• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.245-248
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• 2002

This paper has been studied a new method to update the background image of a visual surveillance system which is not stationary. In order to do this, we use another background model designed with the whole monitored images in a regular time period. By comparing each changed area computed from the two background model images and current monitored image, the areas which will be updated are decided.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.69-76
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• 2010

The segmentation of moving object in video sequence is a core technique of intelligent image processing system such as video surveillance, traffic monitoring and human tracking. A typical method to segment a moving region from the background is the background subtraction. The steps of background subtraction involve calculating a reference image, subtracting new frame from reference image and then thresholding the subtracted result. One of famous background modeling is Gaussian mixture model (GMM). Even though the method is known efficient and exact, GMM suffers from a problem that includes false pixels in ROI (region of interest), specifically shadow pixels. These false pixels cause fail of the post-processing tasks such as tracking and object recognition. This paper presents a method for removing false pixels included in ROT. First, we subdivide a ROI by using shape characteristics of detected objects. Then, a method is proposed to classify pixels from using histogram characteristic and comparing difference of energy that converts the color value of pixel into grayscale value, in order to estimate whether the pixels belong to moving object area or shadow area. The method is applied to real video sequence and the performance is verified.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.108-116
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• 2008

In this paper, we propose the algorithm for making panoramic background and object tacking using pan-tilt-zoom camera. We draw an analogy relation between images for cylinder projection, rearrange of images, stitching, and blending. We can then make the panoramic background, and can track the object use the panoramic background. After generated the background, the proposed algorithm tracks the moving object. Therefore it can detect the wide area, and it tracks the object continuously. So the proposed algorithm is able to use at wide area to detect and track the object.

• Journal of Environmental Health Sciences
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• v.45 no.5
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• pp.474-486
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• 2019

Objectives: This study was performed to investigate the emission characteristics of aldehydes emitted by the printing industry and to evaluate their impact on adjacent residential areas. Methods: Aldehydes and THC were measured from the front of the control device in the printing and coating process. Aldehydes and ketones were measured by workplace area, residential area, and background area to evaluate their impact. Results: The concentrations of formaldehyde (<0.047 ppm) and acetaldehyde (<0.068 ppm) in the printing and coating process were relatively low, and the methyl ethyl ketone used as the primary solvent was the main carbonyl compound in the printing process. The daily mean concentrations of formaldehyde and acetaldehyde were not significantly different by workplace area, residential area, or background area. However, the concentration of methyl ethyl ketone was high in the order of workplace area, residential area, and background area. Conclusions: The concentrations of formaldehyde and acetaldehyde in the adjacent residential areas are considered to be more influenced by secondary sources of photochemical reactions than by primary sources. Methyl ethyl ketone is considered to be highly influenced by the primary source, which is printing facilities.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1678-1680
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• 2002

Stereo matching technique is used in many practical fields like satellite image analysis and computer vision. In this paper, we suggest a method to extract a target object image from a complicated background. For example, human face image can be extracted from random background. This method can be applied to computer vision such as security system, dressing simulation by use of extracted human face, 3D modeling, and security system. Many researches about stereo matching have been performed. Conventional approaches can be categorized into area-based and feature-based method. In this paper, we start from area-based method and apply area tracking using scanning window. Coarse depth information is used for area merging process using area searching data. Finally, we produce a target object image.

• Journal of Digital Contents Society
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• v.13 no.3
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• pp.439-449
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• 2012

Recently, many interactive artworks produce through convergence of art and scientific technology. Artists or designers should cooperate with other areas for analysis in order to share database. According to these requirements, In this study, we analyze Kandinsky's works which are more emphasis on subject area than the emphasis to background area by using a number of colors, faces, and brightness levels. Due to this approach, it determines how to represent for stable screen composition attracting viewer's eyes. As a result, the subject area has more a number of colors, faces, and brightness levels than the background area. In addition, we produce the interactive artwork based on the analyzed data. According to the requirement of convergence and collaboration in the historical background, this study will be able to contribute to make the collaboration by sharing common information between artists and professionals in other areas. In addition, it is expected that other production makers who do not have the background of arts education will be able to configure the visual screen.

• Journal of Korea Game Society
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• v.11 no.2
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• pp.161-166
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• 2011

In this paper, we propose a novel background segmentation and feature point extraction method of a human motion for the augmented reality game. First, our method transforms input image from RGB color space to HSV color space, then segments a skin colored area using double threshold of H, S value. And it also segments a moving area using the time difference images and then removes the noise of the area using the Hessian affine region detector. The skin colored area with the moving area is segmented as a human motion. Next, the feature points for the human motion are extracted by calculating the center point for each block in the previously obtained image. The experiments on various input images show that our method is capable of correct background segmentation and feature points extraction 12 frames per second.

• Bulletin of the Korean Chemical Society
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• v.23 no.2
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• pp.301-308
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• 2002

As part of perfluorocarbon (PFC) tracer release experiment conducted at the western coastal area of Korea in February 2001, the background concentration level of perfluorocarbons (PFCs) in the atmosphere was determined by gas chromatography with electron capture detector. Prior to the PFC tracer release experiment in the field, air samples were collected using active samplers and the background concentrations of PFCs were determined. The concentrations of perfluoromethylcyclohexane ($C_7F_{14}$, PMCH) in the western coastal area of Korea were in the range of 5.8-8.7 fL/L. The mean concentration of the PMCH in the region exhibited no significant spatial and temporal variations. This concentration level is somewhat higher and has larger standard deviation than those of studies previously conducted in USA and Europe on the background concentration levels of PFCs. Because the background concentration of PMCH in Korea is still very low and consistent temporally and spatially, the PMCH tracer can be used suitably for the studies of long-range atmospheric transport.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.159-161
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• 2004

Many motion object detection algorithms rely on the process of background subtraction, an important technique that is used for detecting changes from a model of the background scene. This paper propose a novel method to update the background model image of a visual surveillance system which is not stationary. In order to do this, we use a background model based on statistical qualities of monitored images and another background model that excluded motions. By comparing each changed area computed from the two background model images and current monitored image, the areas that will be updated are decided.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.35-38
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• 2003

In this paper, I propose an automatic background extraction method and continuous background updating technique. Because there is a movement of a vehicle and a change of a background is feeble, the area moving through the time axis is looked for and a background and a vehicle image is divided. A way to give dynamically the threshold which divides the image frame into a vehicle image and the background in a space is enforced. Through the repetition of the above-mentioned process, the background pictorial image is gained. Using the karlman filter technique, the update is done so that a background image can obey a climate situation and an environmental change in day and night. A background image processed algorithm is better than the existent one. Through simulation, the feasibility of the algorithm has been verified.