• Proceedings of the Korean Information Science Society Conference
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• 2000.10b
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• pp.119-121
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• 2000

최근 급속히 발전하고 있는 컴퓨터 하드웨어 기술로 이미지, 오디오, 비디오 등의 방대한 멀티미디어 데이터가 비 선별적으로 일반 사용자에게 제공되어지고 있다. 하지만 상이한 해석이 가능한 멀티미디어 데이터의 특성상 정확한 데이터의 전달을 위해 각각의 사용자의 취향을 고려할 수 있는 지능 컴퓨팅 기술 즉, 개인화 모델의 이용이 필수적이다. 개인화 모델의 구축을 위해서는 사용자의 피드백 정보를 필요로 하게 되는데, 현재까지의 연구는 결과에 대한 만족정도를 사용자가 일일이 조사해야 하는 부담 때문에 사용자에게는 일반적인 환경에서 사용자의 묵시적인 피드백 정보를 이용하는 기술 개발의 필요성이 강조되고 있다. 본 논문에서는 묵시적으로 사용자의 시각 정보 및 행위 정보를 이용하여 사용자의 부담을 줄이는 동시에 적응 및 학습 능력을 갖는 지능 사용자 인터페이스를 적용한 내용기반 이미지 검색 시스템을 구현하였다.

• Journal of KIISE:Software and Applications
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• v.31 no.10
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• pp.1332-1344
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• 2004

Upon development of information super-highway and multimedia-related technoiogies in recent years, more efficient technologies to transmit, store and retrieve the multimedia data are required. Among such technologies, firstly, it is common that the semantic-based image retrieval is annotated separately in order to give certain meanings to the image data and the low-level property information that include information about color, texture, and shape Despite the fact that the semantic-based information retrieval has been made by utilizing such vocabulary dictionary as the key words that given, however it brings about a problem that has not yet freed from the limit of the existing keyword-based text information retrieval. The second problem is that it reveals a decreased retrieval performance in the content-based image retrieval system, and is difficult to separate the object from the image that has complex background, and also is difficult to extract an area due to excessive division of those regions. Further, it is difficult to separate the objects from the image that possesses multiple objects in complex scene. To solve the problems, in this paper, I established a content-based retrieval system that can be processed in 5 different steps. The most critical process of those 5 steps is that among RGB images, the one that has the largest and the smallest background are to be extracted. Particularly. I propose the method that extracts the subject as well as the background by using an Image, which has the largest background. Also, to solve the second problem, I propose the method in which multiple objects are separated using RGB channel selection techniques having optimized the excessive division of area by utilizing Watermerge's threshold value with the object separation using the method of RGB channels separation. The tests proved that the methods proposed by me were superior to the existing methods in terms of retrieval performances insomuch as to replace those methods that developed for the purpose of retrieving those complex objects that used to be difficult to retrieve up until now.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.1
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• pp.1-11
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• 2001

본 논문에서는 관계형 데이타베이스인 오라클과 IRS중 하나인 BRS를 사용하여 XML 저장관리 시스템을 설계 및 구현한다. XML저장관리 시스템의 내용 검색과 인덱스 추출을 위해 BRS 검색 시스템을 사용하였으며, XML 문서, 구조정보, DTD, 이미지 등을 저장하기 위해 오라클을 사용하였다. 본 논문에서 구현한 저장관리 시스템은 질의 처리기, 검색결과생성기, XML 객체관리자, XML 인덱스 관리자, 구조검색엔진 등으로 구성된다. 구현된 XML 저장관리 시스템은 XML 문서에 대한 내용검색뿐만 아니라 구조적 특징 또는 대트리뷰트에 기반한 검색을 효율적으로 제공한다. 구현한 저장관리 시스템은 문서 저장 시간, 문서 추출 시간, 내용 검색 시긴 등에 대해서 분할 모델 저장관리 시스템과 비교한다.

• Journal of KIISE:Databases
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• v.37 no.5
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• pp.228-237
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• 2010

Although conventional index structures provide various nearest-neighbor search algorithms for high-dimensional data, there are additional requirements to increase search performances as well as to support index scalability for large scale data. To support these requirements, we propose a distributed high-dimensional indexing structure based on cluster systems, called a Distributed Vector Approximation-tree (DVA-tree), which is a two-level structure consisting of a hybrid spill-tree and VA-files. We also describe the algorithms used for constructing the DVA-tree over multiple machines and performing distributed k-nearest neighbors (NN) searches. To evaluate the performance of the DVA-tree, we conduct an experimental study using both real and synthetic datasets. The results show that our proposed method contributes to significant performance advantages over existing index structures on difference kinds of datasets.

• Journal of KIISE:Software and Applications
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• v.31 no.2
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• pp.126-136
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• 2004

This paper proposes a new content-based image retrieval algorithm using color-spatial information. For the purpose, the paper suggests two kinds of indexing key to prune away irrelevant images to a given query image; MCS(Main Colors' Set), which is related with color information and DBS (Distribution Block Signature), which is related with spatial information. After successively applying these filters to a database, we could get a small amount of high potential candidates that are somewhat similar to the query image. Then we would make use of new QM(Quad modeling) and relevance feedback mechanism to obtain more accurate retrieval. It would enhance the retrieval effectiveness by dynamically modulating the weights of color-spatial information. Experiments show that the proposed algorithm can apply successfully image retrieval applications.

• The Journal of the Korea Contents Association
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• v.11 no.5
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• pp.125-137
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• 2011

Recently the research on the system using images taken from camera phones as input is actively conducted. This paper proposed a system that shows wine pictures which are similar to the input wine label in order. For the calculation of the similarity of images, the representative color of each cell of the image, the recognized text color, background color and distribution of feature points are used as the features. In order to calculate the difference of the colors, RGB is converted into CIE-Lab and the feature points are extracted by using Harris Corner Detection Algorithm. The weights of representative color of each cell of image, text color and background color are applied. The image similarity is calculated by normalizing the difference of color similarity and distribution of feature points. After calculating the similarity between the input image and the images in the database, the images in Database are shown in the descent order of the similarity so that the effort of users to search for similar wine labels again from the searched result is reduced.

• Annual Conference of KIPS
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• 2003.05c
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• pp.1659-1662
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• 2003

웹 환경에서 사용되고 있는 데이터의 종류는 텍스트뿐만 아니라 멀티미디어 데이터까지 다양하게 사용되어 지고 있다. 그러나 오디오, 이미지, 비디오와 같은 미디어 객체들은 2진화, 비구조화 되어 있으므로 기계 번역이 용이하지 않다. 이런 비정형화 된 비디오 데이터에 대한 검색을 효율적으로 처리하기 위해서는 비디오의 논리적 구조와 의미적 내용을 표현할 수 있어야 한다. 멀티미디어 데이터의 메타 데이터를 표현하기 위해서 XML 문서를 이용하여 표현하고, 표현된 문서를 효율적으로 검색 할 수 있도록 설계하였다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.1
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• pp.46-57
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• 2001

To access the multimedia data, such as video data with temporal properties, the content-based image retrieval technique is required. Moreover, one of the basic techniques for content-based image retrieval is an extraction of representative key-frames. Not only did we implement this method, but also by analyzing the video data, we have proven the proposed method to be both effective and accurate. In addition, this method is expected to solve the real world problem of building video databases, as it is very useful in building an index.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10a
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• pp.296-298
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• 1999

컬러 히스토그램은 멀티미디어 이미지 데이터의 특성을 표현하기 위하여 널이 이용되어 왔다. 그러나 컬러 히스토그램을 고차원으로 설정할 경우 색인 구조에 효율적이지 못할 뿐만 아니라 유사도 계산에서도 고비용이 요구된다. 이러한 단점을 보완하기 위해 히스트그램의 차원을 줄이는 여러 방법이 제시되어 왔으나 이미지의 색상정보 손실을 피할 수 없으며, 이미지의 전체 히스토그램으로는 이미지의 레이아웃을 고려할 수 없기 때문에 필터링을 통한 후보 선정 시 상이한 이미지가 선택되어지는 문제점을 지닌다. 본 논문에서는 이미지를 일정한 크기의 타일로 분할한 이미지 타일 평균 RGB 방법을 제안하였으며, 실험을 통하여 제안한 방법의 성능을 평가하였다.

• The KIPS Transactions:PartC
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• v.17C no.1
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• pp.27-36
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• 2010

In Web registration pages and online polling applications, CAPTCHA(Completely Automated Public Turing Test To Tell Computers and Human Apart) is used for distinguishing human users from automated programs. Text-based CAPTCHAs have been widely used in many popular Web sites in which distorted text is used. However, because the advanced optical character recognition techniques can recognize the distorted texts, the reliability becomes low. Image-based CAPTCHAs have been proposed to improve the reliability of the text-based CAPTCHAs. However, these systems also are known as having some drawbacks. First, some image-based CAPTCHA systems with small number of image files in their image dictionary is not so reliable since attacker can recognize images by repeated executions of machine learning programs. Second, users may feel uncomfortable since they have to try CAPTCHA tests repeatedly when they fail to input a correct keyword. Third, some image-base CAPTCHAs require high communication cost since they should send several image files for one CAPTCHA. To solve these problems of image-based CAPTCHA, this paper proposes a new CAPTCHA based on both image and text. In this system, an image and keywords are integrated into one CAPTCHA image to give user a hint for the answer keyword. The proposed CAPTCHA can help users to input easily the answer keyword with the hint in the fused image. Also, the proposed system can reduce the communication costs since it uses only a fused image file for one CAPTCHA. To improve the reliability of the image-text fusion CAPTCHA, we also propose a dynamic building method of large image dictionary from gathering huge amount of images from theinternet with filtering phase for preserving the correctness of CAPTCHA images. In this paper, we proved that the proposed image-text fusion CAPTCHA provides users more convenience and high reliability than the image-based CAPTCHA through experiments.