• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.4
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• pp.407-414
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• 2008

This study introduces an automatic image matching algorithm that can be applied for the scale different image pairs consisting of the satellite pushbroom images and the aerial frame images. The proposed method is based on several image processing techniques such as pre-processing, filtering, edge thinning, interest point extraction, and key-descriptor matching, in order to enhance the matching accuracy and the processing speed. The proposed method utilizes various characteristics, such as the different geometry of image acquisition and the different radiometric characteristics, of the multi-sensor images. In addition, the suggested method uses the sensor model to minimize search area and eliminate false-matching points automatically.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.6_1
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• pp.583-590
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• 2012

This study proposes fusion image matching method according to land cover property to generate a detailed DEM using the high resolution IKONOS-2 stereo pair. A classified image, consists of building, crop-land, forest, road and shadow-water, is produced by color image with four bands. Edges and points are also extracted from panchromatic image. Matching is performed by the cross-correlation computing after five classes are automatically selected in a reference image. In each of building class, crop-land class, forest class and road class, matching was performed by the grid and edge, only grid, only grid, grid and point, respectively. Shadow-water class was excepted in the matching because this area causes excessive error of the DEM. As the results, edge line, building and residential area could be expressed more dense than DEM by the conventional method.

• Journal of KIISE:Databases
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• v.36 no.2
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• pp.73-83
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• 2009

In this paper we propose an object similarity matching method based on shape characteristics of an object in an image. The proposed method extracts edge points from edges of objects and generates a log polar histogram with respect to each edge point to represent the relative placement of extracted points. It performs the matching in such a way that it compares polar histograms of two edge points sequentially along with edges of objects, and uses a well-known k-NN(nearest neighbor) approach to retrieve similar objects from a database. To verify the proposed method, we've compared it to an existing Shape-Context method. Experimental results reveal that our method is more accurate in object matching than the existing method, showing that when k=5, the precision of our method is 0.75-0.90 while that of the existing one is 0.37, and when k=10, the precision of our method is 0.61-0.80 while that of the existing one is 0.31. In the experiment of rotational transformation, our method is also more robust compared to the existing one, showing that the precision of our method is 0.69 while that of the existing one is 0.30.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.2
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• pp.74-81
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• 2005

As the multimedia data increases, various scene change detection algorithms for video indexing and sequence matching have been proposed to efficiently manage and utilize digital media. In this paper, we propose a robust scene change detection algorithm for video sequences with abrupt luminance variations. To improve the accuracy and to reduce the computational complexity of video indexing with abrupt luminance variations, the proposed algorithm utilizes edge features as well as color features, which yields a remarkably better performance than conventional algorithms. In the proposed algorithm first we extract the candidate shot boundaries using color histograms and then determine using edge matching and luminance compensation if they are shot boundaries or luminance changes. If the scene contains trivial brightness variations, the edge matching and luminance compensation are performed only for shot boundaries. In experimental results, the proposed method gives remarkably a high performance and efficiency than the conventional methods with the similar computational complexity.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.5C
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• pp.487-495
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• 2007

When error occurs during the network transmission of the image, the quality of the restored image is very serious. Therefore to maintain the received image quality, the error concealment technique is necessary. This paper presents an efficient spatial error concealment method using adaptive edge-oriented interpolation. It deals with errors on slice level. The proposed method uses boundary matching method having 2-step processes. We divide error block into external and internal region, adaptively restore each region. Because this method use overall as well as local edge characteristics, it preserves edge continuity and texture feature. The proposed technique reduces the complexity and provide better reconstruction quality for damaged images than the previous methods.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.12
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• pp.55-62
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• 1998

Matching two images is an essential step for many computer vision applications. A new approach to the scale and rotation invariant scene matching, using linear features, is presented. Scene or model images are described by a set of linear features approximating edge information, which can be obtained by the conventional edge detection, thinning, and piecewise linear approximation. A set of candidate parameters are hypothesized by mapping the angular difference and a new distance measure to the Hough space and by detecting maximally consistent points. These hypotheses are verified by a fast linear feature matching algorithm composed of a single-step relaxation and a Hough technique. The proposed method is shown to be much faster than the conventional one where the relaxation process is repeated until convergence, while providing matching performance robust to the random alteration of the linear features, without a priori information on the geometrical transformation parameters.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.655-661
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• 2020

SGM (Semi Global Matching) can be used to find all the conjugate points between stereo images. Therefore, it enables high-density DSM (Digital Surface Model) production from high-resolution satellite images. However, water, shadows, and occlusion areas cause mismatching of the surrounding points in this method. Particularly, in buildings with large-parallax and elongated-shapes such as a Korean style apartment, it is difficult to reconstruct the 3D building even if the SGM method is applied to a high-resolution 50cm satellite image. This study proposed and performed the SGM technique with a classified image and an edge image from the IKONOS-2 satellite stereo-image with a 1m resolution to produce DSM. It was compared with the DSMs from the general SGM and the high-density ABM (Area Based Matching) matching of ERDAS software. The results of the apartment DSM by the proposed method were the best in the test area. As a result, despite the image having a resolution of 1m, the outline of the building DSM could be expressed more clearly than the existing method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.3C
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• pp.133-140
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• 2005

This paper introduces a spatial error concealment technique using directional interpolation in block-based compression. The first step involves finding the spatial direction vectors represented an edge-direction in the lost block using spatial boundary matching algorithm. Then, the error blocks are recovered by directional interpolation through these vectors and concealed by using the recovered blocks which have lower directional boundary matching error out of them relatively. This proposed method is able to deal with errors on macroblock or slice level adaptively. And it has lower complexity and maintains better performance compared to the conventional methods.

• The KIPS Transactions:PartB
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• v.15B no.4
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• pp.269-274
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• 2008

In this paper, we propose a new stereo correspondence method for generating excellent external energy for snake-based object segmentation methods in stereo images. Our method first generates an edge-based disparity map by performing stereo correspondence between multi-level edge maps of the stereo image pair. Only edges of similar strength are considered for matching. To filter the disparity map for edges of the object of interest, the method estimates the object's disparity value by matching the pattern of edges of the region of interest in the left image against candidate patterns in the right image. The filtered edge map is then used to generate external energy for the snake. The proposed method has been tested on two snake models and results show a noticeable enhancement on performance of the snake when compared with other methods.