• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.414-417
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• 1993

The methods for stereo matching are divided into two techniques: area-based matching and feature-based matching. To find corresponding points by area-based method, it takes a lot of time because there are many points to be matched. Feature-based matching algorithm is often used because with this method it matches only some feature points so that the processing time is fast even though it requires interpolation after matching. In this paper, we propose the smart technique by which we makes features simpler than conventional methods to match an image pair by feature-based matching algorithm.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.9
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• pp.1420-1427
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• 1989

A new block matching algorithm that improved the existing block matching algorithm in terms of image quality is proposed in this paper. The subblock of image including the vertical edge of object is subdivided into new two subblocks, and the moving vector found. The result of computer simulation shows on real image that the image quality by the algorithm becomes higher than that of the three step search algorithm by 1.1dB.

• Journal of the Korean Statistical Society
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• v.36 no.1
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• pp.77-91
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• 2007

This paper considers development of noninformative priors for the familial data when the families have equal number of offspring. Several noninformative priors including the widely used Jeffreys' prior as well as the different reference priors are derived. Also, a simultaneously-marginally-probability-matching prior is considered and probability matching priors are derived when the parameter of interest is inter- or intra-class correlation coefficient. The simulation study implemented by Gibbs sampler shows that two-group reference prior is slightly edge over the others in terms of coverage probability.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.6
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• pp.128-135
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• 2002

Burr is a projected part of finished workpiece. It is unavoidable and undesirable by-product of most metal cutting or shearing process. Also, it must be removed to improve the fit of machined parts, safety of workers, and the effectiveness of finishing operation. But deburring process Is one of manufacturing processes that have not been successfully automated, so deburring automation is strongly needed. This paper focused on developing a basic algorithm to find edge of workpiece and match two different image data for deburring automation which includes automatic recognition of parts, generation of deburring tool paths and edge/comer finding ability by analyzing the DXF drawing file which contains information of part geometry. As an algorithm fur corner finding, SUSAN method was chosen. It makes good performance in finding edge and corner in suitable time. And this paper suggested a simple algorithm to find matching point between CCD image and drawing file.

• Journal of Broadcast Engineering
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• v.18 no.3
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• pp.342-348
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• 2013

In this paper, a novel frame rate up conversion (FRUC) algorithm using adaptive extended bilateral motion estimation (AEBME) is proposed. Conventionally, extended bilateral motion estimation (EBME) conducts dual motion estimation (ME) processes on the same region, therefore involves high complexity. However, in this proposed scheme, a novel block type matching procedure is suggested to accelerate the ME procedure. We calculate the edge information using sobel mask, and the calculated edge information is used in block type matching procedure. Based on the block type matching, decision will be made whether to use EBME. Motion vector smoothing (MVS) is adopted to detect outliers and correct outliers in the motion vector field. Finally, overlapped block motion compensation (OBMC) and motion compensated frame interpolation (MCFI) are adopted to interpolate the intermediate frame in which OBMC is employed adaptively based on frame motion activity. Experimental results show that this proposed algorithm has outstanding performance and fast computation comparing with EBME.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.135-139
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• 1996

In this a paper, a new method to measure the wear of the single crystal diamond(SCD) tool using image processing is presented. To increase resoultion, high magnifying lens is used and to enlarge the measurement field of view, a image region matching method is applied. The shape of SCD tool is modeled by mathematical analysis. Cutting edge chipping and wear are calculated by the model. This method is proved to be efficient in detecting a few micron of wear and cutting edge loss by chipping along the whole cutting edge.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.347-350
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• 2002

This paper describes eye detection algorithm using edge information and Support Vector Machine (SVM). We adopt an edge detection and labelling algorithm to detect isolated components. Detected candidate eye pairs finally verified by SVM using Radial Basis Function (RBF) kernel. A detection rate over the test set has been achieved more than 90%, and compared with template matching method. this proposed method significantly reduced FAR.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.4
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• pp.48-57
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• 1992

This paper addresses the estimation of the shift vector from aerial image sequences. The conventional feature-based and area-based matching methods are simulated for determining the suitable image registration scheme. Computer simulations show that the feature-based matching schemes based on the co-occurrence matrix, autoregressive model, and edge information do not give a reliable matching for aerial image sequences which do not have a suitable statistical model or significant features. In area-based matching methods we try various similarity functions for a matching measure and discuss the factors determining the matching accuracy. To reduce the estimation error of the shift vector we propose the reference window selection scheme. We also discuss the performance of the proposed algorithm based on the simulation results.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.1
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• pp.201-210
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• 2003

In this paper, we propose a new binocular stereo correspondence method by maximizing a fitness formulated by integrating two constraints of edge similarity and disparity smoothness simultaneously. The proposed stereopsis focusing to measure distances to leading vehicles on roads uses intensity gradients as matching attribute. In contrast to the previous work of area-based stereo matching, in which matching unit is a pixel, the matching unit of the proposed method becomes an area itself which is obtained by selecting a series of pixels enclosed by two pixels on the left and right boundaries of an object. This approach allows us to cope with real-time processing and to avoid window size selection problems arising from conventional area-based stereo.

• Journal of the Korea Society of Computer and Information
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• v.14 no.12
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• pp.63-73
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• 2009

This paper presents a vehicle detection method that uses convolution matching method based on a simple color information. An input image is expressed as 8 oriented color expression(Red, Green, Blue, White, Black, Cyan, Yellow, Magenta) considering an orientation of a pixel color vector. It makes the image very reliable and strong against changes of illumination condition or environment. This paper divides the vehicle detection into a hypothesis generation step and a hypothesis verification step. In the hypothesis generation step, the vehicle candidate region is found by vertical edge and shadow. In the hypothesis verification step, the convolution matching and the complexity of image edge are used to detect real vehicles. It is proved that the proposed method has the fast and high detection rate on various experiments where the illumination source and environment are changed.