• Journal of Korea Multimedia Society
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• v.12 no.8
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• pp.1172-1181
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• 2009

An electronic medical record (EMR) is the medical system that all the test are recorded as text data. However, domestic EMR systems have various forms of medical records. There are a lot of related works to standardize the laboratory codes as a LOINC (Logical Observation Identifiers Names and Code). However the existing researches resolve the problem manually. The manual process does not work when the size of data is enormous. The paper proposes a novel automatic LOINC mapping algorithm which uses indexing techniques and semantic similarity analysis of medical information. They use file system which is not proper to enormous medical data. We designed and implemented mapping algorithm for standardization laboratory codes in medical informatics compared with the existing researches that are only proposed algorithms. The automatic creation of searching words is being possible. Moreover, the paper implemented medical searching framework based on database system that is considered large size of medical data.

• Journal of Korea Multimedia Society
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• v.7 no.10
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• pp.1452-1463
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• 2004

The requirement of automatic video summary is increasing as bi-directional broadcasting contents and various user requests and preferences for the bi -directional broadcast environment are increasing. Automatic video summary is needed for an efficient management and usage of many contents in service provider as well. In this paper, we propose a method to generate a content-based summary of linguistic educational videos automatically. First, shot-boundaries and keyframes are generated from linguistic educational video and then multiple(low-level) visual features are extracted. Next, the semantic parts (Explanation part, Dialog part, Text-based part) of the linguistic educational video are generated using extracted visual features. Lastly the XMI- document describing summary information is made based on HieraTchical Summary architecture oi MPEG-7 MDS (Multimedia I)escription Scheme). Experimental results show that our proposed algorithm provides reasonable performance for automatic summary of linguistic educational videos. We verified that the proposed method is useful ior video summary system to provide various services as well as management of educational contents.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.5
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• pp.1677-1684
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• 2010

Recently, due to the development of mobile phone and supply of smart phone, many contents have been developed. Especially, since the small-sized cameras are equiped in mobile devices, people are interested in the image based contents development, and it also becomes important part in their practical use. Among them, the character recognition system can be widely used in the applications such as blind people guidance systems, automatic robot navigation systems, automatic video retrieval and indexing systems, automatic text translation systems. Therefore, this paper proposes a system that is able to extract text area from the natural images captured by smart phone camera. The individual characters are recognized and result is output in voice. Text areas are extracted using Adaboost algorithm and individual characters are recognized using error back propagated neural network.

• Journal of KIISE:Software and Applications
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• v.33 no.10
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• pp.851-861
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• 2006

The paper proposes a novel unsupervised video object segmentation algorithm for image sequences with low depth-of-field (DOF), which is a popular photographic technique enabling to represent the intention of photographer by giving a clear focus only on an object-of-interest (OOI). The proposed algorithm largely consists of two modules. The first module automatically extracts OOIs from the first frame by separating sharply focused OOIs from other out-of-focused foreground or background objects. The second module tracks OOIs for the rest of the video sequence, aimed at running the system in real-time, or at least, semi-real-time. The experimental results indicate that the proposed algorithm provides an effective tool, which can be a basis of applications, such as video analysis for virtual reality, immersive video system, photo-realistic video scene generation and video indexing systems.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.727-743
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• 2003

This paper proposes an automatic highlight building algorithm for soccer video by using the structural characteristics of broadcasted sports video that an interesting (or important) event (such as goal or foul) in sports video has a continuous replay shot surrounded by gradual shot change effect like wipe. This shot editing rule is used in this paper to analyze the structure of broadcated soccer video and extracts shot involving the important events to build a highlight. It first uses the spatial-temporal image of video to detect wipe transition effects and zoom out/in shot changes. They are used to detect the replay shot. However, using spatial-temporal image alone to detect the wipe transition effect requires too much computational resources and need to change algorithm if the wipe pattern is changed. For solving these problems, a two-pass detection algorithm and a pixel sub-sampling technique are proposed in this paper. Furthermore, to detect the zoom out/in shot change and replay shots more precisely, the green-area-ratio and the motion energy are also computed in the proposed scheme. Finally, highlight shots composed of event and player shot are extracted by using these pre-detected replay shot and zoom out/in shot change point. Proposed algorithm will be useful for web services or broadcasting services requiring abstracted soccer video.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.1
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• pp.11-24
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• 2008

Region-based image retrieval techniques, which divide image into similar regions having similar characteristics and examine similarities among divided regions, were proposed to support an efficient low-dimensional color indexing scheme. However, color image segmentation techniques are required additionally. The problem of segmentation is difficult because of a large variety of color and texture. It is known to be difficult to identify image regions containing the same color-texture pattern in natural scenes. In this paper we propose an automatic color image segmentation algorithm. The colors in each image are first quantized to reduce the number of colors. The gray level of image representing the outline edge of image is constructed in terms of Fisher's multi-class linear discriminant on quantized images. The gray level of image is transformed into a binary edge image. The edge showing the outline of the binary edge image links to the nearest edge if disconnected. Finally, the final segmentation image is obtained by merging similar regions. In this paper we design and implement a region-based image retrieval system using the proposed segmentation. A variety of experiments show that the proposed segmentation scheme provides good segmentation results on a variety of images.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.4
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• pp.479-488
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• 2002

In recent years the amount of digital video used has risen dramatically to keep pace with the increasing use of the Internet and consequently an automated method is needed for indexing digital video databases. Textual information, both superimposed and embedded scene texts, appearing in a digital video can be a crucial clue for helping the video indexing. In this paper, a new method is presented to extract both superimposed and embedded scene texts in a freeze-frame of news video. The algorithm is summarized in the following three steps. For the first step, a color image is converted into a gray-level image and applies contrast stretching to enhance the contrast of the input image. Then, a modified local adaptive thresholding is applied to the contrast-stretched image. The second step is divided into three processes: eliminating text-like components by applying erosion, dilation, and (OpenClose+CloseOpen)/2 morphological operations, maintaining text components using (OpenClose+CloseOpen)/2 operation with a new Geo-correction method, and subtracting two result images for eliminating false-positive components further. In the third filtering step, the characteristics of each component such as the ratio of the number of pixels in each candidate component to the number of its boundary pixels and the ratio of the minor to the major axis of each bounding box are used. Acceptable results have been obtained using the proposed method on 300 news images with a recognition rate of 93.6%. Also, my method indicates a good performance on all the various kinds of images by adjusting the size of the structuring element.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.73-80
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• 2005

Recently there have been many efforts to support searching and browsing based on the visual content of image and multimedia data. Most existing approaches to content-based image retrieval rely on query by example or user based low-level features such as color, shape, texture. But these methods of query are not easy to use and restrict. In this paper we propose a method for automatic color object extraction and labelling to support multiple queries of content-based image retrieval system. These approaches simplify the regions within images using single colorizing algorithm and extract color object using proposed Color and Spatial based Binary tree map(CSB tree map). And by searching over a large of number of processed regions, a index for the database is created by using proposed labelling method. This allows very fast indexing of the image by color contents of the images and spatial attributes. Futhermore, information about the labelled regions, such as the color set, size, and location, enables variable multiple queries that combine both color content and spatial relationships of regions. We proved our proposed system to be high performance through experiment comparable with another algorithm using 'Washington' image database.

• Journal of KIISE:Databases
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• v.30 no.5
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• pp.507-520
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• 2003

In this paper, an automatic construction method of theme melody index for large music database and an associative content-based music retrieval mechanism in which the constructed theme melody index is mainly used to improve the users' response time are proposed. First, the system automatically extracted the theme melody from a music file by the graphical clustering algorithm based on the similarities between motifs of the music. To place an extracted theme melody into the metric space of M-tree, we chose the average length variation and the average pitch variation of the theme melody as the major features. Moreover, we added the pitch signature and length signature which summarize the pitch variation pattern and the length variation pattern of a theme melody, respectively, to increase the precision of retrieval results. We also proposed the associative content-based music retrieval mechanism in which the k-nearest neighborhood searching and the range searching algorithms of M-tree are used to select the similar melodies to user's query melody from the theme melody index. To improve the users' satisfaction, the proposed retrieval mechanism includes ranking and user's relevance feedback functions. Also, we implemented the proposed mechanisms as the essential components of content-based music retrieval systems to verify the usefulness.