• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.1
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• pp.59-65
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• 2012

In this paper, we proposed a method for automatic detection of a updating object from spatial data sets of different scale and updating cycle by using areal feature matching based on shape similarity. For this, we defined a updating object by analysing matching relationships between two different spatial data sets. Next, we firstly eliminated systematic errors in different scale by using affine transformation. Secondly, if any object is overlaid with several areal features of other data sets, we changed several areal features into a single areal feature. Finally, we detected the updating objects by applying areal feature matching based on shape similarity into the changed spatial data sets. After applying the proposed method into digital topographic map and a base map of Korean Address Information System in South Korea, we confirmed that F-measure is highly 0.958 in a statistical evaluation and that significant updating objects are detected from a visual evaluation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.5
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• pp.411-419
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• 2013

Research on developing algorithms for building modeling such as extracting outlines of the buildings and segmenting patches of the roofs using aerial images or LiDAR data are active. However, utilizing information from the building model is not well implemented yet. This study aims to propose a scheme for search identical or similar shape of buildings by utilizing graph topology pattern matching under the assumptions: (1) Buildings were modeled beforehand using imagery or LiDAR data, or (2) 3D building data from digital maps are available. Side walls, segmented roofs and footprints were represented as nodes, and relationships among the nodes were defined using graph topology. Topology graph database was generated and pattern matching was performed with buildings of various shapes. The results show that efficiency of the proposed method in terms of reliability of matching and database structure. In addition, flexibility in the search was achieved by altering conditions for the pattern matching. Furthermore, topology graph representation could be used as scale and rotation invariant shape descriptor.

• Journal of KIISE:Software and Applications
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• v.32 no.11
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• pp.1013-1020
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• 2005

This paper presents an effective and robust leaf image retrieval system based on shape feature. Specifically, we propose an improved MPP algorithm for more effective representation of leaf images and show a new dynamic matching algorithm that basically revises the Nearest Neighbor search to reduce the matching time. In particular, both leaf shape and leaf arrangement can be sketched in the query for better accuracy and efficiency. In the experiment, we compare our proposed method with other methods including Centroid Contour Distance(CCD), Fourier Descriptor, Curvature Scale Space Descriptor(CSSD), Moment Invariants, and MPP. Experimental results on one thousand leaf images show that our approach achieves a better performance than other methods.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.5
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• pp.134-140
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• 2017

Shape-from-shading (SFS) or stereo vision algorithms can be utilized to measure the shape of an object with imaging techniques for effective sensing in non-contact measurements. SFS algorithms could reconstruct the 3D information from a 2D image data, offering relatively comprehensive information. Meanwhile, a stereo vision algorithm needs several feature points or lines to extract 3D information from two 2D images. However, to measure the size of an object with a freeform surface, the two algorithms need some additional information, such as boundary conditions and grids, respectively. In this study, a stereo vision scheme using the depth information obtained by shape-from-shading as patterns was proposed to measure the size of an object with a freeform surface. The feasibility of the scheme was proved with an experiment where the images of an object were acquired by a CCD camera at two positions, then processed by SFS, and finally by stereo matching. The experimental results revealed that the proposed scheme could recognize the size and shape of freeform surface fairly well.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.8
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• pp.335-343
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• 2002

A segment matching algorithm in stereo vision via the fusion of multiple features on long edge segments is proposed. One problem of the previous segment matching algorithm is the similarity among the segments caused from its short length. In the proposed algorithm, edges are composed of longer segments which are obtained by breaking the edges only at the locations with distinguished changes of the shape. Such long segments can contain extra features such as curvature ratio and length of segments which could not be included in shorter ones. Use of such additional features enhances the matching accuracy significantly To fuse multiple features for matching, weighting value determination algorithm which is computed according to the degree of the contribution of each factor is proposed. The stereo matching simulations with the proposed algorithm are done about various images and their results are included.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.209-214
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• 2004

This paper presents a RFM-based image matching algorithm which put constraints on the search space through the object-space approach. Also, the detail procedure of generating 3-D surface models from the RFM is introduced as an end-user point of view. The proposed algorithm provides the PML (Piecewise Matching Line) for image matching and reduces the search space to within the confined line-shape area.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.605-608
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• 2002

A text-dependent speaker recognition system using a robust matching process is studied. The feature histogram of LPC cepstral coefficients for matching is used. The matching process uses mixture network with penalty scores. Using probability and shape comparison of two feature histograms, similarity values are obtained. The experiment results will be shown to show the effectiveness of the proposed algorithm.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.17-20
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• 2000

This paper describes a shape-based object recognition algorithm using multiple distance images. For the images containing dense edge points and noise, previous Hausdorff distance (HD) measures yield a high ms error for object position and many false matchings for recognition. Extended version of HD measure considering edge position and orientation simultaneously is proposed for accurate matching. Multiple distance images are used to calculate proposed matching measure efficiently. Results are presented for visual images and infrared images.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2533-2536
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• 2003

In this paper, we suggest the 3D Vision Inspection Algorithm which is based on the external shape feature, and is able to recognize the object. Because many objects made by human have the regular shape, if we posses the database of pattern and we recognize the object using the database of the object's pattern, we could inspect the objects of many fields. Thus, this paper suggest the 3D Vision inspection Algorithm using the Geometrical Pattern Matching by making the 3D database.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.104-106
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• 2008

This paper proposes an image based method for arranging ship blocks in a dockyard. The problem of appropriately arranging numerous blocks has to be carefully planned because it has close relation to the effectiveness of the whole working process. To implement the system, the block shape and feature points have to be obtained from block image. The block arrangement system can be implemented by the fusion of the block shape extraction and image matching technology.