• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.4
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• pp.153-160
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• 2016

A developed skill of an intelligent CCTV is also advancing by using its Image Acquisition Device. The most important part in the field of detecting comparatively fast moving objects is to effectively reduce the loads on updating the background image in order to achieve real-time update. However, the ability of the current general-purpose computer extracting the texture as characteristics has limits in application mostly due to the loads on processes. In this thesis, an algorithm for real-time updating the background image in an applied area such as detecting the fast moving objects like a driving car in a video of at least 30 frames per second is suggested and the performance is analyzed by a test of extracting object region from real input image.

• Journal of the Korea Society of Computer and Information
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• v.13 no.6
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• pp.1-12
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• 2008

This paper presents automatic moving object detection method using the rotating camera covering larger area with a single camera. The proposed method is based on the edge segment matching which robust to the dynamic environment with illumination change and background movement. The proposed algorithm presents an edge segment based background panorama image generation method minimizing the distortion due to image stitching, the background image generation method using Generalized Hough Transformation which can reliably register the current image to the panorama image overcoming the stitching distortions, the moving edge segment extraction method that overcome viewpoint difference and distortion. The experimental results show that the proposed method can detect correctly moving object under illumination change and camera vibration.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.8
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• pp.766-772
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• 2015

This paper proposes an object detection method based on motion estimation using background subtraction in the fisheye images obtained through omni-directional camera mounted on the vehicle. Recently, most of the vehicles installed with rear camera as a standard option, as well as various camera systems for safety. However, differently from the conventional object detection using the image obtained from the camera, the embedded system installed in the vehicle is difficult to apply a complicated algorithm because of its inherent low processing performance. In general, the embedded system needs system-dependent algorithm because it has lower processing performance than the computer. In this paper, the location of object is estimated from the information of object's motion obtained by applying a background subtraction method which compares the previous frames with the current ones. The real-time detection performance of the proposed method for object detection is verified experimentally on embedded board by comparing the proposed algorithm with the object detection based on LKOF (Lucas-Kanade optical flow).

• Journal of the Semiconductor & Display Technology
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• v.20 no.1
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• pp.18-24
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• 2021

The current settlement and distribution used in theme, background and signal music market other than conventional music is being carried out with either the comprehensive settlement method or the measured meter-rate settlement method in the payment process of collected user fees and compensation depending on the use-permission types. In this settlement and distribution process, however, the reliability issues are often being raised because of the difficulty of tracking rights due to changes in music source rights management information, etc, and the opaque settlement and distribution method itself. This paper proposes a new settlement and distribution platform using a blockchain for the reliable collection and distribution of copyright fees among music user group, monitoring organization group, trust organization group and copyright holders, based on the monitoring information of the theme, background and signal music usage. This platform also provides the transparency in settlement and distribution process among stakeholders through smart contract system.

• International Journal of Highway Engineering
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• v.19 no.6
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• pp.165-173
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• 2017

PURPOSES : The current practice in car headlight visibility performance evaluation is based on the luminous intensity and illuminance of headlight. Such practice can be inappropriate from a visibility point of view where visibility indicates abilities to perceive an object ahead on the road. This study aimed at evaluating the appropriateness of current headlight evaluation method. METHODS : This study measured the luminance of object and road surface at unlit roadways. The variables were measured by vehicle type and by headlight lamp type. Based on the measurements, the distance where drivers can perceive an object ahead was calculated and then compared against such distance obtained by conventional visibility performance evaluation. RESULTS : The evaluation method based on illuminance of headlight is not appropriate when viewed from the visibility concept that is based on object-perceivable distance. Further, the results indicated a shorter object-perceiving distance even when road surface luminance is higher, thereby suggesting that illuminance of headlight and luminance of road surface are not the representative indices of nighttime visibility. CONCLUSIONS : Considering that this study utilized limited vehicle types and that road surface (background) luminance can vary depending on the characteristics of the given road surface, it would likely go too far to argue that this study's visibility performance evaluation results can get generalized to other conditions. Regardless, there is little doubt that the current performance evaluation criterion which is based on illuminance, is unreasonable. There should be future endeavors on the current subject which will need to explore study conditions further, under which more experiments should be conducted and effective methodologies developed for evaluating automotive headlight visibility performance. Needs are recognized particularly in the development of headlight visibility performance evaluation methodology which will take into account road surface (background) luminance and luminance contrast from various perspectives as the former indicates the driver's perception of the front road alignment and the latter being indicative of object perception performance.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 1997.10a
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• pp.4-10
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• 1997

The fundamental philosophy underlying the seismic design of structures and systems are evolving into the performance based concept. The background and current status of this development in other countries are briefly summarized. The new code system which consists of two level seismic design criteria will be introduced. The implementation of the preformance based design concepts in the criteria will be explained.

• Publications of The Korean Astronomical Society
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• v.26 no.2
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• pp.55-70
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• 2011

Cosmological linear perturbation theory has fundamental importance in securing the current cosmological paradigm by connecting theories with observations. Here we present an explanation of the method used in relativistic cosmological perturbation theory and show the derivation of basic perturbation equations.

• Journal of Broadcast Engineering
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• v.22 no.6
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• pp.724-733
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• 2017

Conventional methods of automatically recording Go game positions do not properly consider obstacles (hand or object) on a Go board during the Go game. If the Go board is blocked by obstacles, the position of a Go stone may not be correctly recognized, or the sequences of moves may be stored differently from the actual one. In the proposed algorithm, only the complete Go board image without obstacles is stored as a background image and the obstacle is recognized by comparing the background image with the current input image. To eliminate the phenomenon that the shadow is mistaken as obstacles, this paper proposes the new obstacle detection method based on the gradient image instead of the simple differential image. When there is no obstacle on the Go board, the background image is updated. Finally, the successive background images are compared to recognize the position and type of the Go stone. Experimental results show that the proposed algorithm has more than 95% recognition rate in general illumination environment.

• Journal of the Ergonomics Society of Korea
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• v.36 no.3
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• pp.213-219
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• 2017

Objective: The present study identified the minimum legible text size by an experiment for eight combinations of background and text colors, which will be used in designing visual information on group-view display (GVD). Background: Information on minimum legible text size is needed to design the visual information presented on GVD in a radioactive waste control room. Method: The experiment was conducted for 22 male participants (age: mean = 37, SD = 6.7; visual acuity: over 0.8) who were recruited by considering demographic characteristics of current control room operators. Eight combinations of background and text colors were considered and the minimum legible text size was determined for each combination by applying the method of limits, one of psychophysical methods. Results: The minimum legible text size was significantly different in accordance with the combination of background and text colors. Statistical analysis results showed that luminance contrast and color contrast between background and text influenced the minimum legible text sizes. Conclusion: This study concluded that the minimum legible text size is 8 minute of arc for various combinations of background and text colors. Application: The minimum legible text size identified in the present study can be utilized in designing visual information on GVD at the main control room in a radioactive waste facility.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.889-894
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• 2009

Accompanied by the rapid development of Computer Vision, Visual surveillance has achieved great evolution with more and more complicated processing. However there are still many problems to be resolved for robust and reliable visual surveillance, and the cast shadow occurring in motion detection process is one of them. Shadow pixels are often misclassified as object pixels so that they cause errors in localization, segmentation, tracking and classification of objects. This paper proposes a novel cast shadow removal method. As opposed to previous conventional methods, which considers pixel properties like intensity properties, color distortion, HSV color system, and etc., the proposed method utilizes observations about edge patterns in the shadow region in the current frame and the corresponding region in the background scene, and applies Laplacian edge detector to the blob regions in the current frame and the background scene. Then, the product of the outcomes of application determines whether the blob pixels in the foreground mask comes from object blob regions or shadow regions. The proposed method is simple but turns out practically very effective for Gaussian Mixture Model, which is verified through experiments.