• Proceedings of the Korea Multimedia Society Conference
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• 2002.05c
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• pp.234-239
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• 2002

영상 검색의 수행 방법으로 사람의 시각 시스템의 특성을 기반으로 효과적인 특징 추출 통한 계층적인 내용 기반 검색 시스템을 제안한다. 영상 고유의 특징을 얻기 위해 영상내에 존재하는 형태 정보와 질감 방향성 및 칼라 정보를 이용한다. 본 논문에서는 형태 정보의 추출을 위하여 사용자의 질의 영상에서 에지 특징 정보를 추출하고 부분 영역으로 분할된 영상에서 GLCM(Gray Level Co-occurrence Matrix)의 Contrast를 질감 특징으로 추출한다. 이들 두 특징을 이용하여 1차 분류 과정을 거치고 2차 검사에서는 보다 정확한 검색을 수행하기 위하여 1차로 분류된 후보영상들에 대하여 영상의 세부 정보인 칼라 정보를 기반으로 유사도를 측정함으로써 유사한 칼라와 형태를 가지는 영상뿐만 아니라 칼라가 다른 유사한 영상에도 효율적인 검색 성능을 보였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.05a
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• pp.753-756
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• 2004

영상의 객체가 갖고 있는 중요도를 계산하는 것은 매우 주관적이기 때문에, 객체의 의미 정도를 판단하는 것은 매우 어려운 문제이다. 따라서 본 논문에서는 효율적인 내용기반 이미지 검색 시스템을 구축하기 위하여 원 영상에서 Wavelet 변환을 이용하여 RGB 이미지를 각각 분리 및 병합하는 방법을 제안한다. 또한, 각각의 RGB 이미지들 중 검색에 필요한 특징들을 추출하여 원 영상과 가장 근접한 이미지들을 찾아내는 방법을 제안한다. 제안한 세가지 특징 정보를 이용한 내용 기반 이미지 정보 검색은 기존 방법에 비해 높은 검색 성능을 보였으며, 사람 얼굴이나 캐릭터 이미지인 경우에는 더욱 효율적이라 예상된다

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.717-723
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• 2019

Smart systems and services aim to facilitate growing urban populations and their prospects of virtual-real social behaviors, gig economies, factory automation, knowledge-based workforce, integrated societies, modern living, among many more. To satisfy these objectives, smart systems and services must comprises of a complex set of features such as security, ease of use and user friendliness, manageability, scalability, adaptivity, intelligent behavior, and personalization. Recently, artificial intelligence (AI) is realized as a data-driven technology to provide an efficient knowledge representation, semantic modeling, and can support a cognitive behavior aspect of the system. In this paper, an integration of AI with the smart systems and services is presented to mitigate the existing challenges. Several novel researches work in terms of frameworks, architectures, paradigms, and algorithms are discussed to provide possible solutions against the existing challenges in the AI-based smart systems and services. Such novel research works involve efficient shape image retrieval, speech signal processing, dynamic thermal rating, advanced persistent threat tactics, user authentication, and so on.

• Current Optics and Photonics
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• v.5 no.1
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• pp.40-44
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• 2021

In this paper, LED arrays with segmented mirrors and a mask are presented as a new dark-field illuminator for reflective Fourier ptychographic microscopy (FPM). The illuminator can overcome the limitations of the size and the position of samples that the dark-field illuminator using a parabolic mirror has had. The new concept was demonstrated by measuring a USAF 1951 target, and it resolved a pattern in group 10 element 6 (274 nm) in the USAF target. The new design of the dark-field illuminator can enhance competitiveness of the reflective FPM as a versatile measurement method in industry.

• Journal of Information Processing Systems
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• v.17 no.6
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• pp.1138-1156
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• 2021

Emotional semantics are the highest level of semantics that can be extracted from an image. Constructing a system that can automatically recognize the emotional semantics from images will be significant for marketing, smart healthcare, and deep human-computer interaction. To understand the direction of image emotion recognition as well as the general research methods, we summarize the current development trends and shed light on potential future research. The primary contributions of this paper are as follows. We investigate the color, texture, shape and contour features used for emotional semantics extraction. We establish two models that map images into emotional space and introduce in detail the various processes in the image emotional semantic recognition framework. We also discuss important datasets and useful applications in the field such as garment image and image retrieval. We conclude with a brief discussion about future research trends.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.328-331
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• 2008

많은 양의 이미지를 포함하고 있는 대용량 데이터베이스에 대한 이미지 검색에서 보다 짧은 시간에 적은 양의 검색공간을 사용하면서 원하는 결과를 얻을 수 있는 이미지 인덱싱 기법에 대한 다양한 연구가 진행되어 왔다. 본 논문에서는 외형 기반의 이미지 검색에서 기존의 인덱싱 기법보다 빠른 검색을 지원할 수 있는 해시 기반의 새로운 인덱싱 기법을 제안한다. 기존의 해시 기반 인덱싱 기법에서는 해시 주소 계산을 위해 인덱스 값의 범위가 미리 정해져야 하기 때문에 색상 정보 등 소수의 특징 정보를 제외하고는 인덱싱에 널리 사용되지 못하고 있다. 한편, 제안된 해시 구조는 값의 범위가 정해지지 않은 정수형의 인덱스 값을 기반으로 효과적으로 이미지 인덱스를 구축할 수 있다. 효과적인 이미지 검색을 위해 제안된 인덱스를 기반한 범위검색(Range Search) 기법을 제안하였으며, 실험을 통해 제안된 인덱스 구조에서의 범위 검색이 기존의 인덱스 구조에 비해 보다 효과적임을 보인다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.1
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• pp.33-42
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• 2001

Recently, the interests in the 3D image, generated from the range data and CAD, have exceedingly increased, accordingly a various 3D image database is being constructed. The efficient and fast scheme to access the desired image data is the important issue in the application area of the Internet and digital library. However, it is difficult to manage the 3D image database because of its huge size. Therefore, a proper descriptor is necessary to manage the data efficiently, including the content-based search. In this paper, the proposed shape descriptor is based on the voxelization of the 3D image. The medial axis transform, stemming from the mathematical morphology, is performed on the voxelized 3D image and the graph, which is composed of node and edge, is generated from skeletons. The generated graph is adequate to the novel shape descriptor due to no loss of geometric information and the similarity of the insight of the human. Therefore the proposed shape descriptor would be useful for the recognition of 3D object, compression, and content-based search.

• Journal of Korea Multimedia Society
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• v.5 no.3
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• pp.281-289
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• 2002

Few studies have been systematically pursued on a multimedia data mining in despite of the over-whelming amounts of multimedia data by the development of computer capacity, storage technology and Internet. Based on the preliminary image processing and content-based image retrieval technology, this paper presents the methods for discovering association rules from recurrent items with spatial relationships in huge data repositories. Furthermore, multimedia mining algorithm is proposed to find implicit association rules among objects of which content-based descriptors such as color, texture, shape and etc. are recurrent and of which descriptors have spatial relationships. The algorithm with recurrent items in images shows high efficiency to find set of frequent items as compared to the Apriori algorithm. The multimedia association-rules algorithm is specially effective when the collection of images is homogeneous and it can be applied to many multimedia-related application fields.

• The Journal of Korean Institute for Practical Engineering Education
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• v.4 no.1
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• pp.80-85
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• 2012

The importance of warehouse is increasing since the role of warehouse in modern industry is changing from concept of storage to concept of circulation which facilitates purchasing, production, storage and distribution activities by induction of information system. In this study, a program is developed using C# for evaluating efficiency of automated storage and retrieval system(AS/RS). A simulation work is done for eight operating schemes under the combination of three conditions, which are storing method, the shape of automatic warehouse and the sequence of command performs, and the moving distance of stacker crane is calculated using the same gateway data. Using this program, the optimal operating scheme can be proposed based on the analyzed results of simulation. This progrm shows the effectiveness and applicability through the simulation work and can be utilized for courses which are related to factory facilities.

• The KIPS Transactions:PartD
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• v.9D no.1
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• pp.57-64
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• 2002

Few studies have been systematically pursued on a multimedia data mining in despite of the overwhelming amounts of multimedia data by the development of computer capacity, storage technology and Internet. Based on the preliminary image processing and content-based image retrieval technology, this paper presents the methods for discovering association rules from recurrent items with spatial relationships in huge data repositories. Furthermore, multimedia mining algorithm is proposed to find implicit association rules among objects of which content-based descriptors such as color, texture, shape and etc. are recurrent and of which descriptors have spatial relationships. The algorithm with recurrent items in images shows high efficiency to find set of frequent items as compared to the Apriori algorithm. The multimedia association-rules algorithm is specially effective when the collection of images is homogeneous and it can be applied to many multimedia-related application fields.