• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.136-138
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• 2022

Edge detection includes information such as the shape, position, size, and material of an object with respect to an image, and is a very important factor in analyzing the characteristics of the image. Existing edge detection methods include Sobel edge detection filter, Roberts edge detection filter, Prewitt edge detection filter, and LoG (Lapacian of Gaussian) using secondary differentials. However, these methods have a disadvantage in that the edge detection results are somewhat insufficient because a fixed weight mask is applied to the entire image area. Therefore, in this paper, we propose an edge detection algorithm that increases edge detection characteristics by considering the center pixel in the mask. In addition, in order to confirm the proposed edge detection performance, it was compared through simulation result images.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.8
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• pp.1129-1135
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• 2013

A new vehicle detection algorithm based on the multiple optimal Adaboost classifiers with optimal feature selection is proposed. It consists of two major modules: 1) Theoretical DDISF(Distance Dependent Image Scaling Factor) based image scaling by site modeling of the installed cameras. and 2) optimal features selection by Haar-like feature analysis depending on the distance of the vehicles. The experimental results of the proposed algorithm shows improved recognition rate compare to the previous methods for vehicles and non-vehicles. The proposed algorithm shows about 96.43% detection rate and about 3.77% false alarm rate. These are 3.69% and 1.28% improvement compared to the standard Adaboost algorithmt.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.113.2-113
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• 2001

In this paper, we present a robot off-Line programming system with collision detection. The collision detection is a very important factor of robot oft-line programming system for collision avoidance, path planning, and so on. The System developed in this paper, basically using an algorithm for the minimum distance calculation between general polyhedra. The proposed system shows an exact and interactive result in static and dynamic environments.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.147-150
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• 1996

A homing torpedo's performance can be expressed a function of many variables, i.e. technical and tactical variables. When designing a homing torpedo, these variables have to be decided upon. The system effectiveness of a homing torpedo can be determined by analyzing of these variables. This paper describes a procedure of simulation metamodelling using a Factor Analysis methodology. A simulation model was used in order to obtain the data base for analyzing detection probability of torpedo. By analyzing the main and interaction effects these variables on the analysis of detection probability, we will show the importance of certain variables, of a homing torpedo.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1155-1158
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• 1999

In this paper, we consider the optimal control of detection threshold to minimize the conditional mean-square state estimation error for the probabilistic data association (PDA) filter. Earlier works on this problem involved the cumbersome graphical optimization algorithm or time-consuming numerical optimization algorithm. Using the numerical approximation of information reduction factor, we obtained the closed-form optimal detection threshold. This results are very useful for real-time implemenation.

• Journal of the Korean Statistical Society
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• v.12 no.2
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• pp.61-68
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• 1983

A parallel flats fraction for the $3^n$ factorial experiment is defined as the union of flats, ${t$\mid$At=C_i(mod 3)}, i=1,2,\cdot,f$, in EG(n,3) and is symbolically written as At=C where A is of rank r. The A matrix partitions the effects into u+1 alias sets where $u=(3^{n-r}-1)/2$. For each alias set the f flats produce an alias component permutation matrix (ACPM) with elements from $S_3$. In this paper, a detection vector of the ACPM was constructed for each combination of k or fewer two-factor interactions. Also the relationship between the detection vectors has been shown.

• Communications for Statistical Applications and Methods
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• v.7 no.1
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• pp.141-150
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• 2000

In this paper we propose a method of computing Bayes factor to detect an outlier in a random effects model. When no information is available and hence improper noninformative priors should be used Bayes factor includes the unspecified constants and has complicated computational burden. To solve this problem we use the fractional Bayes factor (FBF) of O-Hagan(1995) and the generalized Savage0-Dickey density ratio of Verdinelli and Wasserman (1995) The proposed method is applied to outlier deterction problem We perform a simulation of the proposed approach with a simulated data set including an outlier and also analyze a real data set.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.2 no.4
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• pp.553-558
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• 1998

We present in this paper the ture union bound of the performance of chip level detection for coded DS/CDMA system operating in Rician fading channels such as LEO satellite mobile radio where the maximum doppler frequency is very high. The main objective of this paper is to calculate the exact doe union bound of BER performance of different performance of different quadrature detectors and to find a optimum spreading factor as a function of fade rate. The rationale of using multiple chip detection is to reduce the effective fade rate or variation. We considered chip level differential detection, chip level maximum likelihood sequence estimation, noncoherent detection and coherent detection with perfect channel state information as a reference.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.549-551
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• 1999

Recently, Several type of motors are used more widely in Fan system because of their low cost and high reliability. Therefore, the importance of fault detection and isolation of fan system significantly increases. The motor is a important factor bring out the fan system fault. So the problem of a fault detection for motor based on a parameter identification will be considered in this paper. After an introduction into fault detection with parameter estimation, a mathematical model for motor with special emphasis on motor itself. In the fault detection system, current and motor speed are used as parameter. Finally, simulation results are used to demonstrate the efficiency of the fault detection system.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.136-146
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• 2022

Some surface defects make the weak quality of steel materials. To limit these defects, we advocate a one-stage detector model RetinaNet among diverse detection algorithms in deep learning. There are several backbones in the RetinaNet model. We acknowledged two backbones, which are ResNet50 and VGG19. To validate our model, we compared and analyzed several traditional models, one-stage models like YOLO and SSD models and two-stage models like Faster-RCNN, EDDN, and Xception models, with simulations based on steel individual classes. We also performed the correlation of the time factor between one-stage and two-stage models. Comparative analysis shows that the proposed model achieves excellent results on the dataset of the Northeastern University surface defect detection dataset. We would like to work on different backbones to check the efficiency of the model for real world, increasing the datasets through augmentation and focus on improving our limitation.