• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.523-526
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• 2000

본 논문에서는 임의의 모양을 가지는 영상 객체(image object)에 적용 가능한 모양적응 이산변환(PSADT : Polar coordinates shape adaptive discrete transform)에 기반한 새로운 워터마킹 기법을 제안한다. 대수-극 좌표계(log-polar coordinates)와 모양적응 이산변환을 이용하여 제안된 기법은 MPEG-4의 VOP와 같은 임의의 모양을 가지는 영상 객체에 적용할 수 있을 뿐만 아니라 기존 기법에 비하여 회전과 크기 변화와 같은 기하학적인 공격에 대하여 우수한 강인성을 제공한다.

• Proceedings of the KAIS Fall Conference
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• 2008.11a
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• pp.254-256
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• 2008

어안 영상은 화각이 일반 카메라 영상보다 큰 반면, 영상의 피사체 왜곡이 커서 사용자의 인지에 자연스럽지 못하다. 그래서 어안 영상은 원근 영상으로 변환하여 사용하는 것이 일반적이다. 본 논문에서는 스케일링 함수를 이용한 어안 영상의 원근 영상 변환 방법을 제안하였다. 특히 스케일링 함수를 적용한 결과 영상에서 크기 왜곡과 기하학적 왜곡을 감소되는 장점을 보였다.

• Proceedings of the KAIS Fall Conference
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• 2008.05a
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• pp.273-274
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• 2008

어안 렌즈 카메라로 촬영한 어안 영상은 화각이 일반 카메라 영상보다 크다. 반면 영상의 피사체 왜곡이 커서 사용자의 인지에 자연스럽지 못하므로 원근 영상으로 변환하여 사용하는 것이 일반적이다. 본 논문에서는 선형 스케일링을 이용한 어안 영상의 원근 영상 변환 방법을 제안하였다. 선형 스케일링을 적용한 결과 영상에서 크기 왜곡과 기하학적 왜곡을 감소되는 장점을 보였다.

• Journal of Educational Research in Mathematics
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• v.18 no.1
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• pp.51-62
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• 2008

In the 7th-curriculum, only basic arithmetics of complex numbers have been taught. They are taught formally like literal manipulations. This paper analyzes mathematically essential relations between algebra of complex numbers and plane geometry. Historical analysis is also performed to find effective methods of teaching complex numbers in school mathematics. As a result, we can integrates this analysis with school mathematics by help of Viete's operations on right triangles. We conclude that teaching geometric interpretation of complex numbers is possible in school mathematics.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.5
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• pp.313-322
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• 2020

A large volume of data will improve the robustness of deep learning models and avoid overfitting problems. In automatic tongue segmentation, the availability of annotated tongue images is often limited because of the difficulty of collecting and labeling the tongue image datasets in reality. Data augmentation can expand the training dataset and increase the diversity of training data by using label-preserving transformations without collecting new data. In this paper, augmented tongue image datasets were developed using seven augmentation techniques such as image cropping, rotation, flipping, color transformations. Performance of the data augmentation techniques were studied using state-of-the-art transfer learning models, for instance, InceptionV3, EfficientNet, ResNet, DenseNet and etc. Our results show that geometric transformations can lead to more performance gains than color transformations and the segmentation accuracy can be increased by 5% to 20% compared with no augmentation. Furthermore, a random linear combination of geometric and color transformations augmentation dataset gives the superior segmentation performance than all other datasets and results in a better accuracy of 94.98% with InceptionV3 models.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.15 no.5
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• pp.93-103
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• 2005

In this paper, we propose a RST resistant robust logo embedding technique for multimedia copyright protection Geometric manipulations are challenging attacks in that they do not introduce the quality degradation very much but make the detection process very complex and difficult. Watermark embedding in the normalized image directly suffers from smoothing effect due to the interpolation during the image normalization. This can be avoided by estimating the transform parameters using an image normalization technique, instead of embedding in the normalized image. Conventional RST resistant schemes that use full frame transform suffer from the absence of effective perceptual masking methods. Thus, we adopt $8\times8$ block DCT and calculate masking using a spatio-frequency localization of the $8\times8$ block DCT coefficients. Simulation results show that the proposed algorithm is robust against various signal processing techniques, compression and geometrical manipulations.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.213-216
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• 2001

본 논문은 DCT, FFT 및 Wavelet 등과 같은 주파수 영역에 의한 Watermarking 기법에서 정확한 Watermark를 검출하기 위하여 제안한 알고리즘이다. 본 논문에서 사용한 알고리즘은 기존의 왜곡된 영상에서 원 영상의 주파수 변환 값을 제거하여 왜곡된 상태의 영상 값에서 삽입된 Watermark를 검출하는 알고리즘에서 벗어나 왜곡된 값을 완전히 제거한 상태에서 영상의 Watermark를 검출함으로써 보다 완벽한 Watermark를 검출 할 수 있는 향상된 알고리즘을 제안하였다.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06c
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• pp.433-438
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• 1998

본 연구에서는 time averaging과 depth profiling기술을 음향현미경에 적용하여 5MHz 대역의 초음파 영상처리 시스템을 구성하였으며 기존의 피크값 검출기술과 상호 비교, 분석하였다. time averaging기술에서는 한 지점에서 반사된 tone burst파 전체를 디지털 오실로스코프를 통해 시간영역에서 A/D변환하고 변환된 512개 데이터들의 평균값을 취함으로써 영상을 얻을 수 있었으며, 이 기술은 시간영역에서 smoothing효과를 이용하여 산란이 심한 영역에 대한 영상을 개선시킬 수 있었다. depth profiling기술은 기준신호에 대한 반사신호의 시간 지연값을 최소 분해능 2ns로 검출함으로써 샘플의 3차원적인 실제 기하학적인 모양을 상대적인 크기로 얻을 수 있었다.

• Journal of Korea Multimedia Society
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• v.15 no.9
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• pp.1102-1111
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• 2012

In this paper, we propose a robust watermarking method against geometric attack even though the watermarked image is partially damaged. This method consists of standard image normalization which transforms any image into a predefined standard image and embedding watermark in DCT domain of standard normalized image using spread spectrum technique. The proposed standard image normalization method has an improvement over existing image normalization method, so it is robust to partial damage and geometric attack. The watermark embedding method using spread spectrum technique also has a robustness to image losses such as blurring, sharpening and compressions. In addition, the proposed watermarking method does not need an original image to detect watermark, so it is useful to public watermarking applications. Several experimental results show that the proposed watermarking method is robust to partial damage and various attacks including geometric deformation.

• Journal of KIISE:Information Networking
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• v.31 no.3
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• pp.243-251
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• 2004

This paper proposes a digital image watermarking scheme, which is robust to geometrical attacks. The method improves image normalization-based watermarking (INW) technique that doesn't effectively deal with geometrical attacks with cropping. Image normalization is based on the moments of the image, however, in general, geometrical attacks bring the image boundary cropping and the moments are not preserved original ones. Thereafter the normalized images of before and after are not same form, i.e., the synchronization is lost. To solve the cropping problem of INW, Invariant Centroid (IC) is proposed in this paper. IC is a gravity center of a central area on a gray scale image that is invariant although an image is geometrically attacked and the only central area, which has less cropping possibility by geometrical attacks, is used for normalization. Experimental results show that the IC-based method is especially robust to geometrical attack with cropping.