• Journal of the Korea Society of Computer and Information
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• v.22 no.6
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• pp.131-140
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• 2017

As video equipments such as CCTV are used for various purposes in fields of society, digital video data processing technology such as automatic motion detection is essential. In this paper, we proposed and implemented a more stable and accurate motion detection system based on background subtraction technique. We could improve the accuracy and stability of motion detection over existing methods by efficiently processing color information of digital image data. We divided the procedure of color information processing into each components of color information : brightness component, color component of color information and merge them. We can process each component's characteristics with maximum consideration. Our color information processing provides more efficient color information in motion detection than the existing methods. We improved the success rate of motion detection by our background update process that analyzed the characteristics of the moving background in the natural environment and reflected it to the background image.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.11
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• pp.1089-1095
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• 2010

We propose an image segmentation method for auto-teaching system of PCB (Printed Circuit Board) assembly inspection machines. The inspection machine acquires images of all components in PCB, and then compares each image with its standard image to find the assembly errors such as misalignment, inverse polarity, and tombstone. The component window that is the area of component to be acquired by camera, is one of the teaching data for operating the inspection machines. To reduce the teaching time of the machine, we newly develop the image processing method to extract the component window automatically from the image of PCB. The proposed method segments the component window by excluding the soldering parts as well as board background. We binarize the input image by use of HSI color model because it is difficult to discriminate the RGB colors between components and backgrounds. The linear combination of the binarized images then enhances the component window from the background. By use of the horizontal and vertical projection of histogram, we finally obtain the component widow. The experimental results are presented to verify the usefulness of the proposed method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.4
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• pp.361-369
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• 2002

In order to extract motion features from an input image acquired by a static CCD-camera in a restricted area, we need a robust algorithm to cope with noise sensitivity and condition change. In this paper, we proposed an efficient algorithm to extract and track motion features in a noisy environment or with sudden condition changes. We extract motion features by considering a change of neighborhood pixels when moving objects exist in a current frame with an initial background. To remove noise in moving regions, we used a morphological filter and extracted a motion of each object using 8-connected component labeling. Finally, we provide experimental results and statistical analysis with various conditions and models.

• Journal of Digital Contents Society
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• v.8 no.3
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• pp.329-339
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• 2007

In this paper we present a facial region detection algorithm for real-time image with complex background and various illumination using spatial and temporal methods. For Detecting Human region It used summation of Edge-Difference Image between continuous image sequences. Then, Detected facial candidate region is vertically divided two objected. Non facial region is reduced using Analysis of Major Color Component. Non facial region has not available Major Color Component. And then, Background is reduced using boundary information. Finally, The Facial region is detected through horizontal, vertical projection of Images. The experiments show that the proposed algorithm can detect robustly facial region with complex background various illumination images.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.955-958
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• 2005

In this study, the wind load characteristics for a transmission tower is investigated considering the effect of the transmission lines through stochastic analysis. The assemblage of the transmission line and insulator are modeled as a double pendulum system connected to the SDOF model of the tower It is observed that the background component of the overturing moment induced by the wind response of the transmission line has considerable portion in the total overturning moment. Based on this result, a rotational viscoelastic damper (VED) is proposed for the mitigation of the transmission line reactions, which act as wind load transferred to the tower. To verify the effectiveness of the proposed strategy, time history analysis is conducted for different wind velocities and VED damping constants. From the analysis, the proposed VED is proved to be effective for mitigation of the background component rather than the resonance component of the transmission line reaction.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.185-189
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• 2004

For face recognition system, a face detector which can find exact face region from complex image is needed. Many face detection algorithms have been developed under the assumption that background of the source image is quite simple . this means that face region occupy more than a quarter of the area of the source image or the background is one-colored. Color-based face detection is fast but can't be applicable to the images of which the background color is similar to face color. And the algorithm using neural network needs so many non-face data for training and doesn't guarantee general performance. In this paper, A multi-scale, multi-face detection algorithm using PCA is suggested. This algorithm can find most multi-scaled faces contained in static images with small number of training data in reasonable time.

• Journal of the Korean Institute of Educational Facilities
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• v.14 no.4
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• pp.86-95
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• 2007

This study clarifies the theoretical background and the floor plan characteristics of component schools in Small Schools Complexes. The recent researches have proved the enhancement of students' social relationship and school security in the new school environment. The findings fur the characteristics by analyzing the component schools from six school complexes follow: (1) Students can access their classrooms in component schools through main entrances, shared corridors and private corridors. (2) Teachers' area is segregated from students' area, which does not encourage the social relationship between teachers and students. (3) Some of special classrooms, which are generally considered as shared facilities in a Small Schools Complex, are planned within component schools for accommodating specialized educational programs. (4) A component school occupying multiple floors reduces Intelligibility of space and chances of users' visual contact to colleagues. Finally, this study proposed the alternative floor planning directions in order to improve users' social relationship in a component school.

• Journal of Communications and Networks
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• v.12 no.2
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• pp.191-197
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• 2010

In this paper, we propose a novel methodology to identify border gateway protocol (BGP) updates associated with major events - affecting network reachability to multiple ASes - and separate them (statistically) from those attributable to minor events, which individually generate few updates, but collectively form the persistent background noise observed at BGP vantage points. Our methodology is based on principal component analysis, which enables us to transform and reduce the BGP updates into different AS clusters that are likely affected by distinct major events. We demonstrate the accuracy and effectiveness of our methodology through simulations and real BGP data.

• Journal of the Korea Society of Computer and Information
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• v.15 no.1
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• pp.91-102
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• 2010

It is very difficult that a previous surveillance system and vehicle detection system find objects on a limited and unstable illumination condition. This paper proposes a robust method of adaptively updating a reference background image for solving problems that are generated by the unstable illumination. The first input image is set up as the reference background image, and is divided into three block categories according to an edge component. Then a block state analysis, which uses a rate of change of the brightness, a stability, a color information, and an edge component on each block, is applied to the input image. On the reference background image, neighbourhood blocks having the same state of a updated block are merged as a block. The proposed method can generate a robust reference background image because it distinguishes a moving object area from an unstable illumination. The proposed method very efficiently updates the reference background image from the point of view of the management and the processing time. In order to demonstrate the superiority of the proposed stable manner in situation that an illumination quickly changes.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.4
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• pp.87-98
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• 2011

Detecting a moving object from videos and tracking it are basic and necessary preprocessing steps in many video systems like object recognition, context aware, and intelligent visual surveillance. In this paper, we propose a method that is able to detect a moving object quickly and accurately in a condition that background and light change in a real time. Furthermore, our system detects strongly an object in a condition that the target object is covered with other objects. For effective detection, effective Eigen-space and FCM are combined and employed, and a CONDENSATION algorithm is used to trace a detected object strongly. First, training data collected from a background image are linear-transformed using Principal Component Analysis (PCA). Second, an Eigen-background is organized from selected principal components having excellent discrimination ability on an object and a background. Next, an object is detected with FCM that uses a convolution result of the Eigen-vector of previous steps and the input image. Finally, an object is tracked by using coordinates of an detected object as an input value of condensation algorithm. Images including various moving objects in a same time are collected and used as training data to realize our system that is able to be adapted to change of light and background in a fixed camera. The result of test shows that the proposed method detects an object strongly in a condition having a change of light and a background, and partial movement of an object.