• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.5
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• pp.698-704
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• 2010

The machine vision system has been widely applied at automatic inspection field of the industries. Especially, the machine vision system shows good performance at difficult inspection field by contact method. In this paper, the automatic system of a slant method to inspect screw/bolt shape using machine vision is developed. The inspection system uses pattern matching method that search similar degree of the lucidity, the average lucidity, length and angle of inspection set up area using a circular scan and a line scan method. Also the feeding method for inspection product is the slant method, and feed rate is controlled by the ramp angle adjustment. This inspection system is composed of a feeding device, a transfer device, vision systems, a lighting device and computer, and is composed the sorting discharge system of the inferior product. The performance test carried out the feeding speed, the shape correct degree and the sorting discharge speed according to the type of screw/bolt. This sorting inspection system showed a satisfied test results in whole inspection items. Presently, this sorting inspection system is being used in the manufacturing process of screw/bolt usefully.

• Proceedings of KOSOMES biannual meeting
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• 2005.11a
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• pp.203-208
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• 2005

The CGO (Chip on Glass) to be measured a few micro unit is captured by line scan camera for the accuracy of chip inspection. But it is very sensitive to scan speed and lighting conditions. In this paper, we propose the methods to increase the accuracy of faulty detection by image subtraction. Image subtraction is detected faultiness by subtracting the image of a ' perfect ' COG from trot of the sample under tests. For image subtraction to be successful, the two images must be pre챠sely registered The two images is registered by the area segmentation pattern matching, and the result image get by operating the gradient mask image and the image to practice subtraction. A series of experimentation showed that the proposed algorithm shows substantial improvement over the other image subtraction methods.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1959-1960
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• 2008

The Logic Built In Self Test (LBIST) technique is substantially applied in chip design in most many semiconductor company in despite of unavoidable overhead like an increase in dimension and time delay occurred as it used. Currently common LBIST software uses the MISR (Multiple Input Shift Register) However, it has many considerations like defining the X-value (Unknown Value), length and number of Scan Chain, Scan Chain and so on for analysis of result occurred in the process. So, to solve these problems, common LBIST software provides the solution method automated. Nevertheless, these problems haven't been solved automatically by Tri-state Bus in logic circuit yet. This paper studies the algorithm that it also suggest algorithm that reduce additional circuits and time delay as matching of pattern about 2-type circuits which are CUT(circuit Under Test) and additional circuits so that the designer can detect the wrong location in CUT: Circuit Under Test.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.5C
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• pp.539-547
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• 2003

According to the PDE scheme, it is desirable to make the value of SAD to be rapidly increased in motion estimation. In this paper, we propose a new block matching algorithm based on the combination of a new scan and search order. In the proposed scan order, a current block is divided by the frequency that is estimated by summing the difference between the mean and the values of the pixels. And then the calculation of SAD is performed from the highest frequency area. In the proposed search order based on DC difference between the current and the candidate block, candidate blocks with low DC are early checked in motion estimation. Simulation results show that the proposed method achieves about 6% computational gain compared with the conventional methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.9-18
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• 2004

This paper proposes a new and simple stereo matching algorithm using the disparity space image (DSI) technique. First of all, we detect some salient feature points on each scan-line of the image pair and set the matching area using those points and define a simple cost matrix. And we take advantage of matching by pixel-by-pixel instead of using the matching window. While the pixel-by-pixel method boost up the speed of matching, because of no using neighbor information, the correctness of the matching may not be better. To cover this point, we expand the matching path using character of disparity-space-image for using neighbor information. In addition, we devise the compensated matching module using the volume of the disparity space image in order to improve the accuracy of the match. Consequently, we can reduce mismatches at the disparity discontinuities and can obtain the more detailed and correct disparity map.

• The Journal of the Korea Contents Association
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• v.15 no.9
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• pp.411-417
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• 2015

To distinguish between HCC and HH is one of the important test methods in determining the treatment method by determining the treatment method by distinguishing malignant growth and benign tumors in liver CT scan. Currently, the specialist is reading CT images by their subjective judgment. So, the purpose of this study is to treat reading the CT images even more objective way. The test times after injection contrast medium in this study are the before injection phase(Pre.), artery phase(35sec), portal phase(70sec) and delay phase(180sec). The general pattern change of HCC in change of contrast enhancement pattern shows 26.6% matching. And the case of HH shows 16.6% matching. In order to observe the change of HU value between HCC and HH, each average values and standard deviation was confirm and as a result, it shows the lagre difference between artery and portal phase in lesion.(HCC$19.76{\pm}23.52$, HH$60.23{\pm}29.43$). And it shows the 76.6% matching in HCC and 80.0% matching in HH. Thorough this study, to suggest a HU value as objective analysis method and if the anlaysis method was used in clinical will assist in the diagnosis.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.11
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• pp.1153-1163
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• 2014

An efficient 3D SLAM (Simultaneous Localization and Map Building) method is developed for urban building environments using a tilted 2D LRF (Laser Range Finder), in which a 3D map is composed of perpendicular/horizontal planar polygons. While the mobile robot is moving, from the LRF scan distance data in each scan period, line segments on the scan plane are successively extracted. We propose an "expected line segment" concept for matching: to add each of these scan line segments to the most suitable line segment group for each perpendicular/horizontal planar polygon in the 3D map. After performing 2D localization to determine the pose of the mobile robot, we construct updated perpendicular/horizontal infinite planes and then determine their boundaries to obtain the perpendicular/horizontal planar polygons which constitute our 3D map. Finally, the proposed SLAM algorithm is validated via extensive simulations and experiments.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.2
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• pp.177-180
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• 2019

To improve the accuracy rate of guided weapons, many studies have been conducted on the accurate detection and identification of targets from sea clutter. Because of the variety and complicated characteristics of both sea-clutter and target signals, an active target recognition technique is required. In this study, we propose an algorithm to distinguish clutter and recognize targets by applying a fractal signature(FS) classifier, which is a fractal dimension, and a high-resolution target image(HRTI) classifier, which applies scene matching to an image formed from a scanned image. Simulation results using the algorithm revealed that the HRTI classifier recognized targets 1 and 2 at a 100 % rate, whereas the FS classifier recognized targets 1 and 2 at rates of 90 % and 93 %, respectively.

• Journal of Biomedical Engineering Research
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• v.29 no.6
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• pp.431-435
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• 2008

Quantitative information of a three dimensional(3D) kinematics of joint is very useful in knee joint surgery, understanding how knee kinematics related to joint injury, impairment, surgical treatment, and rehabilitation. In this paper, an automated 2D/3D image matching technique was developed to estimate the 3D in vivo knee kinematics using dual X-ray images. First, a 3D geometric model of the knee was reconstructed from CT scan data. The 3D in vivo position and orientation of femoral and tibial components of the knee joint could be estimated by minimizing the pixel by pixel difference between the projection images from the developed 3D model and the given X-ray images. The accuracy of the developed technique was validated by an experiment with a cubic phantom. The present 2D/3D image matching technique for the estimation of in vivo joint kinematics could be useful for pre-operative planning as well as post-operative evaluation of knee surgery.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.6
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• pp.559-566
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• 2008

In this paper, we propose a range subsequence matching under dynamic time warping (DTW) distance. We exploit Dual Match, which divides data sequences into disjoint windows and the query sequence into sliding windows. However, Dual Match is known to work under Euclidean distance. We argue that Euclidean distance is a fragile distance, and thus, DTW should be supported by Dual Match. For this purpose, we derive a new important theorem showing the correctness of our approach and provide a detailed algorithm using the theorem. Extensive experimental results show that our range subsequence matching performs much better than the sequential scan algorithm.