• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.6
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• pp.861-870
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• 1990

A method of recognizing objects is proposed that uses a concept of modified incremental circle transform. The modified incremental circle transform, which maps bundaries of an object into an unit circle, represnets efficiently the shape of the boundaries detected in digitized binary images of the objects. It is proved that modified incremental circle transform of object, which is invariant under object translation, rotation, and size, can be used as feature information for recognizing two dimensional polygonal object efficiently.

• Journal of the Chungcheong Mathematical Society
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• v.22 no.1
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• pp.65-71
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• 2009

Let f be an 2-isometry on a non-Archimedean 2-normed space. In this paper, we prove that the barycenter of triangle is invariant for f up to the translation by f(0), in this case, needless to say, we can imply naturally the Mazur-Ulam theorem in non-Archimedean 2-normed spaces.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.484-486
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• 2002

패턴의 이동, 회전, 크기변화에 영향을 받지 않는 불변 패턴 인식은 컴퓨터 비젼 및 패턴인식에서 오랫동안 다루어온 문제이다. 본 논문에서는 픽셀간의 거 리를 히스토그램으로 나타냄으로써 2차원 이진 패턴을 1차원 신호로 표현하는 방법을 제시한다. 제시되는 방법을 디스토그램(Distogram)이라 부르며 6개 로마문자의 이동, 회전, 크기 변화된 이미지를 테스트해봄으로써 디스토그램의 식별 능력을 테스트해본다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.305-308
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• 2002

패턴 인식(Patterns Recognition)은 인공 지능의 한 분야로서 이해할 수 있는데, 요즈음은 보안과 관련하여 많은 연구가 진행되고 있다. 웨이블렛 변환(Wavelet Transform)은 공간-주파수 영역에서 신호의 국소화를 효율적으로 구현할 수 있다. 하지만, 이를 패턴 인식의 특징 추출에 그대로 이용할 경우 입력 신호의 위치 이동 등이 문제가 되며, 이것은 또한 에러 요인이 된다. 본 논문에서는 웨이블렛 변환을 패턴 인식에 적용할 경우 발생하는 입력 신호의 위치이동에 따른 문제점을 보완하여, 개선된 방법으로 패턴 인식에 사용할 수 있는 알고리즘을 제안하며, 실험 결과를 바탕으로 그의 타당성을 보인다.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.6
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• pp.88-100
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• 1998

In this paper, an algorithm for a real-time automatic fingerprint identification system is proposed. The fingerprint feature volume is extracted by considering distinct and local characteristics(such as intensity and image quality difference etc.) in fingerprint images, which makes the algorithm properly adaptive to various image acquisitionj methods. Also the matching technique is designed to be invariant on rotation, scaling and translation (RST) changes while being capable of real-time processing. And the classification of fingerprints is performed based on the ridge flow and the relations among singular points such as cores and deltas. The developed fingerprint identification algorithm has been applied to various sets of fingerprint images such as one from NIST(National Institute of Standards and Technology, USA), a pressed fingerprint database constructed according to Korean population distributions in sex, ages and jobs, and a set of rolled-than-scanned fingerprint images. The overall performance of the algorithm has been analyzed and evaluated to the false rejection ratio of 0.07% while holding the false acceptance ratio of 0%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.12
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• pp.2586-2594
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• 2009

A digital watermarking technique used as a protection and certifying mechanism of copyrighted creations including music, still images, and videos in terms of finding any loss in data, reproduction and pursuit. This study suggests using a selected geometric invariant point through the whole processing procedure of an image and inserting and extracting based on the invariant point so that it will be robust in a geometric transformation attack. The introduced algorithm here is based on a watershed splitting method in order to make medical images strong against RST(Rotation Scale, Translation) transformation and other processing. It also helps to maintain the watermark in images that are compressed and stored for a period of time. This algorithm also proved that is has robustness against not only JPEG compression attack, but also RST attack and filtering attack.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.3
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• pp.341-351
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• 2003

Digital image watermarking is the method that can protect the copyright of the image by embedding copyright information, which is called watermark. Watermarking must have robustness to intentional or unintentional data changing, called attack. The conventional watermarking schemes are robust to waveform attacks such as image compression, filtering etc. However, they are vulnerable to geometrical attacks such as rotation, scaling, translation, and cropping. Accordingly, this paper proposes new watermarking scheme that is robust to geometrical attacks by using invariant centroid. Invariant centroid is the gravity center of a central area in a gray scale image that remains unchanged even when the image is attacked by RST including cropping and proposed scheme uses invariant centroids of original and inverted image as the template. To make geometrically invariant domain, template and angle compensated Log -Polar Map(LPM) is used. Then Discrete Cosine Transform(DCT) is performed and the watermark is embedded into the DCT coefficients. Futhermore, to prevent a watermarked image from degrading due to interpolation during coordinate system conversion, only the image of the watermark signal is extracted and added to the original image. Experimental results show that the proposed scheme is especially robust to RST attacks including cropping.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.6
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• pp.149-156
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• 2003

This paper proposes a face recognition method based on modified Otsu binarization, Hu moment and linear discriminant analysis (LDA). Proposed method is robust to brightness, contrast, scale, rotation, and translation changes. Modified Otsu binarization can make binary images that have the invariant characteristic in brightness and contrast changes. From edge and multi-level binary images obtained by the threshold method, we compute the 17 dimensional Hu moment and then extract feature vector using LDA algorithm. Especially, our face recognition system is robust to scale, rotation, and translation changes because of using Hu moment. Experimental results showed that our method had almost a superior performance compared with the conventional well-known principal component analysis (PCA) and the method combined PCA and LDA in the perspective of brightness, contrast, scale, rotation, and translation changes with Olivetti Research Laboratory (ORL) database and the AR database.

• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.767-776
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• 2020

GcGAN is a deep learning model to translate styles between images under geometric consistency constraint. However, GcGAN has a disadvantage that it does not properly maintain detailed content of an image, since it preserves the content of the image through limited geometric transformation such as rotation or flip. Therefore, in this study, we propose a new image-to-image translation method, MSGcGAN(Multi-Scale GcGAN), which improves this disadvantage. MSGcGAN, an extended model of GcGAN, performs style translation between images in a direction to reduce semantic distortion of images and maintain detailed content by learning multi-scale images simultaneously and extracting scale-invariant features. The experimental results showed that MSGcGAN was better than GcGAN in both quantitative and qualitative aspects, and it translated the style more naturally while maintaining the overall content of the image.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.3
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• pp.217-226
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• 2003

A novel fingerprint ridge feature extraction using sequential labeling of thinned fingerprint image is proposed, which is invariant to position translation, scaling, and rotation. the proposed algorithm labels ridges of thinned fingerprint image sequentially using vertical line that goes through fingerprint core point. Then, we extract a feature from each labeled ridge and the extraction process is based on the type fo the ridge and a minutiae ridge angle in the ridge. The feature extracted through this process enables us to find out the kind of various minutiae and minutiae angle. As a result of the experiment using two thinned fingerprint images, we finally confirm that proposed algorithm is not related to position translation, scaling, and rotation.