• Proceedings of the Korean Society for Information Management Conference
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• 2005.08a
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• pp.311-318
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• 2005

본 논문은 e-book으로 명명된 전자 원문자료(전자책)를 구조화하여 이용자 편의성을 극대화하는 방안을 연구하였다. 대상으로 특정 컨텐트(텍스트, 이미지, 아이콘 등)를 선택하는 경우 관련정보를 웹브라우저에 의해 웹사이트에서 제공할 수 있는 내용검색기반의 전자원문 고도화 방안 연구를 목적으로 하고 있다. 연구결과 전자원문 서비스체계, 전문정보(專門情報)의 분류체계 적용, 검색효율성 및 편리성을 증진시킨 인터페이스 등의 결과를 부품소재정보망(MCT-net)에 적용하였다. 또한 전자원문의 자동구축방안, 다양한 검색기능 강화방안, 효율적인 전자원문 관리방안을 모색하였다

• The KIPS Transactions:PartB
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• v.13B no.3 s.106
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• pp.309-314
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• 2006

Recently, multimedia DBMS is appeared to be the core technology of the information society to store, manage and retrieve multimedia data efficiently. In this paper, we propose a new method for content based-retrieval system using wavelet transform, energy value to extract automatically feature vector from image data, and suggest an effective retrieval technique through this method. Wavelet transform is widely used in image compression and digital signal analysis, and its coefficient values reflect image feature very well. The correlation in wavelet domain between query image data and the stored data in database is used to calculate similarity. In order to assess the image retrieval performance, a set of hundreds images are run. The method using standard derivation and mean value used for feature vector extraction are compared with that of our method based on energy value. For the simulation results, our energy value method was more effective than the one using standard derivation and mean value.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1563-1566
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• 2013

최근 네트워크와 멀티미디어 관련 기술의 발달로 이미지 및 동영상과 같은 대용량 멀티미디어 데이터가 증가하고 있다. 이에 따라 대용량의 데이터에서 영상 정보의 효율적인 검색 방법이 요구 되고 있다. 하지만 기존의 전통적인 색인기술은 관리자가 영상을 직접 보면서 적절한 텍스트 내용을 입력하는 방법으로 시간이 많이 소요되며, 관리자의 성향에 따라 색인어의 입력이 다를 수 있어 검색시 오류를 발생시킬 수 있다. 따라서 본 논문에서는 영상으로부터 컬러 특징과 질감 특징을 추출하여 보다 효율적으로 내용 기반 영상 검색을 수행하는 방법을 제안한다. 실험을 통하여 다른 기존의 영상 검색 방법보다 검색 효율성에서 안정적이며 보다 나은 결과를 얻음을 확인한다.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10a
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• pp.127-129
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• 2000

일반적인 색 정보추출방법으로 색 히스토그램(Color Histogram)은 색의 분포나 응집성, 질감에 대한 구분능력이 없다는 단점을 가지고 있어 정환한 이미지 유사성 비교를 위해 추가적인 정보를 요구한다. Androutsos등은 Haar Wavelet 변환을 통해 이미지의 방향성 질감정보를 구하였다[1]. 하지만 이 방법은 Haar Wavelet 변환의 특성으로 인해 정확한 방향성 정보를 얻을 수 없었다. 본 논문에서는 인접 픽셀(pixel)값의 편차(deviaiton)를 이용하여 방향성 정보를 추출 성능을 향상시키는 방법을 제안하였고, Brodatz 112 질감 이미지와 실재 자연사진을 통해 방향성 질감의 성능을 평가하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10b
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• pp.449-451
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• 2000

본 논문에서는 내용기반 이미지 검색 시스템을 제작하기 위하여 필수적으로 선행되어야 하는 이미지의 영역구분에 대한 새로운 방법인 경계값을 이용한 영역추출 방법을 소개한다. 빠르고 정확한 이미지 검색엔진을 구현하기 위하여 질의의 결과가 될 이미지들은 전처리기에 의하여 모든 영역을 추출한 뒤 각각의 영역에 따른 특성(feature)를 저장하고 있어야 한다. 정확한 질의 결과를 얻기 위하여는 정확히 영역을 추출할 수 있고 그 특성도 추출할 수 있는 전처리기를 사용하여야 한다. 또한 정확도만을 중시하여 너무 복잡한 알고리즘을 사용한다면 그 또한 실용적이지 못하게 된다. 경계값을 이용한 영역추출 방법은 이미지의 각 점에 대한 경계값(edge value)을 이용하여 그 경계값이 작은 점으로부터 시작하여 경계값이 큰 점들을 병합해 가면서 인접한 영역간의 크기, 색상 등을 고려하여 각각의 영역을 구분해 낸다. 이 방법의 가장 큰 특징은 텍스쳐(texture)를 제외한 일반적인 영역뿐 아니라 텍스쳐 포함하는 영역도 추출할 수 있는 점과 빠른 처리 속도에 있다.

• Journal of Digital Contents Society
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• v.12 no.4
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• pp.429-436
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• 2011

Various documents, images, videos and other materials on the web has been increasing rapidly. Efficient search of those things has become an important topic. From keyword-based search, internet search has been transformed to semantic search which finds the implications and the relations between data elements. Many annotation processing systems manipulating the metadata for semantic search have been proposed. However, annotation data generated by different methods and forms are difficult to process integrated search between those systems. In this study, in order to resolve this problem, we categorized levels of many annotation documents, and we proposed the method to measure the similarity between the annotation documents. Similarity measure between annotation documents can be used for searching similar or related documents, images, and videos regardless of the forms of the source data.

• Journal of the Korean Society for information Management
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• v.21 no.4 s.54
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• pp.187-208
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• 2004

In this study, aesthetic impressions were used for a high-level feature of image retrieval. The term, 'aesthetic' has been studied in psychology, art, and literature. It means unconscious, instantaneous parts of visual perception and emotion. The literatures related to aesthetic impressions were reviewed and four kinds of aesthetic impressions were defined operationally : strong impression, soft impression, courteous impression, and refined impression. 66 image files of paintings were sampled randomly from 1100 paintings and low-level color features were extracted from them by a using perceptual color model(Lai, & Tait, 1998). The high-level features of an image, that is, four kinds of aesthetic impressions of each painting were measured by 4 subjects and averaged. In CBIR, 2 subjects performed image retrievals using example queries. They were asked to retrieve images by using the aesthetic impressions or the keywords. In evaluations, subjects showed that they were satisfied with the aesthetic impression-based image retrieval system on the average. And R-precision of the image retrieval with both color features and aesthetic impressions was higher than that of the image retrieval with color features only. But further studies with larger test collections and query sets should be followed for generalization of the result of this study.

• Journal of IKEEE
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• v.14 no.4
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• pp.339-345
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• 2010

So far, many researches have been done to index high-dimensional feature values for fast content-based image retrieval. Still, many existing indexing schemes are suffering from performance degradation due to the curse of dimensionality problem. As an alternative, heuristic algorithms have been proposed to calculate the result with 'high probability' at the cost of accuracy. In this paper, we propose a new extendible hash-based indexing scheme for high-dimensional feature values. Our indexing scheme provides several advantages compared to the traditional high-dimensional index structures in terms of search performance and accuracy preservation. Through extensive experiments, we show that our proposed indexing scheme achieves outstanding performance.

• 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.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.3
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• pp.303-317
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• 2002

In this paper, we design and implement E-COIRS enabling users to query with concepts and image features used for further refining the concepts. For example, E-COIRS supports the query "retrieve images containing black home appliance to north of reception set. "The query includes two types of concepts: IS-A and composite. "home appliance"is an IS-A concept, and "reception set" is a composite concept. For evaluating such a query. E-COIRS includes three important components: a visual image indexer, thesauri and a query processor. Each pair of objects in an mage captured by the visual image indexer is converted into a triple. The triple consists of the two object identifiers (oids) and their spatial relationship. All the features of an object is referenced by its old. A composite concept is detected by the triple thesaurus and IS-A concept is recolonized by the fuzzy term thesaurus. The query processor obtains an image set by matching each triple in a user with an inverted file and CS-Tree. To support efficient storage use and fast retrieval on high-dimensional feature vectors, E-COIRS uses Cell-based Signature tree(CS-Tree). E-COIRS is a more advanced content-based image retrieval system than other systems which support only concepts or image features.