• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.177-179
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• 2005

This paper suggests a high-speed blurred blob image inspection algorithm. When we inspect some products using high-resolution camera, the detected blob images usually have severe blur. And the blur makes it hard to detect an object. There are many blur-processing algorithms, but most of them have no real-time property for high-speed applications at all. In this paper, an MMX technology based algorithm is suggested. The suggested algorithm was found to be effective to detect the blurred blob images via many simulations and long time real-plant experiments.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.04a
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• pp.459-464
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• 2004

In this paper, an autonomous navigation system for autonomous guided vehicles (AGVs) operated in an automated container terminal is designed. The navigation system is based on the sensors detecting the range and bearing. The navigation algorithm used is an interacting multiple model (IMM) algorithm to detect other AGVs and avoid other obstacles using informations obtained from multiple sensors. As models to detect other AGVs (or obstacles), two kinematic models are derived： Constant velocity model for linear motion and constant speed turn model for curvilinear motion. For constant speed turn model, an unscented Kalman filter (UKF) is used because of drawbacks of the extended Kalman filter (EKF) in nonlinear system. The suggested algorithm reduces the root mean squares error for linear motions, while it can rapidly detect possible turning motions.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08a
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• pp.356-359
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• 2007

Writable Cholesteric Liquid Crystal Display and the algorithm used to detect its image were developed. We could use any hard tip, ex: the tip of a forefinger, to directly write an image on the surface of Cholesteric Liquid Crystal Display (CHLCD). By measuring the capacitance of one pixel of test cell (12mm x 15mm/1x1), F-state or P-state could be detected. By measuring the capacitance of one pixel of 4.1" CHLCD (241um x 241um/ 320x320), F-state or Pstate could not be detected, due to the effect of parasitic capacitance. Therefore, high frequency measurement and the algorithm were developed to detect the image on CHLCD.

• Journal of the Semiconductor & Display Technology
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• v.17 no.4
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• pp.105-108
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• 2018

Face Detection is an essential first step of the face recognition, and this is significant effects on face feature extraction and the effects of face recognition. Face detection has extensive research value and significance. In this paper, we present and analysis the principle, merits and demerits of the classic AdaBoost face detection and ASM algorithm based on point distribution model, which ASM solves the problems of face detection based on AdaBoost. First, the implemented scheme uses AdaBoost algorithm to detect original face from input images or video stream. Then, it uses ASM algorithm converges, which fit face region detected by AdaBoost to detect faces more accurately. Finally, it cuts out the specified size of the facial region on the basis of the positioning coordinates of eyes. The experimental result shows that the method can detect face rapidly and precisely, with a strong robustness.

• Journal of KIISE:Information Networking
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• v.35 no.6
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• pp.474-481
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• 2008

Scanning worm increases network traffic load and result in severe network congestion because it is a self-replicating worm and send copies of itself to a number of hosts through the Internet. So an early detection system which can automatically detect scanning worms is needed to protect network from those attacks. Although many studies are conducted to detect scanning worms, most of them are focusing on the method using packet header information. The method using packet header information has long detection delay since it must examine the header information of all packets entering or leaving the network. Therefore we propose an algorithm to detect scanning worms using network traffic characteristics such as variance of traffic volume, differentiated traffic volume, mean of differentiated traffic volume, and product of mean traffic volume and mean of differentiated traffic volume. We verified the proposed algorithm by analyzing the normal traffic captured in the real network and the worm traffic generated by simulator. The proposed algorithm can detect CodeRed and Slammer which are not detected by existing algorithm. In addition, all worms were detected in early stage: Slammer was detected in 4 seconds and CodeRed and Witty were detected in 11 seconds.

• The KIPS Transactions:PartB
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• v.12B no.5 s.101
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• pp.617-630
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• 2005

General scene change detection determines the changes of a scene by using feature comparison of two continuous images that are above the fixed threshold. But existing algerian detects scene change that was used in comparing the features of two images continuously, it usually takes a lot of time in decrypting the image data and false-detection problem occurs when there is an object motion or a change of illumination. In this paper, macroblock were used to extract the information directly from the MPEG compression area and suggests algorithm that will detect scene changes more effectively. Existing algorithm have shown numerous arithmetic problems that were improved in the proposed algorithm. The existing algorithm cannot detect the changes of a scene after analyzing the relationship of the previousand futureimages while the algorithm being proposed can detect the changes of a scene continuously and resolves the problem of false-detection. To this end, the data used in general were tested to prove that this algerian would be able to detect the scene changes faster and more correctly than the existing ones. The performance of the suggested algorithm was analyzed basedontheresultsoftheexperiment. .

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.2
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• pp.71-77
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• 2017

This paper proposes a low complexity frequency modulated continuous wave (FMCW) surveillance radar algorithm. In the conventional surveillance radar systems, the two dimensional (2D) fast Fourier transform (FFT) method is usually employed in order to detect the distance and velocity of the targets. However, in a surveillance radar systems, it is more important to immediately detect the presence or absence of the targets, rather than accurately detecting the distance or speed information of the target. In the proposed algorithm, in order to immediately detect the presence or absence of targets, 1D FFT is performed on the first and M-th bit signals among a total of M beat signals and then a phase change between two FFT outputs is observed. The range of target is estimated only when the phase change occurs. By doing so, the proposed algorithm achieves a significantly lower complexity compared to the conventional surveillance scheme using 2D FFT. In addition, show in order to verify the performance of the proposed algorithm, the simulation and the experiment results are performed using 24GHz FMCW radar module.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.2
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• pp.213-218
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• 2013

In this paper, a video based ship detection method is proposed to monitor port efficiently. Visual saliency map algorithm and mean shift algorithm is applied to detect moving ships don't include background information which is difficult to track moving ships. It is easy to detect ships at the port using saliency map algorithm, because it is very effective to extract saliency object from background. To remove background information in the saliency region, image segmentation and clustering using mean shift algorithm is used. As results of detecting simulation with images of a camera installed at the harbor, it is shown that the proposed method is effective to detect ships.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.5 no.1
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• pp.69-72
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• 2004

Compared to the barcode which is being widely employed to store information on products, the color code may find more various applications because of its favorable appearance and larger possible number of combinations. However, the color values read in practice may suffer from distortions from environments and devices. In this paper, we propose efficient ways to reduce the effect of such distortions and to detect color codes. for which we apply the Right Hand on Wall (RHOW) algorithm originated from the area of the maze search. The color codes used in this paper have high values of Hue and Saturation components and have a circular shape. We first preprocessed the images to detect candidate areas of color codes, and then applied the RHOW algorithm to determine optimal coordinates of rectangles enclosing the areas. As a result, we could obtain accurate coordinates of color codes by using the RHOW algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.12
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• pp.984-993
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• 2003

In Gravure printing process, there are a lot of printing errors caused by expansion and contraction of printing materials and difficulty of printing of small letters, accordingly we cannot detect those errors with eyes. In this paper, we describe the algorithm which can detect small errors automatically in Gravure printing process and a real-time detection system adopting the algorithm. We present the Perimetric Mask algorithm that can eliminate tiny errors occurring near the contour of printing objects to achieve accurate inspection, and also construct an algorithm utilizing symmetry transform which can emphasize tiny errors to make a robust inspection system. We have made a system running in real-time and verified the efficiency of the algorithm.