• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.926-930
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• 2006

Current image retrieval techniques have shortcomings that make it difficult to search for images based on a semantic understanding of what the image is about. Since an image is normally associated with multiple contexts (e.g. when and where a picture was taken,) the knowledge of these contexts can enhance the quantity of semantic understanding of an image. In this paper, we present a context-aware image retrieval system, which uses the context information to infer a kind of metadata for the captured images as well as images in different collections and databases. Experimental results show that using these kinds of information can not only significantly increase the retrieval accuracy in conventional content-based image retrieval systems but decrease the problems arise by manual annotation in text-based image retrieval systems as well.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.194-197
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• 2000

Wavelet transform used for content-based image retrieval has good performance in texture image. Image features for content-based image retrieval are color, texture, and shape. In this paper, we use color feature extracted from HSI color space known as most similar vision system to human vision system and texture feature extracted from wavelet histogram which has multiresolution property. Proposed method is compared with HSI color histogram method and wavelet histogram method. It is shown better performance.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.11a
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• pp.227-230
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• 2006

A content-based image retrieval system using MPEG-7 is designed and implemented in this thesis. The implemented system uses existing MPEG-7 Visual Descriptors. In addition, a new descriptor for efficient retrieval of bio images is proposed and utilized in the developed content-based image retrieval system. Comparing proposed CBSD(Compact Binary Shape Descriptor) with Edge Histogram Descriptor(EHD) and Region Shape Descriptor(RSD), it shows good retrieval performance in NMRR. The proposed descriptor is robust to large modification of brightness and contrast and especially improved retrieval performance to search images with similar shapes. Also proposed system adopts distributed architecture to solve increased server overload and network delay. Updating module of client efficiently reduces downloading time for metadata. The developed system can efficiently retrieve images without causing server's overload.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.5
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• pp.510-521
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• 2001

Image retrieval system should be construct for searching fast, efficient image be extract the accurate feature information of image with more massive and more complex characteristics. Image retrieval system are essential differences between image databases and traditional databases. These differences lead to interesting new issues in searching of image, data modeling. So, cause us to consider new generation method of database, efficient retrieval method of image. In this paper, To extract feature information of edge using in searching from input image, we was performed to extract the edge by convolution Laplacian mask and input image, and we implemented the annotation-based and content-based image retrieval system for searching fast, efficient image by generation image database from extracting feature information of edge and metadata. We can improve the performance of the image contents retrieval, because the annotation-based and content-based image retrieval system is using image index which is made up of the content-based edge feature extract information represented in the low level of image and annotation-based edge feature information represented in the high level of image. As a conclusion, image retrieval system proposed in this paper is possible the accurate management of the accumulated information for the image contents and the information sharing and reuse of image because the proposed method do construct the image database by metadata.

• The Transactions of the Korea Information Processing Society
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• v.4 no.9
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• pp.2315-2332
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• 1997

In this paper, we implement a content based image retrieval system for image searching by visual features from the image databases on WWW (world wide web). The image retrieval system finds the images that contain the most similar color regions after the system automatically extracts color features from the input image. We can select one of two query methods which use a full image of $4{\times}4$ 16 sketched color region. The image similarity is calculated on the histogram intersection distance and the histogram Euclidean distance. As the experimental results show that the two different query types provide the precision/recall 0.84/0.92 and 0.85/0.93 respectively, this retrieval system has been able to obtain high performance and validity.

• Journal of Korea Society of Industrial Information Systems
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• v.7 no.4
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• pp.9-16
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• 2002

Content based Image retrieval methods in the multimedia information retrievals use primary visual features such as color, texture and shape. Color and texture generally are used as features of the image retrieval systems. But these systems may produce errors in similar image retrieval because two images with different shapes can represent very different contents. Therefore, the use of shape describing features is essential in an efficient content based image retrieval system. In this paper, after the global features filtering process by the boundary of objects, we have created a better shape similarity image retrieval system by a histogram of shape information.

• Journal of the Semiconductor & Display Technology
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• v.13 no.2
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• pp.45-52
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• 2014

This paper proposes an efficient photo retrieval system that automatically indexes for searching of relevant images, using a combination of geo-coded information, direction/location of image capture device and content-based visual features. A photo image is labeled with its GPS (Global Positioning System) coordinates and direction of the camera view at the moment of capture, and the label leads to generate a geo-spatial index with three core elements of latitude, longitude and viewing direction. Then, content-based visual features are extracted and combined with the geo-spatial information, for indexing and retrieving the photo images. For user's querying process, the proposed method adopts two steps as a progressive approach, filtering the relevant subset prior to use a content-based ranking function. To evaluate the performance of the proposed scheme, we assess the simulation performance in terms of average precision and F-score, using a natural photo collection. Comparing the proposed approach to retrieve using only visual features, an improvement of 20.8% was observed. The experimental results show that the proposed method exhibited a significant enhancement of around 7.2% in retrieval effectiveness, compared to previous work. These results reveal that a combination of context and content analysis is markedly more efficient and meaningful that using only visual feature for image search.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.2
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• pp.12-17
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• 2003

This paper proposes content-based image retrieval system with fuzzy ART neural network algorithm. Retrieving large database of image data, the clustering is essential for fast retrieval. However, it is difficult to cluster huge image data pertinently, Because current retrieval methods using similarities have several problems like low accuracy of retrieving and long retrieval time, a solution is necessary to complement these problems. This paper presents a content-based image retrieval system with neural network in order to reinforce abovementioned problems. The retrieval system using fuzzy ART algorithm normalizes color and texture as feature values of input data between 0 and 1, and then it runs after clustering the input data. The implemental result with 300 image data shows retrieval accuracy of approximately 87%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.5
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• pp.889-898
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• 1997

Most general content-based image retrieval techniques use color and texture as retrieval indices. Spatial information is not used to color histogram and color pair based on color retrieval techniques. This paper proposes the selection of a set of representative in the duplicated color histogram, the analysis of spatial information of the selected colors and the image retrieval process based on the duplicated color histogram and spatial information. Two color historgrams for background and object are used in order to decide on color selection in the duplicated color histogram. Spatial information is obtained using a maximum entropy discretization. A retrieval process applies to duplicated color histogram and spatial to retrieve input images and relevant images. As the result of experiment of the image retrieval, improved color his togram and spatial information method hs increased the retrieval effectiveness more the color histogram method and color pair method.

• Journal of the Semiconductor & Display Technology
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• v.7 no.2
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• pp.69-76
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• 2008

Recently, as the multimedia processing application increases rapidly by going on increasing multimedia data, the efficient retrieval method of image information is required in many fields of application and becoming the matter of major concern. Furthermore, in the last few years rapid improvements in hardware technology have made it possible to process, store and retrieve huge amounts of data in a multimedia format. As a result, Content-Based Image Retrieval (CBIR) has been receiving widespread interest during the last decade. This paper propose the content-based retrieval system as a method for performing image retrieval through the effective feature analysis of the object of significant meaning by using YCbCr channel merging on the basis of the characteristics of man's visual system.