• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1491-1494
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• 2002

The paper introduces a novel system of two hands real-time tracking based on the unrestricted hand skin segmentation by multi color systems. After corer-based segmentation and pre-processing operation, a label set of regions is created to locate the two hands automatically. By the normalization, template matching is used to find out the left or right hand. An improved fast self-adaptive tracking algorithm is applied and Canny filter is used for hand detection.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.3
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• pp.42-47
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• 2007

Video Segmentation is an essential part in region-based video coding and any other fields of the video processing. Among lots of methods proposed so far, the watershed method in which the region growing is performed for the gradient image can produce well-partitioned regions globally without any influence on local noise and extracts accurate boundaries. But, it generates a great number of small regions, which we call over segmentation problem. Therefore we proposes that adaptive trimmed mean filter for resolving the over segmentation of image. Simulation result, we confirm that proposed ATM filter improves the performance to remove noise and reduces damage for the clear degree of image in case of the noise ratio of 20% and over.

• Journal of KIISE:Software and Applications
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• v.31 no.3
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• pp.276-292
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• 2004

In this paper. we present methods that extract lung regions from chest EBT(electron beam tomography) images then segment the extracted lung region into lung lobes. We use histogram based thresholding and mathematical morphology for extracting lung regions. For detecting pulmonary fissures, we use edge detector and knowledge-based search method. We suggest this edge detector, which uses adaptive filter scale, to work very well for real edge and insensitive for edge by noise. Our experiments showed about 95% accuracy or higher in extracting lung regions and about 5 pixel distance error in detecting pulmonary fissures.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.176-183
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• 2013

We propose a rolled fingerprint merging algorithm that effectively merges plain fingerprints in consecutive frame units that are fed through rolling and detects more fingerprint minutiae in order to increase the fingerprint recognition rate. The proposed rolled fingerprint merging algorithm uses a adaptive projection mask; it contains a detector that separates plain fingerprints from the background and a projection mask generator that sequentially projects the detect ed images. In addition, in the merging unit, the pyramid-shaped projection method is used to detect merged rolled fingerprints from the generated variable projective mask, starting from the main images. Simulations show that the extracted minutia e are 46.79% more than those from plain fingerprints, and the proposed algorithm exhibits excellent performance by detecting 52.0% more good fingerprint minutiae that are needed for matching.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.201-205
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• 2004

The digital color image can be distorted by noise for a transmission or other elements of system. It happens to vague of a boundary side in the division of a color image object, especially, boundary side of an input color image is very important because it can be determined to the division and detection element in pattern recognition. Therefore it is boundary part In this paper, it detects the optimal edge with applying this color image to WCNN algorithm, after it does level up a boundary side of a color image by using the adaptive morphology as the threshold of an input color image. Also, it is used not a conventional fixed mask edge detection method but variable mask method which is cal led a variable BBM. It is confirmed by simulation that the proposed algorithm can be got the batter result edge at the place of closing to each edges and having smoothly curved line.

• Journal of Sensor Science and Technology
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• v.22 no.5
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• pp.338-345
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• 2013

Premature ventricular contractions are the most common of all arrhythmias and may cause more serious situation like ventricular fibrillation and ventricular tachycardia in some patients. Therefore, the detection of this arrhythmia becomes crucial in the early diagnosis and the prevention of possible life threatening cardiac diseases. Most methods for detecting arrhythmia require pp interval, or the diversity of P wave morphology, but they are difficult to detect the p wave signal because of various noise types. Thus, it is necessary to use noise-free R wave. So, the new approach for the detection of PVC is presented based on the rhythm analysis and the beat matching in this paper. For this purpose, we removed baseline wandering of low frequency band and made summed signals that are composed of two high frequency bands including the frequency component of QRS complex using the wavelet filter. And then we designed R wave detection algorithm using the adaptive threshold and window through RR interval. Also, we developed algorithm to classify PVC using RR interval. The performance of R wave and PVC detection is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate average detection rate of 99.76%, sensitivity of 99.30% and specificity of 98.66%; accuracy respectively for R wave and PVC detection.

• Korean Journal of Ichthyology
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• v.22 no.4
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• pp.217-224
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• 2010

An investigation was carried out to obtain basic information needed to develop methods for artificial propagation and conservation of the mottled skate Raja pulchra, an important food resource in western Korea that has declined from overfishing. In this paper we provide evidence of multiple spawning and describe properties of the ovary, and morphology of the egg capsule and the fully-formed offspring. The vitellogenic follicles in the ovary was $179.8{\pm}57.1$ (54~247) and can be classified into five size groups, which the last group of ova are considered as the moving to the capsule gland where fertilization and encapsulation of ova take place. The morphology of the egg capsule of R. pulchra is unique among the species of the family Rajidae and showed multi-embryo characteristics, having two to six yolks in each capsule. The adaptive morphological changes of larvae developing inside the egg capsule are described based on specimens extracted from the capsule.

• Korean Journal of Ecology and Environment
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• v.53 no.4
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• pp.390-407
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• 2020

This study was carried out to evaluate the restoration effect in the restored Yangjae stream and to draw up an adaptive management plan based on the results. As the result of evaluation on the restoration effect, the restored Yangjae stream was evaluated with low naturalness in both terms of the morphology of the stream and the composition and spatial distribution of vegetation. The diverse functional groups were introduced in the vegetation restoration, but the flooding regime, which is significant in the spatial distribution of riparian vegetation, were not correctly reflected. Exotic species or species that were not ecologically suitable for the location were introduced on the embankment and thus a measure to improve those problems is required. As the ecological principle was not reflected in the restoration plan, the stream was constructed as the double terrace structure. Therefore, the width of the waterway was narrowed further, and the waterfront was not designed to accommodate changes from flooding disturbance, making the micro-topography of the stream simpler and the naturalness lower. The adaptive management plan was prepared to improve those problems, and a plan for creating an ecological network was recommended to enhance the restoration effect.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1424-1436
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• 2020

Although huge progress has been made in current image segmentation work, there are still no efficient segmentation strategies for tree image which is taken from natural environment and contains complex background. To improve those problems, we propose a method for tree image segmentation combining adaptive mean shifting with image abstraction. Our approach perform better than others because it focuses mainly on the background of image and characteristics of the tree itself. First, we abstract the original tree image using bilateral filtering and image pyramid from multiple perspectives, which can reduce the influence of the background and tree canopy gaps on clustering. Spatial location and gray scale features are obtained by step detection and the insertion rule method, respectively. Bandwidths calculated by spatial location and gray scale features are then used to determine the size of the Gaussian kernel function and in the mean shift clustering. Furthermore, the flood fill method is employed to fill the results of clustering and highlight the region of interest. To prove the effectiveness of tree image abstractions on image clustering, we compared different abstraction levels and achieved the optimal clustering results. For our algorithm, the average segmentation accuracy (SA), over-segmentation rate (OR), and under-segmentation rate (UR) of the crown are 91.21%, 3.54%, and 9.85%, respectively. The average values of the trunk are 92.78%, 8.16%, and 7.93%, respectively. Comparing the results of our method experimentally with other popular tree image segmentation methods, our segmentation method get rid of human interaction and shows higher SA. Meanwhile, this work shows a promising application prospect on visual reconstruction and factors measurement of tree.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.4
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• pp.586-594
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• 2018

In this paper, we propose a livestock theft detection system through moving object classification and tracking method. To do this, first, we extract moving objects using GMM(Gaussian Mixture Model) and RGB background modeling method. Second, it utilizes a morphology technique to remove shadows and noise, and recognizes moving objects through labeling. Third, the recognized moving objects are classified into human and livestock using skeletal features and color similarity judgment. Fourth, for the classified moving objects, CAM (Continuously Adaptive Meanshift) Shift and Kalman Filter are used to perform tracking and overlapping judgment, and risk is judged to generate a notification. Finally, several experiments demonstrate the feasibility and applicability of the proposed method.