• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.82-90
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• 2010

In this paper, A new stereo matching method based on reliability space is proposed to acquire 3D information from 2D image. In conventional stereo matching methods, speed is sacrificed to achieve high accuracy. To increase the matching speed while maintaining a high accuracy, this paper proposes this stereo matching method. It first makes the disparity space image for comparing all of the pixels on the stereo images. Then it produce reliability space through analyzing this value. and, By comparing the reliability space according to disparity, it makes disparity map. Moreover, the parts that make regional boundary errors are corrected by classifying the boundary of each region with the reference to color edge. The performance of the proposed stereo matching method is verified by various experiments. As a result, calculation cost is reduced by 30.6%, while the image quality of proposed method has similar performance with the existing method.

• Journal of Korea Multimedia Society
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• v.11 no.2
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• pp.153-162
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• 2008

We propose a novel image inpainting method composed of two parts: band matching and seamless cloning. In band matching, a band enclosing the boundary of a missing region is compared to those from the other parts of the image. The inner area of the minimum difference band is then copied to the missing region. Even though this band matching results in successful inpainting in many practical applications, brightness discontinuity (a seam) may appear between the filled missing region and its neighborhood. We apply seamless cloning to remove such discontinuity between the two regions. However, since this basic method using one patch may not deal with cases where there are abrupt changes of color or brightness along the boundary, we furthermore devise one more step: target sub-division. The target area is subdivided into small sub-areas, and the band matching and seamless cloning are applied to each of them. The multiple results from the sub-division are then ordered according to inpainting quality, which is measured based on the edge map or discontinuity map along the boundary band.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.11
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• pp.2711-2722
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• 1993

Most of the current 2-D object recognition systems are model-based. In such systems, the representation of each of a known set of objects are precompiled and stored in a database of models. Later, they are used to recognize the image of an object in each instance. In this thesis, the approach method for the 2-D object recognition is treating an object boundary as a string of structral units and utilizing string matching to analyze the scenes. To reduce string matching time, models are rebuilt by means of fuzzy c-means clustering algorithm. In this experiments, the image of objects were taken at initial position of a robot from the CCD camera, and the models are consturcted by the proposed algorithm. After that the image of an unknown object is taken by the camera at a random position, and then the unknown object is identified by a comparison between the unknown object and models. Finally, the amount of translation and rotation of object from the initial position is computed.

• Fire Science and Engineering
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• v.19 no.4 s.60
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• pp.64-68
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• 2005

In this paper, we studied fire position recognition and alarm system when we acquired CCDcamera image of fire region and position. We proposed effectively extraction system of boundary of fire region using RED Filtering, and applied 2-graylevel image method to fire boundary extraction. Finally we can make system of fire position and region using mask extraction and matching for fire recognition. For the purpose of experiment result, we effectively recognized that the tire occurrence position and region have steadily spread.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.3C
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• pp.279-287
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• 2009

In this paper, a hierarchical stereo matching with color information is proposed. To generate an initial disparity map, feature based stereo matching is carried out and to generate a final disparity map, hierarchical stereo matching is carried out. The boundary (edge) region is obtained by segmenting a given image into R, G, B and White components. From the obtained boundary, disparity is extracted. The initial disparity map is generated when the extracted disparity is spread to the surrounding regions by evaluating autocorrelation from each color region. The initial disparity map is used as an initial value for generating the final disparity map. The final disparity map is generated from each color region by changing the size of a block and the search range. 4 test images that are provided by Middlebury stereo vision are used to evaluate the performance of the proposed algorithm objectively. The experiment results show better performance compared to the Graph-cuts and Dynamic Programming methods. In the final disparity map, about 11% of the disparities for the entire image were inaccurate. It was verified that the boundary for the non-contiguous point was clear in the disparity map.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.1
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• pp.102-110
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• 2015

In this paper, adaptive matching method using the same features for rigid and deformable object images is proposed. Firstly, we determine whether the two images are matched or not using the geometric verification and generate the matching information. Decision boundary which separates deformable matching-pair from non-matching pair is obtained through statistical analysis of matching information. The experimental result shows that the proposed method lowers the computational complexity and increases the matching accuracy compared to the existing method.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.327-328
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• 2007

A contour shape matching based pixel motion estimation is proposed. The pixel motion information is very useful to compensate the motion artifact generated at the specific gray level contours in the moving image for subfield gray-scale display devices. In this motion estimation method, the gray level boundary contours are extracted from the input image. Then using contour shape matching, the most similar contour in next frame is found, and the contour is divided into segment unit. The pixel motion vector is estimated from the displacement of the each segment in the contour by segment matching. From this method, more precise motion vector can be estimated and this method is more robust to image motion with rotation or from illumination variations.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.820-823
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• 1996

In contrast to parts of relatively simple shapes, it is important to match their cross-sectional shapes during mating parts of complicated shapes. It requires the 2.pi. information along their matching boundary to figure out their relative geometrical shapes. In this paper, we propose a method measuring a misalignment at the interface during mating parts with the complicated shapes by using the omnidirectional image sensing system(OLSSA). Also we carried out experiments in order to prove the method, and the results show the feasibility.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1067-1087
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• 2018

In a study for LiDAR data based building boundary extraction, usually dense point cloud was used to cluster building rooftop area and extract building outline. However, when we used DSM generated from stereo image matching to extract building boundary, it is not trivial to cluster building roof top area automatically due to outliers and large holes of point cloud. Thus, we propose a technique to extract building boundary semi-automatically from the DSM created from stereo images. The technique consists of watershed segmentation for using user input as markers and recursive MBR algorithm. Since the proposed method only inputs simple marker information that represents building areas within the DSM, it can create building boundary efficiently by minimizing user input.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.279-286
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• 2000

The objective of this research is to detect the papaya fruits on tree in an orchard. The detection of papaya on natural background is difficult because colors of fruits and background such as leaves are similarly green. We cannot separate it from leaves by color information. Therefore, this research will use shape information instead. First, we detect an interested object by detecting its boundary using edge detection technique. However, the edge detection will detect every objects boundary in the image. Therefore, shape description technique will be used to describe which one is the interested object boundary. The good shape description should be invariant in scaling, rotating, and translating. The successful concept is to use Fourier series, which is called "Fourier Descriptors". Elliptic Fourier Descriptors can completely represent any shape, which is selected to describe the shape of papaya. From the edge detection image, it takes a long time to match every boundary directly. The pre-processing task will reduce non-papaya edge to speed up matching time. The deformable template is used to optimize the matching. Then, clustering the similar shapes by the distance between each centroid, papaya can be completely detected from the background.