• Journal of the Korean Society for information Management
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• v.19 no.3
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• pp.123-143
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• 2002

Developing good methods for image description and indexing is fundamental for successful image retrieval, regardless of the content of images. Researchers and practitioners in the field of image indexing have developed a variety of image indexing systems and methods with the consideration of information types delivered by images. Such efforts in developing image indexing systems and methods include Panofsky's levels of image indexing and indexing systems adopting different approaches such as thesauri-based approach, classification approach. description element-based approach, and categorization approach. This study investigated users' perception of the objectiveness of image indexing, especially the iconographical analysis of image information advocated by Panofsky. One of the best examples of subjectiveness and conditional-dependence of image information is emotion. As a result, this study dealt with visual emotional information. Experiments were conducted in two phases : one was to measure the degree of agreement or disagreement about the emotional content of pictures among forty-eight participants and the other was to examine the inter-rater consistency defined as the degree of users' agreement on indexing. The results showed that the experiment participants made fairly subjective interpretation when they were viewing pictures. It was also found that the subjective interpretation made by the participants resulted from the individual differences in terms of their educational or cultural background. The study results emphasize the importance of developing new ways of indexing and/or searching for images, which can alleviate the limitations of access to images due to the subjective interpretation made by different users.

• 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.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.4
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• pp.99-124
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• 2015

As the improvement of digital technologies increases the use of images from various fields, the domain of image retrieval has evolved and become a growing topic of research in the Library and Information Science field. The purpose of this study is to identify the knowledge structure of the image retrieval domain by using the author co-citation analysis and author bibliographic coupling as analytical tools in order to understand the domain's past and present. The data set for this study is 245 articles with 8,031 cited articles in the field of image retrieval from 1998 to 2013, from the Web of Science citation database. According to the results of author co-citation analysis for the past of the image retrieval domain, our findings demonstrate that the intellectual structure of image retrieval in the LIS field consists of predominantly user-oriented approaches, but also includes some areas influenced by the CBIR area. More specifically, the user-oriented approach contains six specific areas which include image needs, information seeking, image needs and search behavior, image indexing and access, indexing of image collection, and web image search. On the other hand, for CBIR approaches, it contains feature-based image indexing, shape-based indexing, and IR & CBIR. The recent trends of image retrieval based on the results from author bibliographic coupling analysis show that the domain is expanding to emerging areas of medical images, multimedia, ontology- and tag-based indexing which thus reflects a new paradigm of information environment.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.810-813
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• 2004

Indexing and Retrieving images from large and varied collections using image content as a key is a challenging and important problem in computer vision application. In this paper, a color Content-based Image Retrieval (CBIR) system using hierarchical Region of Interest (ROI) query and indexing is presented. During indexing process, First, The ROIs on every image in the image database are extracted using a region-based image segmentation technique, The JSEG approach is selected to handle this problem in order to create color-texture regions. Then, Color features in form of histogram and correlogram are then extracted from each segmented regions. Finally, The features are stored in the database as the key to retrieve the relevant images. As in the retrieval system, users are allowed to select ROI directly over the sample or user's submission image and the query process then focuses on the content of the selected ROI in order to find those images containing similar regions from the database. The hierarchical region-of-interest query is performed to retrieve the similar images. Two-level search is exploited in this paper. In the first level, the most important regions, usually the large regions at the center of user's query, are used to retrieve images having similar regions using static search. This ensures that we can retrieve all the images having the most important regions. In the second level, all the remaining regions in user's query are used to search from all the retrieved images obtained from the first level. The experimental results using the indexing technique show good retrieval performance over a variety of image collections, also great reduction in the amount of searching time.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3001-3003
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• 1999

Color 이미지 데이터 베이스로부터 원하는 이미지를 찾아내는 방법으로 image indexing에 대한 많은 연구가 이루어지고 있다. 본 논문에서는 image indexing의 한 방법인 color indexing을 이용하여 이동 로봇의 위치 추정 문제를 해결하고자 한다. Color indexing은 영상의 color 분포를 분석하여 원하는 이미지를 찾아내는 기법으로 로봇은 사전에 저장되어 있는 주변 환경에 대한 모델 이미지들로부터 현재 입력되는 영상과 가장 가까운 이미지를 찾아낸다. 또한 로봇은 찾아진 영상을 이용하여 사전에 저장되어 있는 지도상에서의 자신의 위치를 추정할 수 있다. 본 논문에서는 일반적으로 로봇이 작업하는 환경의 조명 상황이 일정하지 않음을 고려하여 다양한 조명 상태에 대하여 여러 가지 color indexing 알고리즘을 적용하여 실험하였으며 matching된 이미지를 이용하여 지도상에서의 로봇의 위치를 추정하는 구체적인 방법을 제시하고 실험을 통하여 타당성을 검증하였다.

• Journal of KIISE:Databases
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• v.29 no.2
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• pp.128-137
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• 2002

In this paper, we propose the LPC+-file for efficient indexing of high-dimensional image data. With the proliferation of multimedia data, there Is an increasing need to support the indexing and retrieval of high-dimensional image data. Recently, the LPC-file (5) that based on vector approximation has been developed for indexing high-dimensional data. The LPC-file gives good performance especially when the dataset is uniformly distributed. However, compared with for the uniformly distributed dataset, its performance degrades when the dataset is clustered. We improve the performance of the LPC-file for the strongly clustered image dataset. The basic idea is to adaptively partition the data space to find subspaces with high-density clusters and to assign more bits to them than others to increase the discriminatory power of the approximation of vectors. The total number of bits used to represent vector approximations is rather less than that of the LPC-file since the partitioned cells in the LPC+-file share the bits. An empirical evaluation shows that the LPC+-file results in significant performance improvements for real image data sets which are strongly clustered.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.2 no.3
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• pp.150-170
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• 2008

In recent years, main focus of research on image retrieval techniques is on content-based image retrieval. Text-based image retrieval schemes, on the other hand, provide semantic support and efficient retrieval of matching images. In this paper, based on Formal Concept Analysis (FCA), we propose a new image indexing and retrieval technique. The proposed scheme uses keywords and textual annotations and provides semantic support with fast retrieval of images. Retrieval efficiency in this scheme is independent of the number of images in the database and depends only on the number of attributes. This scheme provides dynamic support for addition of new images in the database and can be adopted to find images with any number of matching attributes.

• Journal of Industrial Technology
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• v.20 no.B
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• pp.207-211
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• 2000

For efficient massive image retrieval, an image retrieval requires that several important objectives are satisfied, namely: automated extraction of features, efficient indexing and effective retrieval. In this work, we present a technique for extracting the 4-dimension directional feature. By directional detail, we imply strong directional activity in the horizontal, vertical and diagonal direction present in region of the image texture. This directional information also present smoothness of region. The 4-dimension feature is only indexed in the 4-D space so that complex high-dimensional indexing can be avoided.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.827-830
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• 2000

In this paper, we propose the method using PCA(principal component analysis) algorithm when proposed algorithm performs multimedia information indexing. After we extract DC coefficients of DCT from MPEG video stream which is an international standard of moving picture compression coding, we apply PCA algorithm to image made of DC coefficients and extract the feature of each DC image. Using extracted features, we generate codebook and perform multimedia information indexing. The proposed algorithm Is very fast when indexing and can generate optimized codebook because of using statistical feature of data

• Journal of the Semiconductor & Display Technology
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• v.9 no.3
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• pp.17-21
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• 2010

As the compact and easily accessible handheld devices, such as cellular phones and MP3 players equipped with image acquisition functionality, are becoming widely available among common users, various applications of images are rapidly increasing. Image related services and software such as web-based image presentation and image manipulation for personal or commercial purpose enable users to view contents of remote image archive and to manipulate enormous amount of images in local or network based storage as well. It is necessary for users to identify the images efficiently so that the same images are perceived as one physical entity instead of recognizing them as different images as the trends are getting stronger. In order to support this environment, we propose a method that generates image identifiers or indexing for images within a solid and efficient manner. The proposed image identifier utilizes multiple index values. The integration of component index values creates a unique composite value that can be used as a file name, file system identifier, or database index. Our experimental results on generation of constituent index values have shown favorable results.