• Journal of Institute of Control, Robotics and Systems
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• v.4 no.6
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• pp.759-764
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• 1998

We propose a novel algorithm capable of recognizing the road lane by image processing. Considering the fact that the direction and location of road lane are maintained similarly in successive images we formulate a function to represent the property. However, as noises play the role of making a lot of similar patterns appear and disappear in the road image, keeping of robustness in the lane detection has been known a difficult work. To overcome this problem, we introduce the following three ideas: 1) design of a function based on an edge direction and magnitude, 2) construction of a recursive filter to estimate the function recursively for successive images, 3) principal axis-based line fitting. These concepts enhance the adaptability to cope with the random environment of traffic scene and eventually lead to the reliable detection of a road lane.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.9
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• pp.2209-2215
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• 2014

This paper presents, a deinterlacing method by improving the Direction-Oriented Interpolation (DOI) technique. The technique is considered to be a very strong tool for intrafield-based deinterlacing. However, DOI has some problems such as long processing time, wrong edge detection in periodic pattern. To remedy this problem, we replace the full search in DOI by a two-step search to reduce processing time and introduces two additional processes to improve image quality. In the proposed method, the spatial direction vectors (SDVs) misread data are reconsidered to prevent them utilizing in the next interpolation step, resulting in an accurate deinterlacing method. We conduct experiments with ISO experimental images to compare the proposed method with the existing methods including line evarage (LA), edge-based line averaging (ELA), DOI, selective deinterlacing algorithm (SDA). Experimental results show the proposed method gives better performance in objective and subjective quality than existing deinterlacing methods.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.8 no.2
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• pp.3-9
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• 2009

When washing machine is rotated in the laundry, it tends to lean toward one side. This tendency causes a serious vibration. The balance of washing machine plays an important role in order to reduce the vibration by injecting the sand or the salt water into the balance of washing machine. The hot plate welder is used to prevent from outflow of contents. The hot plate welder brings about many problems which is concerned with accidents. The direction recognition and location information of the balance are required in this system. In this paper, the recognition direction of balance in washing machine using machine vision system is studied. The template matching algorithm compares sub-image with original image acquired in real-time to obtain a center point of balance image. The mid points and the edges of balance are estimated by the edge detection and gauging algorithms. The data acquired by these results is used for recognition direction of balance. The automation software for image processing is developed by using LabVIEW.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.13 no.1
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• pp.74-84
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• 1988

This paper presents feature extraction technique for linear image using edge detection algorithms. The process of edge finding consists of determining edge magnitud and direction by convolution of an image with a number of edge masks, of thinning and ghresholding these edge magnitudes, of linking the edge elemtnts based on proximity ans orientation, and finally, of approximating the linked elements by piede-wise linear segmentss. These techniques are intened to be general and opplications to terminal detection and road recognition tasks are described. The presentation will be helpful to other researchers attempting to implement similar algorithms.

• Proceeding of EDISON Challenge
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• 2016.11a
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• pp.19-22
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• 2016

Leading edge thrust is generally caused by passing air flow from lower to upper surface and it is required to have sufficient angle of attack for notable leading edge thrust. To produce leading edge thrust at low angle of attack, utilizing expansion wave accompanying low pressure is able to be a solution. Fore structure changes the direction of flow, and this flow passes the projected edge. As a result, from a perspective of the edge, it is able to have high angle of attack, and artificial expansion wave is generated. This concept shows 9.48% increase of L/D in inviscid flow, at Mach number 1.3 and angle of attack $1^{\circ}$ in maximum, and this model shows the 3.98% of increasement at angle of attack $2^{\circ}$. Although advantage of the artificial expansion wave decreased as angle of attack increase, it shows the possibility of aerodynamical improvement with artificial expansion wave.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.1
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• pp.53-61
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• 1996

A clear understanding of the surface formation mechanism due to cutting is very important to help produce a good quality surface. Much of the roughness along the length of a bar being cut in a lathe can be explained in terms of macroscopic tool shape and feed rate. However, the roughness along the direction of cutting requires a different explanation. The formation of surface roughness is a problem in flow and fracture of materials in the vicinity of the tool edge. On a microscopic scale the cutting edge is rounded because it is impossible to grind a perfectly sharp cutting edge. Even if a perfectly sharp cutting edge were obtained it would soon become dull as a result of rapid breakdown and wear of the cutting edge. A research project is proposed in which in the main object is to model the surface formation mechanism due to cutting. The tool was assumed to be dull, that is, its edge has a finite radius. In order to study the effect of the radius of cutting edge on the surface formation, tools having different cutting edges were used. For orthogonal cutting experiment, cast iron and glass were chosen as brittle materials. Plowing forces acting in the cutting edge were estimated and its effect on the surface roughness was studied by observing the machined surface using optical microscope.

• Journal of the Korean Society of Combustion
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• v.5 no.2
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• pp.19-27
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• 2000

A turbulent combustion model, based on edge flame dynamics, is discussed in order to predict global extinction of turbulent flames. The model is applicable to the broken flamelet regime of turbulent combustion, in which global extinction of turbulent flame is achieved by gradual expansion of flame holes. The edge flame dynamics is the key mechanism to describe the flame hole expansion or contraction. For flames with Lewis numbers near unity, there is a $Damk{\ddot{o}}hler$ number, namely the crossover $Damk{\ddot{o}}hler$ number, at which edge flame changes its direction of propagation. The parametric region between the quasi-steady extinction condition and the edge-flame crossover condition is a metastable region, in that flames without edge can stay in their burning states while flames with edge have to retract to expand quenching holes. Using the above properties of edge flame, Hartley and Dold proposed a Lagrangian hole dynamics, which allows us to simulate transient variation of quenching holes. In their model, each stoichiometric surface is subjected to a random sequence of scalar dissipation rate compatible to the equilibrium turbulence. Then, each stoichiometric surface will evolve, according to the combustion map, dependent on the scalar dissipation rate and existence of flame edge, If all the burning surfaces are annihilated, the event can be declared as a global extinction. The consequence obtained from the above model also can be used as a subgrid model to determine local extinction occurring in a calculation grid.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.328-330
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• 2015

Edge is a characteristic information that can easily obtain the size, direction and location of objects included in the image, and the edge detection is utilized as a preprocess processing in various image processing application sectors such as object detection and object recognition, etc. For the conventional edge detection methods, there are Sobel, Prewitt and Roberts. These existing edge detection methods are easy to implement but the edge detection characteristics are somewhat insufficient as fixed weighted mask is applied. Therefore, in order to compensate the problems of existing edge detection methods, in this paper, an edge detection algorithm was proposed after applying the weighted value according to the standard deviation and means within the local mask.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.11
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• pp.146-154
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• 2014

The local binary pattern (LBP) scheme that is one of the texture classification methods normally uses the distribution of flat, edge and corner patterns. However, it cannot examine the edge direction and the pixel difference because it is a sort of binary pattern caused by thresholding. Furthermore, since it cannot consider the pixel distribution, it shows lower performance as the image size becomes larger. In order to solve this problem, we propose a sub-classification method using the edge direction distribution and eigen-matrix. The proposed sub-classification is applied to the particular texture patches which cannot be classified by LBP. First, we quantize the edge direction and compute its distribution. Second, we calculate the distribution of the largest value among eigenvalues derived from structure matrix. Simulation results show that the proposed method provides a higher classification performance of about 8 % than the existing method.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.9
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• pp.901-908
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• 2016

Edge is the basic characteristic of image, edge detection is very important in image processing applications and computer vision area. Many studies are being performed to detect these edges by domestic and foreign researchers. The conventional edge detection methods such as Roberts, Sobel, Prewitt, and Laplacian etc, which are using a fixed value of mask are widely used and morphological gradient which uses dilation and erosion among morphology process techniques is also widely used. But these methods does not detect edges well in the diagonal direction or gradually changing image parts. Accordingly, in this paper, the modified top-hat and bottom-hat transform algorithms which are detecting edges well in the parts of diagonal direction or gradually changing image are proposed. The proposed algorithms present the detected edge images compared with the conventional methods and are evaluated performance by using cosine similarity.