• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.2
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• pp.1-8
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• 2003

This paper proposes an object-based image retrieval technique based on the dominant color pair information. Most of existing methods for content based retrieval extract the features from an image as a whole, instead of an object of interest. As a result, the retrieval performance tends to degrade due to the background colors. This paper proposes an object based retrieval scheme, in which an object of interest is used as a query and the similarity is measured on candidate regions of DB images where the object may exist. From the segmented image, the dominant color pair information between adjacent regions is used for selecting candidate regions. The similarity between the query image and DB image is measured by using the color correlogram technique. The dominant color pair information is robust against translation, rotation, and scaling. Experimental results show that the performance of the proposed method has been improved by reducing the errors caused by background colors.

• The KIPS Transactions:PartB
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• v.11B no.2
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• pp.233-240
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• 2004

This paper presents a method to implicitly resolve ambiguities using dynamic incremental clustering in Korean-to-English and Japanese-to-English cross-language information retrieval (CLIR). The main objective of this paper shows that document clusters can effectively resolve the ambiguities tremendously increased in translated queries as well as take into account the context of all the terms in a document. In the framework we propose, a query in Korean/Japanese is first translated into English by looking up bilingual dictionaries, then documents are retrieved for the translated query terms based on the vector space retrieval model or the probabilistic retrieval model. For the top-ranked retrieved documents, query-oriented document clusters are incrementally created and the weight of each retrieved document is re-calculated by using the clusters. In the experiment based on TREC test collection, our method achieved 39.41% and 36.79% improvement for translated queries without ambiguity resolution in Korean-to-English CLIR, and 17.89% and 30.46% improvements in Japanese-to-English CLIR, on the vector space retrieval and on the probabilistic retrieval, respectively. Our method achieved 12.30% improvements for all translation queries, compared with blind feedback in Korean-to-English CLIR. These results indicate that cluster analysis help to resolve ambiguity.

• Journal of Internet Computing and Services
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• v.1 no.2
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• pp.49-59
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• 2000

The majority of work done to date on natural language processing has focused on analysis and understanding of language, thus natural language generation had been relatively less attention than understanding, And people even tends to regard natural language generation CIS a simple reverse process of language understanding, However, need for natural language generation is growing rapidly as application systems, especially multi-language machine translation systems on the web, natural language interface systems, natural language query systems need more complex messages to generate, In this paper, we propose an algorithm to generate more flexible and natural sentence using lexical functions of Igor Mel'uk (Mel'uk ＆ Zholkovsky, 1988) and systemic grammar.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.575-578
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• 2005

Topographical images, in case of aerial or satellite images, are usually similar in colors and textures, and complex in shapes. Thus we have to use shape features of images for efficiently retrieving a query image from topographical image databases. In this paper, we propose a shape feature extraction method which is suitable for topographical images. This method, which improves the existing projection in the Cartesian coordinates, performs the projection operation in the polar coordinates. This method extracts three attributes, namely the number of region pixels, the boundary pixel length of the region from the centroid, the number of alternations between region and background, along each angular direction of the polar coordinates. It extracts the features of complex shape objects which may have holes and disconnected regions. An advantage of our method is that it is invariant to rotation/scale/translation of images. Finally we show the advantages of our method through experiments by comparing it with CSS which is one of the most successful methods in the area of shape feature extraction

• The KIPS Transactions:PartB
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• v.12B no.1 s.97
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• pp.31-38
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• 2005

This paper proposes an object-based image retrieval scheme using color adjacency and clustering method. Color adjacency features in boundary regions are utilized to extract candidate blocks of interest from image database and a clustering method is used to extract the regions of interest(ROI) from candidate blocks of interest. To measure the similarity between the query and database images, the histogram intersection technique is used. The color pair information used in the proposed method is robust against translation, rotation, and scaling. Consequently, experimental results have shown that the proposed scheme is superior to existing methods in terms of ANMRR.

• Journal of Broadcast Engineering
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• v.2 no.1
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• pp.74-83
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• 1997

We have proposed a composite feature measure which combines the color and shape features of an image for image retrieval. We improved the performance of retrieval based on the efficient color quantization using the Lloyd-Max quanizer and on the Histogram matrix matching method which considers the spatial correlation of quantized color group. We also supplemented the color information using shape information with the Improved Moment Invarlants. We have tested our technique on Image database consisting of 200 actual trademark images. Our experimental results showed that our approach improved the performance compared to the previous method under the various situations such as rotation images, translation images, noise added images, gamma corrected images and so on. The efficiency of retrieval is found to be very high and experimental results are

• Journal of Korea Society of Industrial Information Systems
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• v.6 no.1
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• pp.33-38
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• 2001

In this paper, we present an image retrieval system using shape features. The preprocessing to gain shape feature includes edge extraction using chain code. The shape features consist of center of mass, standard deviation, ratio of major axis and minor axis length. The similarity is estimated as comparing the features of query image with the features of images in database. Thus, the candidates of images are retrieved according to the order of similarity. The result of an experimentation is dullness for scale, rotation and translation. We evaluate the performance of shape features for image retrieval on a database with over 170 images. The Recall and the Precision is each 0.72 and 0.83 in the result of average experiment. So the proposed method is presented useful method.

• Annual Conference on Human and Language Technology
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• 1999.10e
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• pp.55-62
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• 1999

교차언어 문서검색에서는 단일언어 문서 상황을 만들기 위하여 질의나 문서를 다른 언어로 변환하게 되는데, 일반적으로 간단하면서도 실용적인 질의 변환의 방법을 주로 사용하고 있다. 하지만 단순한 대역 사전을 사용한 질의 변환의 경우에 변환 모호성 때문에 40% 이상의 검색 효과의 감소를 가져온다. 본 논문에서는 이러한 변환 모호성을 해결하기 위하여 대역 코퍼스로부터 추출한 상호 정보를 이용하는 단순하지만 효과적인 사전 기반 질의 변환 방법을 제안한다. 본 연구에서는 변환 모호성으로 발생한 다수의 후보들에서 가장 좋은 후보를 선택하는 모호성 해소 뿐 아니라 후보 단어들에 적절히 가중치를 부여하는 방법을 사용한다. 본 질의 변환 방법은 단순히 가장 큰 상호 정보의 단어를 선택하여 모호성 해소만을 적용하는 방법과 Krushall의 최소 스패닝 트리 구성과 유사한 방법으로 상호 정보가 큰 순서대로 간선들을 연결하여 모호성 해소와 가중치 부여를 적용하는 방법들과 질의 변환의 검색 효과를 비교한다. 본 질의 변환 방법은 TREC-6 교차언어 문서검색 환경의 실험에서 단일 언어 문서검색의 경우의 85%, 수작업 모호성 해소의 경우의 96%에 도달하는 성능을 얻었다.

• Annual Conference on Human and Language Technology
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• 2015.10a
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• pp.35-40
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• 2015

본 논문은 영어-한국어 교차언어 정보검색의 질의어 번역에 대한 중요한 자원으로 활용되는 병렬 말뭉치의 품질 향상을 위해서, 위키피디아의 비교 말뭉치로부터 자동으로 병렬 문장을 추출하여 활용하는 기법을 제안한다. 기존 연구에서 질의어 번역을 위해 위키피디아의 이중 어휘 사전 및 동의어, 다의어 정보를 구축하고, 기 기축된 병렬 말뭉치와 함께 활용하여 여러 의미를 가진 번역 후보 단어들 중, 최적의 단어를 선택하는 방법을 이용하고 있다. 여기서 활용되는 병렬 말뭉치는 질의어 번역에서 가장 중요한 자원이다. 하지만, 기 구축된 병렬 말뭉치는 양이 적거나, 특정 영역을 중심으로 구성되어 있는 문제가 있다. 이러한 문제를 해결하기 위해, 본 논문은 위키피디아로부터 자동 병렬 문장 추출 기법을 이용, 대량의 영어-한국어 간 병렬 말뭉치를 구축하고, 이를 교차언어 정보검색을 위한 질의어 번역에 적용하여 개선을 보인다. 실험의 성능 비교를 위해서 NTCIR-5 데이터를 이용하였으며 기 구축된 세종 병렬 말뭉치를 활용한 질의어 번역의 성능이 MAP 31.5%, R-P 33.0%에서, 새롭게 구축한 위키피디아 병렬 말뭉치를 활용한 질의어 번역의 성능이 MAP 34.6%, R-P 34.6%로, 각각 MAP 3.1%와 R-P 1.6%의 성능 향상을 보였다.

• Proceedings of the KAIS Fall Conference
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• 2006.11a
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• pp.290-293
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• 2006

The goal of research is to propose a framework for drawing data search system which is based on the web. The existing search systems were reviewed in the form of case studies and thereby the limitation were addressed: the unsystematic translation between the presentational building model and the discursive design criteria. besides the limited area in sharing and space. Therefore, a web-based drawing search with common structure which building representational model and building behavior model is proposed. The system contains a number of phases: firstly, a user is required to build a building model with the proposed building representational model and then this model is automatically transformed into an aspect model; secondly, a user is also required to present his query in form of the propose building behavior model by web page; finally, these two models - building representational model and building behavior model - are compared by database data so as to retrieve the proper result.