• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.3
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• pp.89-95
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• 2003

This research analyzes the cutting mechanism of A1100-H18 of commercially pure aluminum by image processing in SEM(Scanning Electron Microscope) for the measurement of strain rate distribution near a cutting edge in orthogonal micro-cutting. The distribution is measured using various methods in order. The methods are in-situ observations of cutting process in SEM, inputting image data, a computer image processing, calculating displacements by SSDA(Sequential Similarity Detection Algorithm) and calculating strain rates by FEM. The min results obtained are as follows: (1)It enables to measure a microscopic displacement near a cutting edge. (2) An application of this system to cutting process of various materials will help to make cutting mechanism clear.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.10a
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• pp.395-401
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• 1993

The purpose of this paper is to develop an automatic measuring system based on the digital image processing which can be applied to the in-process measurement of the characteristics of the thin thickness. The derivative operators is used for edge detection in gray level image. This concept can be easiliy illustrated with the aid of object shows an image of a simple light object on a dark background, the gray level profile along a horizontal scan line of the image, and the first and second derivatives of the profile. The first derivative of an edge modeled in this manner is () in all regions of constant gray level, and assumes a constant value during a gray level transition. The experimental results indicate that the developed qutomatic inspection system can be applied in real situation.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.304-309
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• 1999

In this paper, we presents a new disparity map refinement algorithm using statistical characteristics of disparity map and edge information. The proposed algorithm generate a refined disparity map using disparity maps which are obtained from area and feature-based Stereo Matching by selecting a disparity value of edge point based on the statistics of both disparity maps. Experimental results on aerial stereo image show the better results than conventional fusion algorithms in the disparity error. This algorithm can be applied to the reconstruction of building image from the high resolution remote sensing data.

• The Journal of Korea Robotics Society
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• v.9 no.3
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• pp.140-146
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• 2014

This paper introduces a dual-arm robot painter system which is capable of sketching a camera-captured image with short line segments. To express various curved edges in the image by combining line segments, we first apply edge detection algorithm to the entire image, split the edged image into small boxed pieces, and then apply Hough Transformation to each piece so that the edges inside the piece can be approximated with short line segments. To draw the picture within a reasonable time, we designed a simple dual-arm robot system and controlled both arms concurrently according to linear interpolation algorithm. From the experiments, we could verify that simple linear motions can describe various images effectively with a unique brush style.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.827-828
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• 2008

Blur identification is the first and the most important step of restoring images. Edge region of the image usually conveys important information of blur parameters. In this paper we propose a region-based edge extraction method for estimating point-spread-function (PSF). As a result, the proposed method can detect the starting and the ending points of a step response, and provides the PSF parameters to the restoration process.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.269-272
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• 1997

It is need to inspect a injected E.V.A midsole automatically in shoe manufacture. We applied image processing technology to inspect a injected E.V.A midsole. Captured image by CCD camera was processed with smoothing and edge detection. We compensated error of length from processed image of gauge block and error by bending strain with the measurement method of interval length for midsole image.

• Journal of Institute of Control, Robotics and Systems
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• v.1 no.2
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• pp.105-111
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• 1995

This paper proposes a segmentation algorithm using gray-level discontinuity and surface reflectance ratio of input images obtained under different illumination conditions. Each image is divided by a certain number of subregions based on the thresholds. The thresholds are determined using the histogram of fusion image which is obtained by ANDing the multiple input images. The subregions of images are projected on the eigenspace where their bases are the major eigenvectors of image matrix. Points in the eigenspace are classified into two clusters. Images associated with the bigger cluster are fused by revised ANDing to form a combined edge image. Missing edges are detected using surface reflectance ration and chain code. The proposed algorithm obtains more accurate edge information and allows to more efficiently recognize the environment under various illumination conditions.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.159-162
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• 2008

This paper presents a modified mean curvature diffusion filter to smooth speckle noise in images. Mean curvature diffusion filter has already shown good results in reducing noise in images while preserving fine details. In the mean curvature diffusion, the rate of smoothing is controlled by the local value of the diffusion coefficient chosen to be a function of the local image gradient magnitude. In this paper, the diffusion coefficient is modified to be controlled adaptively by local image surface slope and heterogeneity. The local surface slope contributes to preserving details (e.g.edges) in image and the local surface heterogeneity helps the smoothing filter consider the amount of noise in both edge and non-edge area. The proposed filter's performance is demonstrated by quantitative experiments using speckle noised aerial image and TerraSAR-X satellite image.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.29-31
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• 2007

In this paper we propose an directional analytic approach in image data space for X-ray image which is detected from the X-ray projection system. Such a radiographic nondestructive testing has long been used for steel-tube inspection and weld monitoring. The welded area and thickness of steel-tube are detected from gradient radiating mechanism based on the evaluation of biased X-ray source position. The welded area is an ellipse type on low contrast X-ray image including noise. Noise originates from most of elements of the system. such as shielding CCD camera, imaging screen, X-ray source, inspected object, electronic circuits and etc.. Projection incorrectness and noise influence on imaging quality is to be represented by vertical pixels' distribution. Space analysis due to vertical direction also shows the segmental possibility between regions by visual edge evaluation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1997.06a
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• pp.107-112
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• 1997

This paper proposes the regularized constrained iterative image restoration algorithms which apply new space-adaptive methods to degraded image signals, and analyzes the convergence condition of the proposed algorithm. First, we introduce space-adaptive regularization operators which change according to edge characteristics of local images in order to effectively prevent the restored edges and boundaries from reblurring. And, pseudo projection operator is used to reduce the ringing artifact which results from extensive amplification of noise components in the restoration process. The analysed algorithm is stable convergent to the fixed point. According to the experimental results for various signal-to-noise ratios(SNR) and blur models, the proposed algorithms other methods and is robust to noise effects and edge reblurring by regularization especially.