• Proceedings of the Korean Information Science Society Conference
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• 2010.06c
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• pp.447-451
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• 2010

In this paper, we propose a simple but effective algorithm to increase the speed of Emphysema region classification. Emphysema region classification method based on CT image consumes a lot of time because of the large number of subregions due to the large size of CT image. Some of the sub-regions contain no Emphysema and the classification of these regions is worthless. To speed up the classification process, we create an algorithm to select Emphysema region candidates and only use these candidates in the Emphysema region classification instead of all of the sub-regions. First, the lung region is detected. Then we threshold the lung region and only select the dark pixels because Emphysema only appeared in the dark area of the CT image. Then the thresholded pixels are clustered into a region that called the Emphysema pre-detected region or Emphysema region candidate. This region is then divided into sub-region for the Emphysema region classification. The experimental result shows that Emphysema region classification using predetected Emphysema region decreases the size of lung region which will result in about 84.51% of time reduction in Emphysema region classification.

• Journal of Cadastre & Land InformatiX
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• v.48 no.2
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• pp.213-225
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• 2018

For constructing three-dimensional (3D) spatial information occlusion region problem arises in the process of taking the texture of the building. In order to solve this problem, it is necessary to investigate the automation method to automatically recognize the occlusion region, issue it, and automatically complement the texture. In fact there are occasions when it is possible to generate a very large number of structures and occlusion, so alternatives to overcome are being considered. In this study, we attempt to apply an approach to automatically create an occlusion region based on learning by patterning the blocked region using the recently emerging deep learning algorithm. Experiment to see the performance automatic detection of people, banners, vehicles, and traffic lights that cause occlusion in building walls using two advanced algorithms of Convolutional Neural Network (CNN) technique, Faster Region-based Convolutional Neural Network (R-CNN) and Mask R-CNN. And the results of the automatic detection by learning the banners in the pre-learned model of the Mask R-CNN method were found to be excellent.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.5 s.311
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• pp.30-36
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• 2006

In this paper, a new type of written image segmentation based on relative comparison of region areas is proposed. The original image is composed of two distinctive regions; information and background. Compared with this binary original image, the observed one is the gray scale which is represented with complex regions with speckles and noise due to degradation or contamination. For applying threshold or statistical approach, there occurs the region-deformation problem in the process of binarization. At first step, the efficient iterated conditional mode (ICM) which takes the lozenge type block is used for regions formation into the binary image. Secondly the information region is estimated through selecting action and restored its primary state. Not only decision of the attachment to a region but also the calculation of the magnitude of its area are carried on at each current pixel iteratively. All region areas are sorted into a set and selected through the decision parameter which is obtained statistically. Our experiments show that these approaches are effective on ink-rubbed copy image (拓本 'Takbon') and efficient at shape restoration. Experiments on gray scale image show promising shape extraction results, comparing with the threshold-segmentation and conventional ICM method.

• Proceedings of the Korean Society of Rural Planning Conference
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• 1998.10a
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• pp.25-27
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• 1998

The objective of this study is by analyzing villages("Ri" units) to specify the proper unit of the area that the rural development policy is suitable for, and to examine whether the current rural development policy considers the characteristics of community and region. The study included twelve districts(in Korean "Eup" or "Myun") and one hundred one villages(in Korean ri) in Poryong-si, Chungchungnam-do. Twelve and fifteen variables are respectively employe for the analysis of Myun`s and Ri`s. Using Factor Analysis, Cluster Analysis, and Z-Score Analysis, the study examines the degree of disadvantage and the process of growth pattern of each Myun or Ri. The Ri`s are also classified according to their functional characteristics. The results of this study could be summarized as follows; 1) There exist some problems in the current rural development policy because it does not take into consideration the characteristics community and region. 2) Except a few distinct of areas, the proper unit of the area for the rural development policy should be set being based on regional characteristics rather than the administrative units. 3) The spatial boundary of rural development policy should be sets from villages(ri) to beyond the unit of administrative units("Si" or "Gun"), according to the village unit analysis. 4) It is needed that community and region data should be consistently accumulated after specifying Standard Statistical Districts. 5) The application of indicators should be in accordance with the characteristics of the policy.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.185-186
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• 2006

Image Guided Surgery(IGS) system has been developed to provide exquisite and objective information to surgeons for surgical operation process. It is necessary that registration technique is important to match between 3D image model reconstructed from image modalities and the object operated by surgeon. Majority techniques of registration in IGS system have been used by recognizing fiducial markers placed on the object. However, this method has been criticized due to its invasive protocol inserting fiducial markers in patient's bone. Therefore, shape-based registration technique using geometric characteristics of the object has been invested to improve the limitation of IGS system. During Total Knee Replacement(TKR) operation, it is challenge to register with high accuracy by using shape-based registration because the area to acquire sample data from knee is limited. We have developed region-based 3D registration technique based on anatomical landmarks on the object and this registration algorithm was evaluated in femur model. It was found that region-based algorithm can improve the accuracy in 3D registration. We expect that this technique can efficiently improve the IGS system.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.7 no.1
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• pp.55-60
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• 2014

In this paper, we proposed a method for face region extraction by skin-color hue, saturation and facial feature extraction in natural images. The proposed algorithm is composed of lighting correction and face detection process. In the lighting correction step, performing correction function for a lighting change. The face detection process extracts the area of skin color by calculating Euclidian distances to the input images using as characteristic vectors color and chroma in 20 skin color sample images. Eye detection using C element in the CMY color model and mouth detection using Q element in the YIQ color model for extracted candidate areas. Face area detected based on human face knowledge for extracted candidate areas. When an experiment was conducted with 10 natural images of face as input images, the method showed a face detection rate of 100%.

• Journal of the Korean Society of Marine Environment & Safety
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• v.19 no.6
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• pp.606-611
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• 2013

In this study, the regional states of 7 items are analyzed, the regional risks are calculated by using normalized data & analysis hierarchy process to set regional oil recovery capacity. Area on-water oil recovery capacity, $7,500k{\ell}$, is separated and regional on-water oil recovery capacity is determined, based on calculated regional degree of risk. Excessive current oil recovery capacities, setting in Incheon, Gunsan, Mokpo, Busan region, are as a result distributed to the other regions in each area. In case of central region, Daesan is increased as much as $1,475k{\ell}$, Yeosu is increased as much as $375k{\ell}$, Ulsan is increased as much as $475k{\ell}$. The regional on-water oil recovery capacity, considering both the cause of accident aspects and marine environmental & economic aspects, is estimated as more balanced distribution model, compared to current standard of on-water oil recovery capacity.

• Journal of Advanced Marine Engineering and Technology
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• v.32 no.4
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• pp.630-636
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• 2008

Monitoring the location of the shoreline and foreshore changes through the time and core tasks are carried out by coastal engineers for a wide range of research. With the advent of digital imaging technology, the shore-based video monitoring system provides many advantages than field surveys. This study presents the development and construction(installation) of video monitoring system to assist the study of coastal and shoreline dynamics and evolution, especially sandbar variation at the Nakdong river estuary. For the purpose of this study, at high building near the Dadea-po beach (St. 2) and Jinudo(island) (St. 1) foreshore region, where coastline variation is highly active, 5 video cameras installed; the coastline movement has monitored since Aug. 2007 using the systems. From the image results of video camera, the 'Spit' type sandbar appears at the foreshore region of Doyodeung and Dadea-po beach and measured the deposition process of Jinudo(island) foreshore region. As a result, the monitoring system using video-based technique built in this study would be able to identify changes in the area and width of shoreline and beach of Nakdong river estuary.

• Journal of the Semiconductor & Display Technology
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• v.9 no.2
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• pp.79-85
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• 2010

In this paper, we propose a web inspection system (WIS) for real-time detection of paper defects which can cause critical fractures during papermaking process. Our system incorporates high speed line-scan camera, lighting system, and detection algorithm to provide robust and precise detection of paper defects in real-time. Since edge defects are very crucial to the paper fractures, our system focuses on the edge region of the paper instead of inspecting the whole paper area. In our algorithm, image projection and sub-pixel operation are utilized to detect the edge defects precisely and connected component labeling and shape analysis techniques are adopted to extract various kinds of the region defects. Experimental results revealed that our web inspection system is very efficient for detecting paper defects during papermaking processes.

• The Journal of Korea Robotics Society
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• v.11 no.1
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• pp.1-8
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• 2016

In this paper, we propose a new algorithm of the guidance line extraction for autonomous agricultural robot based on vision camera in paddy field. It is the important process for guidance line extraction which finds the central point or area of rice row. We are trying to use the central region data of crop that the direction of rice leaves have convergence to central area of rice row in order to improve accuracy of the guidance line. The guidance line is extracted from the intersection points of extended virtual lines using the modified robust regression. The extended virtual lines are represented as the extended line from each segmented straight line created on the edges of the rice plants in the image using the Hough transform. We also have verified an accuracy of the proposed algorithm by experiments in the real wet paddy.