• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.210-213
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• 2000

In the closed range space, the parallel two CCD cameras are used to acquire a pair of stereo image. The acquired stereo image are computed with Wavelet Transform repeatedly and including the low frequency component, the image size of those are reduced. It is the pyramid structure. The optimum matching point is searched to the pixel. Then appling the optimum matching point to DLT, it extract the three - dimensional surface coordinate from a stereo image. The direct linear transformation(DLT) method is used to calibrate the stereo camera compute the coordinate on a three dimensional space. To find the parameters for the DLT method, 30 control points which marked on the cylinder type object are used. To improve the matching algorithm, the paper select the pyramid structure for Wavelet Transform. The acquired disparity information is used to represent the really three-dimensional surface coordinate.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.10a
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• pp.141-146
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• 2003

In case of producing image map by using the color aerial photograph, DEM makes on huge effects to the accuracy of ortho image. Thus, this paper has the purpose that evaluate the accuracy of DEM acquired by matching the color aerial photograph. At the study, result of color aerial photograph's control point surveying was X=${\pm}$0.14m, f=${\pm}$0.16m. Estimated result by DEM of plot-map and matching has RMSE=${\pm}$1.058m for the elevation(Z). For matching DEM has a minor(-)'s value, it can access that produce by high point than plot-map DEM.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.11a
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• pp.226-230
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• 2002

This paper proposes a method of improvement of accuracy of projective transformation matrix for Image Mosaicing. Using shift theorem, we extracted global translation components between images and using translation components, we found matching points between images so we solve general matching point problem we extracted highly trusted matching point using RANSAC algorithm. we normalized matching point coordinates and improved accuracy of projective transformation matrix.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.5
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• pp.960-966
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• 2017

In this paper, we proposed an algorithm that can extract lesion by inputting a medical image. Feature points are extracted using SIFT algorithm to extract genetic training of medical image. To increase the intensity of the feature points, the input image and that raining image are matched using vector similarity and the lesion is extracted. The vector similarity match can quickly lead to lesions. Since the direction vector is generated from the local feature point pair, the direction itself only shows the local feature, but it has the advantage of comparing the similarity between the other vectors existing between the two images and expanding to the global feature. The experimental results show that the lesion matching error rate is 1.02% and the processing speed is improved by about 40% compared to the case of not using the feature point intensity information.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.3
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• pp.305-323
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• 2010

This paper proposes an efficient and yet powerful local descriptor called phase-space partition based descriptor (PPD). This descriptor is designed for the mobile image matching and retrieval. PPD, which is inspired from SIFT, also encodes the salient aspects of the image gradient in the neighborhood around an interest point. However, without employing SIFT's smoothed gradient orientation histogram, we apply the region based gradient statistics in phase space to the construction of a feature representation, which allows to reduce much computation requirements. The feature matching experiments demonstrate that PPD achieves favorable performance close to that of SIFT and faster building and matching. We also present results showing that the use of PPD descriptors in a mobile image retrieval application results in a comparable performance to SIFT.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.12
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• pp.124-130
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• 2012

In this paper, we propose a feature point selection method for MPEG CDVS CE-7 which is processing on International Standard task. Among a large number of extracted feature points, more important feature points which is used in image matching should be selected for the compactness of image descriptor. The proposed method is that remove the feature point in the extraction phase which is filtered by nearest neighbor distance ratio matching in the matching phase. We can avoid the waste of the feature point and employ additional feature points by the proposed method. The experimental results show that our proposed method can obtain true positive rate improvement about 2.3% in pair-wise matching test compared with Test Model.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1025-1034
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• 2022

In this paper, we propose a post-processing method through interpolation of hole regions that occur when extracting point clouds. When image matching is performed on stereo image data, holes occur due to occlusion and building façade area. This area may become an obstacle to the creation of additional products based on the point cloud in the future, so an effective processing technique is required. First, an initial point cloud is extracted based on the disparity map generated by applying stereo image matching. We transform the point cloud into a grid. Then a hole area is extracted due to occlusion and building façade area. By repeating the process of creating Triangulated Irregular Network (TIN) triangle in the hall area and processing the inner value of the triangle as the minimum height value of the area, it is possible to perform interpolation without awkwardness between the building and the ground surface around the building. A new point cloud is created by adding the location information corresponding to the interpolated area from the grid data as a point. To minimize the addition of unnecessary points during the interpolation process, the interpolated data to an area outside the initial point cloud area was not processed. The RGB brightness value applied to the interpolated point cloud was processed by setting the image with the closest pixel distance to the shooting center among the stereo images used for matching. It was confirmed that the shielded area generated after generating the point cloud of the target area was effectively processed through the proposed technique.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.8
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• pp.640-646
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• 2003

We presents an edge-based point correlation algorithm for fast and stable visual inspection system. Conventional algorithms based on NGC(normalized gray-level correlation) have to overcome some difficulties in applying automated inspection systems to real factory environment. First of all, NGC algorithms involve highly complex computation and thus require high performance hardware for realtime process. In addition, lighting condition in realistic factory environments is not stable and therefore intensity variation from uncontrolled lights gives many troubles for applying NGC directly as pattern matching algorithm. We propose an algorithm to solve these problems, using thinned and binarized edge data, which are obtained from the original image. A point correlation algorithm with the thinned edges is introduced with image pyramid technique to reduce the computational complexity. Matching edges instead of using original gray-level image pixels overcomes problems in NGC method and pyramid of edges also provides fast and stable processing. All proposed methods are proved by the experiments using real images.

• Journal of Korean Society for Geospatial Information Science
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• v.5 no.2 s.10
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• pp.99-110
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• 1997

Image matching to determine the conjugate points in stereo photos is the one of the most important subject in digital photogrammetry and many researches In digital photogrammetric field are on going to automate the image matching process. In this study, we analyzes the effect of allowable correlation coefficient, which controls the accuracy in areal based image matching, on the accuracy of digital photogrammetry. So, some areal based matching methods such as image correlation coefficient matching, image Pyramid matching and interest point matching, are implemented, and the effect of allowable correlation coefficient on accuracy of digital photogrammetry in each method is analyzed. As a result of this study, a method to determine the optimal correlation coefficient is presented.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.9
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• pp.714-719
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• 2003

We propose a measuring method of large object using the pattern matching. It is hard and expensive to get the complete 3D data when the object is large and exceeds the limit of measuring devices. The large object is divided into several smaller areas and is scanned several times to get the data of all the pieces. These data are aligned to get the complete 3D data using the pattern matching method such as point pattern matching method and transform matrix algorithm. The laser slit beam and CCD camera are applied for the experimental measurement. Visual C＋＋ on Windows 98 is implemented in processing the algorithm.