• Journal of Korean Society for Geospatial Information Science
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• v.4 no.1 s.6
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• pp.93-102
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• 1996

For an atomatic generation of DEM(Digital Elevation Model) by computer, it is a time-consumed work to determine adquate matches from stereo images. Correlation and evenly distributed area-based method is generally used for matching operation. In this paper, we propose a new approach that computes matches efficiantly by changing the size of mask window and search area according to the given terrain information. For image segmentation, at first edge-preserving smoothing filter is used for preprocessing, and then region growing algorithm is applied for the filterd images. The segmented regions are classifed into mountain, plain and water area by using MRF(Markov Random Filed) model. Maching is composed of predicting parallex and fine matching. Predicted parallex determines the location of search area in fine matching stage. The size of search area and mask window is determined by terrain information for each pixel. The execution time of matching is reduced by lessening the size of search area in the case of plain and water. For the experiments, four images which are covered $10km{\times}10km(1024{\times}1024\;pixel)$ of Taejeon-Kumsan in each are studied. The result of this study shows that the computing time of the proposed method using terrain information for matching operation can be reduced from 25% to 35%.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.18 no.3
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• pp.263-269
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• 2000

As the accuracy of digital photogrammetry is restricted by the resolution of image to be used, it is axiomatic that the resolution of image should be improved. As for the method to constitute hardware with CCD sensor that capacity was expanded or the method to acquire the image of high resolution by deciding the quantity of sub-pixel in advance through moving sensor, the price is expensive. This study tries to enhance the resolution of low resolution image by acquiring the image with the digital camera that the price is cheap and deciding shifts and rotations through matching multiple digital image by means of least square method. As the result of study, the resolution of digital image was improved greatly. So, not only the digital photogrammetry which has the competitive power of price economically is possible in the future but also the application is expected widely.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.8
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• pp.1792-1801
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• 2003

In these days, image mosaic is getting interest in the field of advertisement, tourism, game, medical imaging, and so on with the development of internet technology and the performance of personal computers. The main problem of mage mosaic is searching corresponding points correctly in the overlapped area between images. However, previous methods requires a lot of CPU times and data processing for finding corresponding points. And they need repeated recording with a revolution of 360 degree around objects or background. This paper presents a new image mosaic method which generates a panorama image from a video sequence recorded by a general video camera. Our method finds the corresponding points between two successive images by using a new direction oriented 3­step block matching methods. Experimental results show that the suggested method is more efficient than the methods based on existing block matching algorithm, such as full search and K­step search algorithm.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.4
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• pp.443-452
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• 2008

To deduce 3D linear information which express shapes of buildings out of airphoto by fusion of airphoto and LiDAR data, this research went through 2 process. First, research made LiDAR data into projected data of 2D based on airphoto. For this, the virtual points were added to solve the visual problem of building boundary area which has poor information because the attribute in LiDAR data. Research construct irregular triangular nets from modified LiDAR data and judge visual triangular nets out of image. Through this, research can make reference to information of triangular nets in each image pixel. Second, 3D information was extracted from stereo images segments by combining extracted information of visible region and 2D irregular triangular nets. Matching way based on TIN for segments from stereo images was used. Matching condition based on TIN can improve about 20% of edge matching accuracy compared to existing quadrilateral condition of epipolar geometry.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.17 no.4
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• pp.321-330
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• 1999

Automation of observation and positioning of fiducial marks is made possible with the application of image matching technique, developed through the cooperative research effort of computer vision and digital photogrammetry. The major problem in such automation effort is to minimize the computing time and to increase the positional accuracy. Except for scanning and ground control surveying, the interior orientation process was automated in this study, through the development of an algorithm which applies the image matching and image processing techniques. The developed system was applied to close-range photogrammetry and the analysis of the results showed 54% improvement in processing time. For fiducial mark observation during interior orientation, the Laplacian of Gaussian transformation and the Hough transformation were applied to determine the accurate position of the center point, and the correlation matching and the least squares matching method were then applied to improve the accuracy of automated observation of fiducial marks. Image pyramid concept was applied to reduce the computing time of automated positioning of fiducial mark.

• 한국전산유체공학회:학술대회논문집
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• 1998.11a
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• pp.13-18
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• 1998

The practical use of the particle image velocimetry(PIV), a whole-field velocity measurement method, requires the use of fast, reliable, computer-based methods for tracking velocity vectors. The full search block matching, the most widely studied and applied technique both in area of PIV and Image Coding and Compression, is computationally costly. Many less expensive alternatives have been proposed mostly in the area of Image Coding and Compression. Among others, TSS, NTSS, HPM are introduced for the past PIV analysis, and found to be successful. But, these algorithms are based on small dynamic range, 7 pixels/frame in maximum displacement. To analyze the images with large displacement, Even and Odd field image separation and a simple version of multi-resolution hierarchical procedures are introduced in this paper. Comparison with other algorithms are summarized. A Results of application to the turbulent backward step flow shows the improvement of new algorithm.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.519-525
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• 2006

The traditional area-based matching or efficient matching methods using epipolar geometry and height restriction of stereo images, which have a confined search space for image matching, have still some disadvantages such as mismatching and timeconsuming, especially in the dense metropolitan city that very high and similar buildings exist. To solve these problems, a new image matching method through building recognition has been presented. This paper described building recognition in color stereo images using edge and color information as a elementary study of new matching scheme. We introduce the modified Hausdorff distance for using edge information, and the modified color indexing with 3-D RGB histogram for using color information. Color information or edge information alone is not enough to find conjugate building pairs. For edge information only, building recognition rate shows 46.5%, for color information only, 7.1%. However, building recognition rate distinctly increase 78.5% when both information are combined.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.545-554
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• 2019

This research aims to provide a building area extraction approach over the areas where data acquisition is impossible through field surveying, aerial photography and lidar scanning. Hence, high-resolution satellite images, which have high accessibility over the earth, are utilized for the automated building extraction in this study. 3D point clouds or DSM (Digital Surface Models), derived from the stereo image matching process, provides low quality of building area extraction due to their high level of noises and holes. In this regards, this research proposes a hybrid building area extraction approach which utilizes 3D point clouds (from image matching), and color and linear information (from imagery). First of all, ground and non-ground points are separated from 3D point clouds; then, the initial building hypothesis is extracted from the non-ground points. Secondly, color based building hypothesis is produced by considering the overlapping between the initial building hypothesis and the color segmentation result. Afterwards, line detection and space partitioning results are utilized to acquire the final building areas. The proposed approach shows 98.44% of correctness, 95.05% of completeness, and 1.05m of positional accuracy. Moreover, we see the possibility that the irregular shapes of building areas can be extracted through the proposed approach.

• Journal of the Korea Society of Computer and Information
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• v.21 no.9
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• pp.19-25
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• 2016

This paper is to recognize and play tab chords from guitar musical sheets. The musical chord area of an input image is segmented by changing the image in saturation and applying the Grabcut algorithm. Based on a template matching, our approach detects tab starting sections on a segmented musical area. The virtual block method is introduced to search blanks over chord lines and extract tab fret segments, which doesn't cause the computation loss to remove tab lines. In the experimental tests, the prototype based classification outperforms Bayesian method and the nearest neighbor rule with the whole set of training data and its performance is similar to that of the support vector machine. The experimental result shows that the prediction rate is about 99.0% and the number of selected prototypes is below 3.0%.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.13-20
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• 2024

This paper introduces a method for generating model images that can identify specific cylindrical medicine containers in videos and investigates data collection techniques. Previous research had separated object detection from specific object recognition, making it challenging to apply automated image stitching. A significant issue was that the coordinate-based object detection method included extraneous information from outside the object area during the image stitching process. To overcome these challenges, this study applies the newly released YOLOv8 (You Only Look Once) segmentation technique to vertically rotating pill bottles video and employs the ORB (Oriented FAST and Rotated BRIEF) feature matching algorithm to automate model image generation. The research findings demonstrate that applying segmentation techniques improves recognition accuracy when identifying specific pill bottles. The model images created with the feature matching algorithm could accurately identify the specific pill bottles.