• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.177-180
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• 2002

In this paper, an effective digital watermarking method for copyright protection of binary image data is proposed. First, a binary image is grouped into feature regions which have geometrical features and general one. The watermark for authentication is embedded in general regions in order to preserve geometrical features regions. We have used run-length code and special runs for grouping feature regions and general one. For invisibility of watermark, we have embedded the watermark considering transition sensitivity of each pixel in general regions. The proposed method is applied to some binary image such as character, signature, seal, and fingerprint image to evaluate performance. By the experimental results, the proposed method preserve feature regions of original image and have higher invisibility of watermarks.

• Journal of Biosystems Engineering
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• v.17 no.2
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• pp.143-155
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• 1992

The aim of this study is to develop a general purpose algorithm for analyzing geometrical features of agricultural products and microscopic particles regardless of their numbers, shapes and positions with a computer vision system. Primarily, boundary informations of an image were obtained by Scan Line Coding and Scan & Chain Coding methods and then with these informations, geometrical features such as area, perimeter, lengths, widths, centroid, major and minor axes, equivalent circle diameter, number of individual objects, etc, were analyzed. The algorithms developed in this study was evaluated with test images consisting of a number of randomly generated ellipsoids or a few synthesized diagrams having different features. The result was successful in terms of accuracy.

• Journal of Biosystems Engineering
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• v.22 no.2
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• pp.227-236
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• 1997

Manual grading and sorting of red-ginsengs are inherently unreliable due to its subjective nature. A computerized technique based on optical and geometrical characteristics was studied for the objective quality evalution. Spectral reflectance of three categories of red-ginsengs - "Chunsam", "Chisam", "Yangsam" - were measured and analyzed. Variation of reflectance among parts of a single ginseng was more significant than variation among the quality categories of ginsengs. A PC-based image processing algorithm was developed to extract geometrical features such as length and thickness of body, length and number of roots, position of head and branch point, etc. The algorithm consisted of image segmentation, calculation of Euclidean distance, skeletonization and feature extraction. Performance of the algorithm was evaluated using sample ginseng images and found to be mostly sussessful.

• 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.

• Publications of The Korean Astronomical Society
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• v.20 no.1 s.24
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• pp.43-48
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• 2005

We present a high resolution spectrum of PU Vul observed at Bohyunsan Optical Astronomy Observatory (BOAO) on April 9, 2004. Permitted emission and nebular lines of PU Vul had been significantly changed compared to all spectra observed since its eruption in 1979. Therefore all new lines should be re-identified and were done so. We do-convoluted a $H{\beta}$ line into several emission components with Gaussian functions. Then we carefully discussed the geometrical feature of PU Vul in April 2004.

• Publications of The Korean Astronomical Society
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• v.21 no.2
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• pp.35-42
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• 2006

We report a high resolution spectrum of AG Pegasi observed at Bohyunsan Optical Astronomy Observatory (BOAO) on October 2, 2004. Some of permitted emission lines, for example H I, He I, He II, Fe II and Ti II were observed in the spectrum of AG Pegasi in 2004. Lines presented in the longer wavelength region than $6500{\AA}$ are identified. And radial velocities for each element are measured. Then we carefully discuss the geometrical feature of AG Pegasi in October 2004.

• IE interfaces
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• v.18 no.3
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• pp.247-252
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• 2005

In the automated production environment in the present days, the minimization of manual operation becomes a very important factor in increasing the efficiency of the production system. The exit burr produced through the milling operation on the edge of workpiece usually requires manual deburring process to enhance the level of precision of the resulting product. So far, researchers have developed various methods to understand the formation of exit burr in cutting process. One method to analytically identify the formation of exit burr was to use the geometrical information of CAD and CAM data used in automated machining. This method, in turn, generated the information resulting from the analysis such as burr type, cutting region, and exit angle. Up to now, the geometrical data were restricted to the single feature and single path. In this paper, a method to deal with the complicated geometric features such as line segment, arc, hole, and spline will be presented and validated using the field data. This method also deals with the complex workpiece shape which is a combination of multiple features. As for the cutting path, multiple tool path is analyzed in order to simulate the real cutting process. All this analysis is combined into a Windows based software and real data are used to validate the program in the conclusion.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.12
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• pp.2844-2851
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• 2015

How to recover from the multiple 2D images into 3D object has been widely studied in the field of computer vision. In order to improve the accuracy of the recovered 3D shape, it is more important that noise must be minimized and the number of image frames must be guaranteed. However, potential noise is implied when tracking feature points. And the number of image frames which is consisted of an observation matrix usually decrease because of tracking failure, occlusions, or low image resolution, and so on. Therefore, it is obviously essential that the number of image frames must be secured by recovering the missing feature points under noise. Thus, we propose the analytic approach which can control directly the error distance and orientation of missing feature point by the geometrical properties under noise distribution. The superiority of proposed method is demonstrated through experimental results for synthetic and real object.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.6-8
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• 2005

Study that uses geometrical information in computer vision is lively. Problem that should be preceded is matching problem before studying. Feature point should be extracted for well matching. There are a lot of methods that extract feature point from former days are studied. Because problem does not exist algorithm that is applied for all images, it is a hot water. Specially, it is not easy to find feature point in endoscope image. The big problem can not decide easily a point that is predicted feature point as can know even if see endoscope image as eyes. Also, accuracy of matching problem can be decided after number of feature points is enough and also distributed on whole image. In this paper studied algorithm that can apply to endoscope image. SIFT method displayed excellent performance when compared with alternative way (Affine invariant point detector etc.) in general image but SIFT parameter that used in general image can't apply to endoscope image. The gual of this paper is abstraction of feature point on endoscope image that controlled by contrast threshold and curvature threshold among the parameters for applying SIFT method on endoscope image. Studied about method that feature points can have good distribution and control number of feature point than traditional alternative way by controlling the parameters on experiment result.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.299-302
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• 2001

The statistical analysis of the feature extraction and the neural networks are proposed to recognize a human face. In the preprocessing step, the normalized skin color map with Gaussian functions is employed to extract the region of face candidate. The feature information in the region of the face candidate is used to detect the face region. In the recognition step, as a tested, the 120 images of 10 persons are trained by the backpropagation algorithm. The images of each person are obtained from the various direction, pose, and facial expression. Input variables of the neural networks are the geometrical feature information and the feature information that comes from the eigenface spaces. The simulation results of$.$10 persons show that the proposed method yields high recognition rates.