• Journal of Biomedical Engineering Research
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• 제23권2호
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• pp.101-107
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• 2002

This paper presents a segmentation algorithm to extract endocardial contour and epicardial contour of left ventricle in MR Cardiac images. The algorithm is based on a generalized gradient vector flow(GGVF) snake and a prediction of initial contour(PIC). Especially. the proposed algorithm uses physical characteristics of endocardial and epicardial contours, cross profile correlation matching(CPCM), and a mixed interpolation model. In the experiment, the proposed method is applied to short axis MR cardiac image set, which are obtained by Siemens, Medinus, and GE MRI Systems. The experimental results show that the proposed algorithm can extract acceptable epicardial and endocardial walls. We calculate quantitative parameters from the segmented results, which are displayed graphically. The segmented left vents role is visualized volumetrically by surface rendering. The proposed algorithm is implemented on Windows environment using Visual C ++.

• The Magazine of the IEIE
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• 제23권12호
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• pp.115-125
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• 1996

This paper presents a new algorithm for the self-localization of a mobile robot using one degree perspective Invariant(Cross Ratio). Most of conventional model-based self-localization methods have some problems that data structure building, map updating and matching processes are very complex. Use of a simple cross ratio can be effective to the above problems. The algorithm is based on two basic assumptions that the ground plane is flat and two locally parallel sloe-lines are available. Also it is assumed that an environmental map is available for matching between the scene and the model. To extract an accurate steering angle for a mobile robot, we take advantage of geometric features such as vanishing points. Feature points for cross ratio are extracted robustly using a vanishing point and intersection points between two locally parallel side-lines and vertical lines. Also the local position estimation problem has been treated when feature points exist less than 4points in the viewed scene. The robustness and feasibility of our algorithms have been demonstrated through real world experiments In Indoor environments using an indoor mobile robot, KASIRI-II(KAist Simple Roving Intelligence).

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.920-923
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• 1996

This paper presents a new algorithm for the self-localization of a mobile robot using perspective invariant(Cross Ratio). Most of conventional model-based self-localization methods have some problems that data structure building, map updating and matching processes are very complex. Use of the simple cross ratio can be effective to the above problems. The algorithm is based on two basic assumptions that the ground plane is flat and two parallel walls are available. Also it is assumed that an environmental map is available for matching between the scene and the model. To extract an accurate steering angle for a mobile robot, we take advantage of geometric features such as vanishing points(V.P). Point features for computing cross ratios are extracted robustly using a vanishing point and the intersection points between floor and the vertical lines of door frames. The robustness and feasibility of our algorithms have been demonstrated through experiments in indoor environments using an indoor mobile robot, KASIRI-II(KAist SImple Roving Intelligence).

• Proceedings of the KSME Conference
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• 대한기계학회 2001년도 추계학술대회논문집B
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• pp.410-416
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• 2001

An algorithm of 3-D particle image velocimetry(3D-PIV) was developed for the measurement of 3-D velocity field of complex flows. The measurement system consists of two or three CCD camera and one RGB image grabber. In this study, stereo photogrammetty was applied for the 3-D matching of tracer particles. Epipolar line was used to decect the stereo pair. 3-D CFD data was used to estimate algorithm. 3-D position data of the first frame and the second frame was used to find velocity vector. Continuity equation was applied to extract error vector. The algorithm result involved error vecotor of about 0.13 %. In Pentium III 450MHz processor, the calculation time of cross-correlation for 1500 particles needed about 1 minute.

• Journal of Information Processing Systems
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• 제12권4호
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• pp.661-680
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• 2016

The vehicle license plate recognition (VLPR) system analyzes and monitors the speed of vehicles, theft of vehicles, the violation of traffic rules, illegal parking, etc., on the motorway. The VLPR consists of three major parts: license plate detection (LPD), license plate character segmentation (LPCS), and license plate character recognition (LPCR). This paper presents an efficient method for the LPCS and LPCR of Korean vehicle license plates (LPs). LP tilt adjustment is a very important process in LPCS. Radon transformation is used to correct the tilt adjustment of LP. The global threshold segmentation method is used for segmented LP characters from two different types of Korean LPs, which are a single row LP (SRLP) and double row LP (DRLP). The cross-correlation matching method is used for LPCR. Our experimental results show that the proposed methods for LPCS and LPCR can be easily implemented, and they achieved 99.35% and 99.85% segmentation and recognition accuracy rates, respectively for Korean LPs.

• Proceedings of the KIEE Conference
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.3044-3046
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• 2000

A Stereo matching has been an important tool for reconstructing three dimensional terrain. In this stereo matching process, DEM(Digitai Elevation Map) can be generated by the disparity from reference image to target image. Generally disparity map in matching process can be implemented by wraping from reference image to target image and if the role of reference and target is interchanged, the different DEM can be obtained. To evaluate the generated DEM from matching process, We adapted the Photorealistic synthetic image generator using ray tracing technique. The generator produce two simulated image from previous DEM and Ortho-image which is regard as Ground-truth. In this paper, we are concern about estimating more accurate DEM from these two DEMs. The several fusion methods of two DEMs are proposed to generate accurate DEM and compared with previous method. one of fusion methods is by using Cross-Correlation match score and the true DEM should have a high matching score.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• 제22권1호
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• pp.150-155
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• 2013

This work present a new method of sealing inspection system for vehicle in which foam rubber materials are used for sealing the vehicle parts. This system is composed from a devices comprising non-contact and real-time scanning on visual inspection in machine parts. We have been investigated qualitative factors that influenced on sealing system of vehicle structure which flexibly attenuated vibration and plenty of foam rubber materials having elastic property. However, there are different factors which still depended on outdated technique (personnel subjective judgment) in the performance inspection of rubber parts, specially for cross section inspection. Through a newly developed inspection system which recently applied for the production line, we successfully achieved more effective results of matching rate by about 80 % in the sealing performance inspection with 0.7% to 1.4% in the repeated errors. These are resulted from non-contacted response by CCD camera and vision program using geometry matching method. We expect that this system may be widely applied in the strict inspection parts of more diverse cross-section in future.

• ETRI Journal
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• 제33권4호
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• pp.537-546
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• 2011

This paper introduces an automated method for building height recovery through the integration of high-resolution satellite images and digital vector maps. A cross-correlation matching method along the vertical line locus on the Ikonos images was deployed to recover building heights. The rational function models composed of rational polynomial coefficients were utilized to create a stereopair of the epipolar resampled Ikonos images. Building footprints from the digital maps were used for locating the vertical guideline along the building edges. The digital terrain model (DTM) was generated from the contour layer in the digital maps. The terrain height derived from the DTM at each foot of the buildings was used as the starting location for image matching. At a preset incremental value of height along the vertical guidelines derived from vertical line loci, an evaluation process that is based on the cross-correlation matching of the images was carried out to test if the top of the building has reached where maximum correlation occurs. The accuracy of the reconstructed buildings was evaluated by the comparison with manually digitized 3D building data derived from aerial photographs.

• The Journal of the Acoustical Society of Korea
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• 제19권1호
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• pp.54-60
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• 2000

There are many works to analyze a simple expansion chamber involving higher order modes. These works are classified to mode matching method, velocity potential method and finite element method. Among these methods, mode matching method has good performance at analyzing a concentric expansion chamber. Generally inlet/outlet pipe cross section area is smaller than middle chamber cross section area. So the number of higher order modes of inlet/outlet pipe can be fewer than that of middle chamber. But mode matching method must use the same number of higher order modes at inlet pipe, middle chamber and outlet pipe. Therefore the redundant modes of inlet/outlet pipe makes the computation time of mode matching method longer. In this paper, the new method, which can select number of each higher order modes of inlet pipe, middle chamber and outlet pipe, was suggested. And this method was compared to conventional mode matching method and finite element method in order to demonstrate the accuracy of the new method and to show that the new method can reduce a calculating time.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• 제37권6호
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• pp.473-479
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• 2019

This study applied SGM (Semi Global Matching) to generate DSM (Digital Surface Model) using WorldView-1 high-resolution satellite stereo pair in Terrassa, Spain provided by ISPRS (International Society for Photogrammetry and Remote Sensing). The SGM is an image matching algorithm that performs the computation of the matching cost for the stereo pair in multi-paths and aggregates the computed costs sequentially. This method finally calculates the disparity corresponding to the minimum (or maximum) value of the aggregation cost. The cost was applied to MI (Mutual Information), NCC (Normalized Cross-Correlation), and CT (Census Transform) in order to the SGM. The accuracy and performance of the outline representation result in DSM by each cost are presented. Based on the images used and the subject area, the accuracy of the CT cost results was the highest, and the outline representation was also most clearly depicted. In addition, while the SGM method represented more detailed outlines than the existing software, many errors occurred in the water area.