• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.11
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• pp.2137-2142
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• 2016

The electrical current generated by heart creates not only electric potential but also a magnetic field. In this study, the signals obtained magnetocardiogram(MCG) using 61 channel superconducting quantum interference device(SQUID) system, and the clinical significance of various feature parameters has been developed MCG. Neural network algorithm was used to perform the classification of ischemic heart disease. The MCG signal was obtained to facilitate the extraction of parameters through a process of pre-processing. The data used to research the normal group 10 and ischemic heart disease group 10 with visible signs of stable angina patients. The available clinical indicators were extracted by characteristic point, characteristic interval parameter, and amplitude ratio parameter. The extracted parameters are determined to analysis the significance and clinical parameters were defined. It is possible to classify ischemic heart disease using the MCG feature parameters as a neural network input.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.2
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• pp.111-119
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• 2013

It is essential and fundamental to extract boundary information of target object via massive three-dimensional point data acquired from laser scanner. Especially extracting boundary information of manmade features such as buildings is quite important because building is one of the major components consisting complex contemporary urban area, and has artificially defined shape. In this research, extended ${\chi}$-algorithm using geometry information of point data was proposed to extract boundary information of building from three-dimensional point data consisting building. The proposed algorithm begins with composing Delaunay triangulation process for given points and removes edges satisfying specific conditions process. Additionally, to make whole boundary extraction process efficient, we used Sweep-hull algorithm for constructing Delaunay triangulation. To verify the performance of the proposed extended ${\chi}$-algorithm, we compared the proposed algorithm with Encasing Polygon Generating Algorithm and ${\alpha}$-Shape Algorithm, which had been researched in the area of feature extraction. Further, the extracted boundary information from the proposed algorithm was analysed against manually digitized building boundary in order to test accuracy of the result of extracting boundary. The experimental results showed that extended ${\chi}$-algorithm proposed in this research proved to improve the speed of extracting boundary information compared to the existing algorithm with a higher accuracy for detecting boundary information.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.2 s.314
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• pp.144-152
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• 2007

We propose a 3D modeling method for surface inspection of non-linear moving object. The laser lines reflect the surface curvature. We can acquire 3D surface information by analyzing projected laser lines on object. ill this paper, we use multi-line laser to make use of robust of single stripe method and high speed of single frame. Binarization and channel edge extraction method were used for robust laser line extraction. A new labeling method was used for laser line labeling. We acquired sink information between each 3D reconstructed frame by feature point matching, and registered each frame to one whole image. We verified the superiority of proposed method by applying it to container damage inspection system.

• The KIPS Transactions:PartB
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• v.14B no.7
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• pp.503-512
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• 2007

An infant of a baby child who haven't communication skills through a language expresses their intention or baby condition as generally crying. Among these things, it is important to show a baby condition because their disease miss diagnosis time or remain to decide an exact diagnosis result too hard. For this, in this paper, we are going to develop system which decides where to be not good body point by analysing their face color and crying sound. Specifically, in this paper, we are going to act for baby heart diseases by doing feature extraction for their face region color and crying sound. To embody, we are going to present diagnosis method and compare analyze their crying sound a stand child, a different diseases child and a baby heart diseases child through each analyzed element. And also, we are going to extract matters to be attended to baby heart diseases through experiment and prepare objective index and an accuracy of baby heart diseases diagnosis result.

• The KIPS Transactions:PartD
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• v.12D no.6 s.102
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• pp.829-836
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• 2005

The way to assign a splitting criterion for correct object classification is the main issue in all decisions trees. This paper describes new splitting rules for classification in order to find an optimal split point. Unlike the current splitting rules that are provided by searching all threshold values, this paper proposes the splitting rules that we based on the probabilities of pre assigned intervals. Our methodology provides that user can control the accuracy of tree by adjusting the number of intervals. In addition, we applied the proposed splitting rules to a set of image data that was retrieved by parameterized feature extraction to recognize image objects.

• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.177-186
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• 2005

In this Paper. we propose vision-based camera localization technique using 3D information which is created by mapping of DEM and mountain image. Typically, image features for localization have drawbacks, it is variable to camera viewpoint and after time information quantify increases . In this paper, we extract invariance features of geometry which is irrelevant to camera viewpoint and estimate camera extrinsic Parameter through accurate corresponding Points matching by Proposed similarity evaluation function and Graham search method we also propose 3D information creation method by using graphic theory and visual clues, The Proposed method has the three following stages; point features invariance vector extraction, 3D information creation, camera extrinsic Parameter estimation. In the experiments, we compare and analyse the proposed method with existing methods to demonstrate the superiority of the proposed methods.

• Journal of Korea Multimedia Society
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• v.20 no.3
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• pp.465-473
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• 2017

Electrocardiogram(ECG) signal is one of the unique bio-signals of individuals and is used for personal authentication. The existing studies on personal authentication method using ECG signals show a high detection rate for a small group of candidates, but a low detection rate and increased execution time for a large group of candidates. In this paper, we propose a hierarchical algorithm that extracts fiducial points based on curvature of ECG signals as feature values for grouping candidates ​and identifies candidates using waveform-based comparisons. As a result of experiments on 74 ECG signal records of QT-DB provided by Physionet, the detection rate was about 97% at 3-heartbeat input and about 99% at 5-heartbeat input. The average execution time was 22.4 milliseconds. In conclusion, the proposed method improves the detection rate by the hierarchical personal authentication process, and also shows reduced amount of computation which is plausible in real-time personal authentication usage in the future.

• Journal of KIISE:Software and Applications
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• v.31 no.6
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• pp.817-828
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• 2004

In this paper, we propose vector-based face generation system that uses montage and shading method and preserves designer(artist)'s style. Proposed system generates character's face similar to human face automatically using facial features that extracted from a photograph. In addition, unlike previous face generation system that uses contours, we propose the system is based on color and composes face from facial features and shade extracted from a photograph. Thus, it has advantages that can make more realistic face similar to human face. Since this system is vector-based, the generated character's face has no size limit and constraint. Therefore it is available to transform the shape freely and to apply various facial expressions to 2D face. Moreover, it has distinctiveness with another approaches in point that can keep artist's impression just as it is in result.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.05a
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• pp.109-112
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• 1999

Image segmentation is the critical first step in image information extraction for computer vision systems. Clustering methods have been used extensively in color image segmentation. Most analytic fuzzy clustering approaches are divided from the fuzzy c-means(FCM) algorithm. The FCM algorithm uses fie probabilistic constraint that the memberships of a data point across classes sum to 1. However, the memberships resulting from the FCM do not always correspond to the intuitive concept of degree of belonging or compatibility. Moreover, the FCM algorithm has considerable trouble under noisy environments in the feature space. Recently, a possibilistic approach to clustering(PCM) for solving above problems was proposed. In this paper, we used the PCM for color image segmentation. This approach differs from existing fuzzy clustering methods for color image segmentation in that the resulting partition of the data can be interpreted as a possibilistic partition. So, the problems in the FCM can be solved by the PCM. But, the clustering results by the PCM are not smoothly bounded, and they often have holes. The region growing was used as a postprocessing after smoothing the noise points in the pixel seeds. In our experiments, we illustrate that the PCM us reasonable than the FCM in noisy environments.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.19 no.2
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• pp.162-168
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• 2006

Recently, diagnosis techniques have been investigated to detect a Partial Discharge associated with a dielectric material defect in a high voltage electrical apparatus, However, the properties of detection technique of Partial Discharge aren't completely understood because the physical process of Partial Discharge. Therefore, this paper analyzes the process on surface discharge of polymer insulator using wavelet transform. Wavelet transform provides a direct quantitative measure of spectral content in the time~frequency domain. As it is important to develop a non-contact method for detecting the kaolin contamination degree, this research analyzes the electromagnetic waves emitted from Partial Discharge using wavelet transform. This result experimentally shows the process of Partial Discharge as a two-dimensional distribution in the time-frequency domain. Feature extraction parameter namely, maximum and average of wavelet coefficients values, wavelet coefficients value at the point of $95\%$ in a histogram and number of maximum wavelet coefficient have used electromagnetic wave signals as input signals in the preprocessing process of neural networks in order to identify kaolin contamination rates. As result, root sum square error was produced by the test with a learning of neural networks obtained 0.00828.