• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.5
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• pp.2430-2436
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• 2013

This study suggests a method of detecting the still object, which becomes a cause of danger within the crossroad. The Inverse Perspective Transform was performed in order to make the object size consistent by being inputted the real-time image from CCTV that is installed within the crossroad. It established the detection area in the image with the perspective transform and generated the adaptative background image with the use of the moving information on object. The detection of the stop object was detected the candidate region of the stop object by using the background-image differential method. To grasp the appearance of truth on the detected candidate region, a method is proposed that uses the gradient information on image and EHD(Edge Histogram Descriptor). To examine performance of the suggested algorithm, it experimented by storing the images in the commuting time and the daytime through DVR, which is installed on the cross street. As a result of experiment, it could efficiently detect the stop vehicle within the detection region inside the crossroad. The processing speed is shown in 13~18 frame per second according to the area of the detection region, thereby being judged to likely have no problem about the real-time processing.

• The KIPS Transactions:PartB
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• v.13B no.4 s.107
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• pp.463-470
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• 2006

It is difficult to track and extract the movement of an object through a camera exactly because of noises and changes of the light. The fast searching algorithm is necessary to extract the object and to track the movement for realtime image. In this paper, we propose the correct and fast algorithm using the variable searching area and the background image change method to robustic for the change of background image. In case the threshold value is smaller than reference value on an experimental basis, change the background image. When it is bigger, we decide it is the point of the time of the object input and then extract boundary point of it through the pixel check. The extracted boundary points detect precise movement of the object by creating area block of it and searching block that maintaining distance. The designed and embodied system shows more than 95% accuracy in the experimental results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.5
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• pp.1080-1088
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• 2004

In this paper, the interesting moving objects tracking algorithm using color information on Multi-Video camera against variance of intensity, shape and background is proposed. Moving objects are detected by using difference image method and integral projection method to background image and objects image only with hue area, after converting RGB color coordination of image which is input from multi-video camera into HSI color coordination. Hue information of the detected moving area are segmented to 24 levels from $0^{\circ}$ to $360^{\circ}$. It is used to the feature parameter of the moving objects that are three segmented hue levels with the highest distribution and difference among three segmented hue levels. To examine propriety of the proposed method, human images with variance of intensity and shape and human images with variance of intensity, shape and background are targeted for moving objects. As surveillance results of the interesting human, hue distribution level variation of the detected interesting human at each camera is under 2 level, and it is confirmed that the interesting human is tracked and surveilled by using feature parameters at cameras, automatically.

• Journal of Environmental Science International
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• v.21 no.4
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• pp.535-543
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• 2012

The aerosol number concentration have measured with an aerodynamic particle sizer spectrometer(APS) at Gosan site, which is known as background area in Korea, from January to September 2011. The temporal variation and the size distribution of aerosol number concentration have been investigated. The entire averaged aerosol number concentration in the size range 0.25~32.0 ${\mu}m$ is about 252 particles/$cm^3$. The number concentration in small size ranges(${\leq}0.5{\mu}m$) are very higher than those in large size ranges, such as, the number concentration in range of larger than 6.5 ${\mu}m$ are almost zero particles/$cm^3$. The contributions of the number concentration to PM10 and/or PM2.5 are about 34%, 20.1% and 20.4% in the size range 0.25~0.28 ${\mu}m$, 0.28~0.30 ${\mu}m$ and 0.30~0.35 ${\mu}m$, respectively, however, the contributions are below 1% in range of larger than 0.58 ${\mu}m$. The monthly variations in the number concentration in smaller size range(<1.0 ${\mu}m$) are evidently different from the variations in range of larger than 1.0 ${\mu}m$, but the variations are appeared similar patterns in smaller size range(<1.0 ${\mu}m$), also the variations in range of larger than 1.0 ${\mu}m$ are similar too. The diurnal variations in the number concentration for smaller particle(<1.0 ${\mu}m$) are not much, but the variations for larger particle are very evident. Size-fractioned aerosol number concentrations are dramatically decreased with increased particle size. The monthly differences in the size-fractioned number concentrations for smaller size range(<0.7 ${\mu}m$) are not observed, however, the remarkable monthly differences are observed for larger size than 0.7 ${\mu}m$.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.4 s.34
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• pp.3-9
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• 2005

The extraction of traffic information based on image processing is under broad research recently because the method based on image processing takes less cost and effort than the traditional method based on physical equipment. The main purpose of the algorithm based on image processing is to extract vehicles from an image correctly. Before the extraction, the algorithm needs the pre-processing such as background subtraction and binary image thresholding. During the pre-processing much noise is brought about because roadside tree and passengers in the sidewalk as well as vehicles are extracted as traffic flow. The noise undermines the overall accuracy of the algorithm. In this research, most of the noise could be removed by extracting the exact road area which does not include sidewalk or roadside tree. To extract the exact road area, traffic lanes in the image were used. Algorithm speed also increased. In addition, with the ratio between the sequential images, the problem caused by vehicles' shadow was minimized.

• Journal of Korea Multimedia Society
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• v.14 no.5
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• pp.607-613
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• 2011

In this paper, we propose a hand image segmentation method using the dynamic threshold values on input images with various lighting and background attributes. First, a moving hand silhouette is extracted using the camera input difference images, Next, based on the R,G,B histogram analysis of the extracted hand silhouette area, the threshold interval for each R, G, and B is calculated on run-time. Finally, the hand area is segmented using the thresholding and then a morphology operation, a connected component analysis and a flood-fill operation are performed for the noise removal. Experimental results on various input images showed that our hand segmentation method provides high level of accuracy and relatively fast stable results without the need of the fixed threshold values. Proposed methods can be used in the user interface of mixed reality applications.

• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.83-92
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• 2009

In this paper, an extended snake algorithm using color variance energy is proposed for segmenting an interest object in color image. General snake algorithm makes use of energy in image to segment images into a interesting area and background. There are many kinds of energy that can be used by the snake algorithm. The efficiency of the snake algorithm is depend on what kind of energy is used. A general snake algorithm based on active contour model uses the intensity value as an image energy that can be implemented and analyzed easily. But it is sensitive to noises because the image gradient uses a differential operator to get its image energy. And it is difficult for the general snake algorithm to be applied on the complex image background. Therefore, the proposed snake algorithm efficiently segment an interest object on the color image by adding a color variance of the segmented area to the image energy. This paper executed various experiments to segment an interest object on color images with simple or complex background for verifying the performance of the proposed extended snake algorithm. It shows improved accuracy performance about 12.42 %.

• Korean Journal of Remote Sensing
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• v.14 no.4
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• pp.366-375
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• 1998

Optical characteristics of the yellow sand and their influences on the ocean color remote sensing has been studied using ocean color sensor SeaWiFS measurements. Two cases of April 18 and April 25, 1998, representing yellow sand and background aerosol, are selected for emphasizing the impact of high aerosol concentration on the ocean color remote sensing. It was shown that NASA's standard atmospheric correction algorithm treats yellow sand area as either too high radiance or cloud area, in which ocean color information is not generated. Optical thickness of yellow sand arrived over the East Asian sea waters in April 18 indicates that there are two groups loaded with relatively homogeneous yellow sand, i.e.: heavy yellow sand area with optical thickness peak around 0.8 and mild area with about 0.4, which are consistent with ground observations. The movement of the yellow sand area obtained from surface weather maps and backward trajectory analysis manifest the notion that the weak yellow sand area was originated from the outer region of the dust storm. It is also noted that high optical thickness associated with the yellow sand is significantly different from what we may observe from background aerosol, which is about 0.2. These characteristics allow us to determine the yellow sand area with an aid of atmospheric correction parameter. Results indicate that the yellow sand area can be determined by applying the features revealed in scattergrams of atmospheric correction parameter and optical thickness.

• Journal of Fashion Business
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• v.10 no.1
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• pp.148-163
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• 2006

The purpose of this study is to examine differences in university students' spatial behavior and time for purchasing weekdays or weekends according to trading areas they use to purchase casual wears. Theoretical background examined trading areas, in Busan, consumers' spatial behavior. An empirical research developed a questionnaire as a measuring tool to conduct a preliminary survey and a main survey. Data collection was implemented with 507 students from four universities in Busan; and for data analysis, descriptive statistics, cross-tabulation analysis, correspondence analysis, and McNemar test were carried out by using the SPSS for Windows 12.0K program. This study obtained the main results as follows: The characteristics of university students' spatial behavior according to trading areas show significant difference in reasons of trading area selection, time slots for visiting. University students who visited the Seomyeon trading area were found to consider comparison-based purchasing and prominence of the trading area, regardless of the time for purchasing weekdays or weekends. As for trading areas around Busan National University, visits were mainly due to accessibility. Students visited trading areas in Nampo-Gwangbok-dong regardless of the time for purchasing in diverse reasons of trading area selection, time slots. As for trading areas around Kyungsung University, students were visited due to accessibility.

• Particle and aerosol research
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• v.7 no.3
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• pp.99-108
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• 2011

To establish area specific control strategies for the reduction of the ozone concentration, the Ozone Isopleth Plotting Package for Research(OZIPR) model has been widely used. However, the model results tend to changed by various input parameters such as the background concentration, emission amount of NOx and volatile organic compounds (VOCs), and meteorological condition. Thus, sensitivity analysis should be required to ensure the reliability of the result. The OZIPR modeling results for five local government districts in the Seoul Metropolitan Area (SMA) in June 2000 were used for the sensitivity analysis. The sensitivity analysis result showed that the modeling result of the SMA being VOC-limited region be still valid for a wide range of input parameters' variation. The estimated ozone concentrations were positively related with the initial VOCs concentrations while were negatively related with the initial NOx concentrations. But, the degree of the variations at each local district was different suggesting area specific characteristics being also important. Among the five local governments, Suwon was chosen to identify other variance through the period from April to September in 2000. The monthly modeling results show different ozone values, but still showing the characteristics of VOCs-limited region. Limitations due to not considering long range transport and transfer from neighbor area, limitation of input data, error between observed data and estimated data are all discussed.