• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2028-2031
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• 2003

This paper proposes a face identification algorithm, robust on lighting condition and complex background. The proposed method estimates facial area under bad light condition by expanding face color boundaries and then finds a lip using the templates for lips. Then the eyes are found using their topological relationship with the long and short axes of lip area. The experimental results have shown that the proposed algorithm is robust on lighting conditions and complex background.

• Proceedings of the Korean Society of Toxicology Conference
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• 2005.05a
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• pp.111-111
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• 2005

• The Research Journal of the Costume Culture
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• v.16 no.5
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• pp.863-877
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• 2008

The purpose of this study is to investigate the effect of dot pattern size(0.8, 1.8, 2.5, 5, 8), color combination (BG/R, Y/B), value tone(lt/dk, p/g), area-ratio on image information. Sets of stimulus and response scales(7 point semantic) were used as experimental materials. The stimuli were 20 color pictures manipulated with the combination of dot pattern size, color combination, value tone and area-ratio using computer simulation. The subjects were 240 female undergraduates living in Gyeongsangnam-do. Image factor of the stimulus was composed of 4 different components, visibility, chastity.feminity, cuteness and attractiveness. In the visibility, color combination, value tone, area-ratio, dot pattern size showed independent effect. In the chastity feminity, color combination, value tone, showed independent effect. In the cuteness, value tone, area-ratio, dot pattern size showed independent effect. Significant interaction effects of color and area-ratio combination on visibility and cuteness were found. Interaction efforts of color and value tone combination, value tone and area-ratio was significant on cuteness. For visibility image, BG/R combination of color and yellow background/blue dots were effective. For cuteness image, pale/grayish tone and background/dots area-ratio were effective.

• Journal of the Korean Society of Costume
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• v.58 no.6
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• pp.54-68
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• 2008

The purpose of this study is to investigate the effect of dot pattern size(0.8, 1.8, 2.5, 5, 8), color combination(BG/R, Y/B), area-ratio on image formation. Sets of stimulus and response scales(7 point semantic) were used as experimental materials. The stimuli were 20 color pictures manipulated with the combination of dot pattern size, color combination, and area-ratio using computer simulation. The subjects were 240 female undergraduates living in Gyeongnam-do. Image factor of the stimulus was composed of 5 different components, visibility, attractiveness, cuteness, stability and high class image. In the cuteness, color combination, dot pattern size showed independent effect. In the stability, area-ratio, dot pattern size showed independent effect. Interaction effects of color and area-ratio combination was significant on cuteness. For visibility image 8cm yellow dot/blue background, for attractiveness image BG/R coloration, for cuteness image Y/B coloration and for stability image 0.8cm yellow dot/blue background were effective. According to the variation of dot pattern size, color combination and area-ratio, it was investigated that the images for a dress wearer were expressed diversely, were shown differently in image dimensions, and could be produced to different images.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.11
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• pp.105-114
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• 2015

This paper proposes methods to remove background area and segment region of interest (ROI) in chest X-ray images. Conventional algorithms to improve detail or contrast of images normally utilize brightness and frequency information. If we apply such algorithms to the entire images, we cannot obtain reliable visual quality due to unnecessary information such as background area. So, we propose two effective algorithms to remove background and segment ROI from the input X-ray images. First, the background removal algorithm analyzes the histogram distribution of the input X-ray image. Next, the initial background is estimated by a proper thresholding on histogram domain, and it is removed. Finally, the body contour or background area is refined by using a popular guided filter. On the other hand, the ROI, i.e., lung segmentation algorithm first determines an initial bounding box using the lung's inherent location information. Next, the main intensity value of the lung is computed by vertical cumulative sum within the initial bounding box. Then, probable outliers are removed by using a specific labeling and the pre-determined background information. Finally, a bounding box including lung is obtained. Simulation results show that the proposed background removal and ROI segmentation algorithms outperform the previous works.

• International Journal of Contents
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• v.9 no.1
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• pp.6-10
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• 2013

Foreground estimation in object segmentation has been an important issue for last few decades. In this paper we propose a GrabCut based automatic foreground estimation method using block clustering. GrabCut is one of popular algorithms for image segmentation in 2D image. However GrabCut is semi-automatic algorithm. So it requires the user input a rough boundary for foreground and background. Typically, the user draws a rectangle around the object of interest manually. The goal of proposed method is to generate an initial rectangle automatically. In order to create initial rectangle, we use Gabor filter and Saliency map and then we use 4 features (amount of area, variance, amount of class with boundary area, amount of class with saliency map) to categorize foreground and background. From the experimental results, our proposed algorithm can achieve satisfactory accuracy in object segmentation without any prior information by the user.

• Journal of the Korean Institute of Landscape Architecture
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• v.19 no.4
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• pp.58-79
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• 1992

This is a study of Sadaebu(previllaged class in a Yi-Dynasty士 大夫) clan villages in the Andong Area with emphasis on Formantion Process of development. The purposes and the contents of this study are as following : 1. To review the process and the background fo growth of Myung-Mun-Se-Ga(名文大家:the traditional famed & mighty clans) in Yi-Dynasty, in cases of Andong(安東) province. 2. To analyze about formation process of a sphere of their homogeneous clan villages, and to understand the factors affecting their sphere. 3. To identity the background factor of formation of their sphere of traditional clan villages in Andong province.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.6
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• pp.797-807
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• 2008

This paper proposes a new algorithm of extracting forward vehicle areas using the acquired lanes and road area information on road images with complex background to improve the efficiency of the vehicle detection. In the first stage, lanes are detected by taking into account the connectivity among the edges which are determined from a method of chain code. Once the lanes proceeding to the same direction with the running vehicle are detected, neighborhood roadways are found from the width and vanishing point of the acquired roadway of the running vehicle. And finally, vehicle areas, where forward vehicles are located on the road area including the center and neighborhood roadways, are extracted. Therefore, the proposed scheme of extracting forward vehicle area improves the rate of vehicle detection on the road images with complex background, and is highly efficient because of detecting vehicles within the confines of the acquired vehicle area. The superiority of the proposed algorithm is verified from experiments of the vehicle detection on road images with complex background.

• Journal of Korean Society of Water and Wastewater
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• v.24 no.5
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• pp.495-508
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• 2010

The aim of this study is to develop a quantified water loss Index to evaluate and manage leakage scientifically for the reduction of non-revenue water in water distribution systems. For the purpose, unavoidable background leakage suggested from UK water industry and IWA, and allowable water leakage in accord with the concept of allowable water loss are proposed by analyzing the inflow into two study water districts and the short-term water use of each customer in the districts. The study distribution areas are selected among the metered districts with good maintenance of leakage after improvement activities in Nonsan, medium sized city in Korea. Estimation models of allowable leakage are developed by metering and analyzing the minimum night flow at residential and commercial areas in the city. In the results of the investigation, it is estimated that background night flow in residential area was larger than that of commercial area where the types of business shows small water use characteristics. Meanwhile, night flow and background water loss on internal plumbing systems show great differences for each district which is influenced much by the water use characteristics and facilities scale. Based on metering water use data in various districts, leakage management criteria can be established under the consideration of domestic conditions in Korea by analyzing separated real water use and background leakage and it is possible to apply into presentation of optimal leakage level and reasonable time for working activities for leakage reduction.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.269-276
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• 2010

In this paper, we present the detection method of moving objects based on two background models. These background models support to understand multi layered environment belonged in images taken by shaking camera and each model is MBM(Multiple Background Model) and TMBM (Temporal Median Background Model). Because two background models are Pixel-based model, it must have noise by camera movement. Therefore correlation coefficient calculates the similarity between consecutive images and measures camera motion vector which indicates camera movement. For the calculation of correlation coefficient, we choose the selected region and searching area in the current and previous image respectively then we have a displacement vector by the correlation process. Every selected region must have its own displacement vector therefore the global maximum of a histogram of displacement vectors is the camera motion vector between consecutive images. The MBM classifies the intensity distribution of each pixel continuously related by camera motion vector to the multi clusters. However, MBM has weak sensitivity for temporal intensity variation thus we use TMBM to support the weakness of system. In the video-based experiment, we verify the presented algorithm needs around 49(ms) to generate two background models and detect moving objects.