• Journal of KIISE:Software and Applications
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• v.29 no.1_2
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• pp.80-90
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• 2002

Clustering is a useful technique for grouping data points such that points within a single group/cluster have similar characteristics. Many clustering algorithms have been developed and used in engineering applications including pattern recognition and image processing etc. Recently, it has drawn increasing attention as one of important techniques in data mining. However, clustering algorithms such as K-means and Fuzzy C-means suffer from difficulties. Those are the needs to determine the number of clusters apriori and the clustering results depending on the initial set of clusters which fails to gain desirable results. In this paper, we propose a new clustering algorithm, which solves mentioned problems. In our method we use evolutionary algorithm to solve the local optima problem that clustering converges to an undesirable state starting with an inappropriate set of clusters. We also adopt a new measure that represents how well data are clustered. The measure is determined in terms of both intra-cluster dispersion and inter-cluster separability. Using the measure, in our method the number of clusters is automatically determined as the result of optimization process. And also, we combine heuristic that is problem-specific knowledge with a evolutionary algorithm to speed evolutionary algorithm search. We have experimented our algorithm with several sets of multi-dimensional data and it has been shown that one algorithm outperforms the existing algorithms.

• Journal of KIISE:Software and Applications
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• v.29 no.1_2
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• pp.114-125
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• 2002

In this paper, we are proposing a hierarchical segmentation method that first segments the video data into units of shots by detecting cut and dissolve, and then decides types of camera operations or object movements in each shot. In our previous work[1], each picture group is divided into one of the three detailed categories, Shot(in case of scene change), Move(in case of camera operation or object movement) and Static(in case of almost no change between images), by analysing DC(Direct Current) component of I(Intra) frame. In this process, we have designed two-stage hierarchical neural network with inputs of various multiple features combined. Then, the system detects the accurate shot position, types of camera operations or object movements by searching P(Predicted), B(Bi-directional) frames of the current picture group selectively and hierarchically. Also, the statistical distributions of macro block types in P or B frames are used for the accurate detection of cut position, and another neural network with inputs of macro block types and motion vectors method can reduce the processing time by using only DC coefficients of I frames without decoding and by searching P, B frames selectively and hierarchically. The proposed method classified the picture groups in the accuracy of 93.9-100.0% and the cuts in the accuracy of 96.1-100.0% with three different together is used to detect dissolve, types of camera operations and object movements. The proposed types of video data. Also, it classified the types of camera movements or object movements in the accuracy of 90.13% and 89.28% with two different types of video data.

• Journal of KIISE:Software and Applications
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• v.31 no.10
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• pp.1332-1344
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• 2004

Upon development of information super-highway and multimedia-related technoiogies in recent years, more efficient technologies to transmit, store and retrieve the multimedia data are required. Among such technologies, firstly, it is common that the semantic-based image retrieval is annotated separately in order to give certain meanings to the image data and the low-level property information that include information about color, texture, and shape Despite the fact that the semantic-based information retrieval has been made by utilizing such vocabulary dictionary as the key words that given, however it brings about a problem that has not yet freed from the limit of the existing keyword-based text information retrieval. The second problem is that it reveals a decreased retrieval performance in the content-based image retrieval system, and is difficult to separate the object from the image that has complex background, and also is difficult to extract an area due to excessive division of those regions. Further, it is difficult to separate the objects from the image that possesses multiple objects in complex scene. To solve the problems, in this paper, I established a content-based retrieval system that can be processed in 5 different steps. The most critical process of those 5 steps is that among RGB images, the one that has the largest and the smallest background are to be extracted. Particularly. I propose the method that extracts the subject as well as the background by using an Image, which has the largest background. Also, to solve the second problem, I propose the method in which multiple objects are separated using RGB channel selection techniques having optimized the excessive division of area by utilizing Watermerge's threshold value with the object separation using the method of RGB channels separation. The tests proved that the methods proposed by me were superior to the existing methods in terms of retrieval performances insomuch as to replace those methods that developed for the purpose of retrieving those complex objects that used to be difficult to retrieve up until now.

• Geophysics and Geophysical Exploration
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• v.8 no.4
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• pp.262-269
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• 2005

Since the buried cultural relics are three-dimensional (3-D) objects in nature, 3-D survey is more preferable in archeological exploration. 3-D Ground Penetrating Radar (GPR) survey based on very dense data in principle, however, might need much higher cost and longer time of exploration than other geophysical methods commonly used for the archeological exploration, such as magnetic and electromagnetic methods. We developed a small-scale continuous data acquisition system which consists of two sets of GPR antennas and the precise positioning device tracking the moving-path of GPR antenna automatically and continuously. Since the high cost of field work may be partly attributed to establishing many profile lines, we adopted a concept of data acquisition at arbitrary locations not along the pre-established profile lines. Besides this hardware system, we also developed several software packages in order to effectively process and visualize the 3-D data obtained by the developed system and the data acquisition concept. Using the developed system, we performed 3-D GPR survey to investigate the possible historical remains of Baekje Kingdom at Buyeo city, South Korea, prior to the excavation. Owing to the newly devised system, we could obtain 3-D GPR data of this survey area having areal extent over about $17,000m^2$ within only six-hours field work. Although the GPR data were obtained at random locations not along the pre-established profile lines, we could obtain high-resolution 3-D images showing many distinctive anomalies, which could be interpreted as old agricultural lands, waterways, and artificial structures or remains. This cast: history led us to the conclusion that 3-D GPR method is very useful not only to examine a small anomalous area but also to investigate the wider region of the archeological interests.

• Journal of radiological science and technology
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• v.29 no.3
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• pp.167-175
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• 2006

With the recent prevalence of helical CT and multi-slice CT, which deliver higher radiation dose than conventional CT due to overbeaming effect in X-ray exposure and interpolation technique in image reconstruction. Although multi-detector and helical CT scanner provide a variety of opportunities for patient dose reduction, the potential risk for high radiation levels in CT examination can't be overemphasized in spite of acquiring more diagnostic information. So much more concerns is necessary about dose characteristics of CT scanner, especially dose efficient design as well as dose modulation software, because dose efficiency built into the scanner's design is probably the most important aspect of successful low dose clinical performance. This study was conducted to evaluate z-axis geometric dose efficiency in single detector CT and each level multi-detector CT, as well as to compare z-axis dose efficiency with change of technical scan parameters such as focal spot size of tube, beam collimation, detector combination, scan mode, pitch size, slice width and interval. The results obtained were as follows ; 1. SDCT was most highest and 4 MDCT was most lowest in z-axis geometric dose efficiency among SDCT, 4, 8, 16, 64 slice MDCT made by GE manufacture. 2. Small focal spot was 0.67-13.62% higher than large focal spot in z-axis geometric dose efficiency at MDCT. 3. Large beam collimation was 3.13-51.52% higher than small beam collimation in z-axis geometric dose efficiency at MDCT. 4. Z-axis geometric dose efficiency was same at 4 slice MDCT in all condition and 8 slice MDCT of large beam collimation with change of detector combination, but was changed irregularly at 8 slice MDCT of small beam collimation and 16 slice MDCT in all condition with change of detector combination. 5. There was no significant difference for z-axis geometric dose efficiency between conventional scan and helical scan, and with change of pitch factor, as well as change of slice width or interval for image reconstruction. As a conclusion, for reduction of patient radiation dose delivered from CT examination we are particularly concerned with dose efficiency of equipment and have to select proper scanning parameters which increase z-axis geometric dose efficiency within the range of preserving optimum clinical information in MDCT examination.