional methods with the similar computational complexity.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8649-8653
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• 2015

A number of video indexing and retrieval algorithms have been proposed to manage large video databases efficiently. The video similarity measure is one of most important technical factor for video content management system. In this paper, we propose the luminance characteristics model to measure the video similarity efficiently. Most algorithms for video indexing have been commonly used histograms, edges, or motion features, whereas in this paper, the proposed algorithm is employed an efficient similarity measure using the luminance projection. To index the video sequences effectively and to reduce the computational complexity, we calculate video similarity using the key frames extracted by the cumulative measure, and compare the set of key frames using the modified Hausdorff distance. Experimental results show that the proposed luminance projection model yields the remarkable improved accuracy and performance than the conventional algorithm such as the histogram comparison method, with the low computational complexity.

• Journal of Broadcast Engineering
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• v.21 no.3
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• pp.307-318
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• 2016

비디오 프레임 내의 오버레이 텍스트는 음성과 시각적 내용에 부가적인 정보를 제공한다. 특히, 뉴스 비디오에서 이 텍스트는 비디오 영상 내용을 압축적이고 직접적인 설명을 한다. 그러므로 뉴스 비디오 색인 시스템을 만드는데 있어서 가장 신뢰할 수 있는 실마리이다. 텔레비전 뉴스 프로그램의 색인 시스템을 만들기 위해서는 텍스트를 검출하고 인식하는 것이 중요하다. 이 논문은 뉴스 비디오에서 오버레이 텍스트를 검출하고 인식하는데 도움이 되는 오버레이 텍스트 시작 프레임 식별을 제안한다. 비디오 시퀀스의 모든 프레임이 오버레이 텍스트를 포함하는 것이 아니기 때문에, 모든 프레임에서 오버레이 텍스트의 추출은 불필요하고 시간 낭비다. 그러므로 오버레이 텍스트를 포함하고 있는 프레임에만 초점을 맞춤으로써 오버레이 텍스트 검출의 정확도를 개선할 수 있다. 텍스트 시작 프레임 식별 방법에 대한 비교 실험을 뉴스 비디오에 대해서 실시하고, 적절한 처리 방법을 제안한다.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.15 no.1
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• pp.23-41
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• 2004

In indexing and organizing Web resources, there have been two basic methods: automatic indexing by extracting key words and library classification schemes or subject directories of search engines. But, both methods have failed to satisfy the user's information needs, due to the lack of standard criteria and the irrationality of its structural system. In this paper I have examined the limits of library classification scheme's structures and the problems related to the nature of Web resources such as specificity and exhaustivity. I have also attempted to explain the logicality of Web resources organization by facet analysis and its strengths and limitations. In so doing, I have proposed three specific methods in using facet analysis: firstly, indexing system by facet analysis; secondly, the alternative transformation of the enumerative classification scheme into facet classification scheme; and finally, the facet model of subject directory of domestic search engine. After examining the three methods, my study concludes that a controlled vocabulary by facet analysis can be employed as a useful method in organizing Web resources.