• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.11a
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• pp.139-142
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• 2011

본 논문에서는 이산 웨이블릿 변환(Discrete Wavelet Transform : DWT)을 이용한 새로운 초고해상도 기법을 제안한다. 제안된 기법에서는 DWT 수행 시 수반되는 다운 샘플링 과정을 수행하지 않음으로써 입력 받은 영상과 동일한 크기의 고주파 부대역(sub-band)들을 생성하고, 이 부대역들과 입력 받은 영상을 조합하여 이산 웨이블릿 역변환(Inverse Discrete Wavelet Transform : Inverse DWT)을 수행함으로써 고해상도의 영상을 획득한다. 실험을 통하여 제안된 기법이 이중 선형 보간법(bilinear interpolation)에 비해 향상된 효율을 보이며, 확률 기반의 기법들에 비해 처리시간도 줄어드는 것을 확인하였다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.11a
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• pp.347-350
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• 2020

본 논문에서는 영상 변환 기술인 이산웨이블릿변환(Discrete Wavelet Transform, DWT)를 딥러닝 기반의 네트워크로 구현한다. 딥러닝 기술 중에도 CNN 기반으로 네트워크를 설계하였으며, 본 DWT 네트워크는 해상도에 의존적이지 않은 계층들로만 구성된다. 데이터세트를 구성할 때 파이썬의 라이브러리를 사용하여 레이블 데이터세트를 구성한다. 128×128크기의 gray-scale 영상을 입력으로 사용하고 이에 대응하는 레이블 데이터세트를 구성하여 1-level DWT를 수행하는 네트워크의 학습을 진행한다. 역방향 변환도 네트워크 설계 후 데이터세트를 구성하여 학습을 진행한다. 학습이 완료된 1-level DWT 네트워크를 반복적으로 사용하여 Multi-level DWT 네트워크를 구성한다. 또한 양자화에 의한 간단한 영상압축 실험을 진행하여 DWT 네트워크의 성능과 압축 등의 응용분야에 활용할 수 있음을 보인다. 설계한 DWT 네트워크의 1-level 순방향 변환 성능은 42.18dB의 PSNR을 보였고, 1-level 역방향 변환 성능은 50.13dB의 PSNR을 보였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.3
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• pp.603-611
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• 2013

In this paper, we propose a new method which estimates and encrypts significant component of digital image such as digital cinema using discrete wavelet packet transform (DWPT). After analyzing the characteristics of images in spatial and frequency domain, the required information for ciphering an image was extracted. Based on this information an ciphering method was proposed with wavelet transform and packetization of subbands. The proposed algorithm can encrypt images in various robust from selecting transform-level and energy threshold. From analyzing the encryption effect numerically and visually, the optimized parameter for encryption is presented. Without additional analyzing process, one can encrypt efficiently digital image using the proposed parameter. Although only 0.18% among total data is encrypted, the reconstructed image dose not identified. The paketization information of subbands and the cipher key can be used for the entire secret key.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.793-795
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• 2004

본 논문에서는 웨이블릿 변환과 Direct LDA(DLDA)을 사용한 홍채 특징추출 방법을 제안한다. 이것은 획득한 홍채 영상으로부터 독특한 특징을 추출하기 위해 특별히 이차원 이산 웨이블릿 변환의 다중해상도 분해 방법을 사용하는 것이다 또한 홍채의 다양한 웨이블릿 성분으로부터 변별력을 가진 특징을 얻을 수 있도록 DLDA 기법을 적용하였다. 이러한 특징추출 방법은 이동이나 회전에 변하지 않는 알고리즘을 요구하는 홍채의 모양을 묘사하는데 적합하다. 홍채의 패턴정합을 위해서는 최근접 평균 분류기(Nearest Mean Classifier)를 사용하였다. 본 논문에서 인간의 홍채인식을 위해 제시한 방법이 홍채패턴을 표현하는 효과적인 방법이며, 시간 및 공간의 절약이라는 측면에서 유리하다는 것을 보여준다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.5
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• pp.65-76
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• 2001

In this paper, performance of frequency-based watermarking methods is compared, which are used to protect copyright of image data. For performance comparison of each transform method, a test image is transformed into frequency domain by a full- and block-discrete cosine transforms and wavelet transform, and after general image processing, robustness of each transform is evaluated with using the same watermark signals. Simulation results show that the watermarking method based on DCTs are more robust than WT. Especially, $8{\times}8$ BDCT is most robust for JPEG lossy compression and sharpening, while $8{\times}8$ FDCT is best. for smoothing and scaling. In addition, watermarking based on BDCT shows decreasing robustness for a larger block size, compared with general image processing.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.265-268
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• 2000

본 논문에서는 영상데이터의 효율적인 압축과 전송을 위하여 이산 웨이블릿 변환(Discret Wavelet Trans-form)과 MPEG 부호화 방법을 이용한 영상 부호화 방법을 제안하였다. 이 방법은 다해상도를 제공하는 계층적 피라미드 구조를 이용한다. DWT로 영상을 여러 개의 밴드들로 분해한 다음, 각 밴드에서 MPEG 부호화기에서 사용하는 방법을 그대로 이용하여, 광범위하게 쓰이는 MPEG 하드웨어나 소프트웨어를 재 사용한다는 이점을 가진다. 기존의 DWT-MPEG 방법[1]은 MPEG 부호화 방법을 쓰기 전에 웨이블릿 필터 분해를 여러번을 하여, 움직임 추정을 정확하게 하지 못하였으나, 제안한 방법은 웨이블릿 필터 분해를 한 번만 하고, MPEG 부호화를 할 때, 웨이블릿 분해를 한번 더 사용하여, 움직임 추정과 보상을 좀 더 개선되게 하였다. 실험 결과, 기존의 DWT-MPEG 방법보다 제안한 방법이 화질이나 압축면에서 좀 더 향상된 결과를 얻을 수가 있었다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.5
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• pp.1245-1252
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• 2013

As the usage of digital image contents increase, a security problem for the payed image data or the ones requiring confidentiality is raised. This paper propose a depth-map image contents encryption methodology to hide the depth information. This method is performed on the frequency coefficients in the Wavelet domain. This method, by selecting the level and threshold value for the wavelet transform, encryption at various strengths are possible. The experimental results showed that encrypting only 0.048% of the entire data was enough to hide the constants of the depth-map. The encryption algorithm expected to be used effectively on the researches on encryption and others for image processing.

• Journal of Internet Computing and Services
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• v.22 no.3
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• pp.45-52
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• 2021

Although many studies have been conducted to identify unknown attacks in cyber security intrusion detection systems, studies based on outliers are attracting attention. Accordingly, we identify outliers by defining categories for unknown attacks. The unknown attacks were investigated in two categories: first, there are factors that generate variant attacks, and second, studies that classify them into new types. We have conducted outlier studies that can identify similar data, such as variants, in the category of studies that generate variant attacks. The big problem of identifying anomalies in the intrusion detection system is that normal and aggressive behavior share the same space. For this, we applied a technique that can be divided into clear types for normal and attack by discrete wavelet transformation and detected anomalies. As a result, we confirmed that the outliers can be identified through One-Class SVM in the data reconstructed by discrete wavelet transform.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.4
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• pp.521-526
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• 2015

Research on how to use the biological characteristics of human to confirm the identity of the individual is being actively conducted. Electrocardiogram(: ECG) based biometric system is difficult to counterfeit and does not cause skin irritation on the subject. It can be easily combined with conventional biometrics such as fingerprint and face recognition to give multimodal biometric systems. In this thesis, biometric identification method analysing ECG waveform characteristics from Discrete Wavelet Transform(DWT) coefficients is suggested. Feature selection is performed on the 9 coefficients of DWT using the correlation analysis. The verification is achieved by using the error back propagation neural networks. Using the proposed approach on 24 subjects of MIT-BIH QT Database, 98.88% verification rate has been obtained.

• Journal of Advanced Navigation Technology
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• v.10 no.3
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• pp.219-225
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• 2006

This paper presents a method of object classification based on discrete wavelet transform (DWT) and fuzzy inference(FI). It concentrated not only on the design of fuzzy inference algorithm which is suitable for low speed uninhabited transportation such as, conveyor but also on the minimize the number of fuzzy rule. In the preprocess of feature extracting, feature parameters are extracted by using characteristics of the coefficients matrix of DWT. Such feature parameters as area, perimeter and a/p ratio are used obtained from DWT coefficients blocks. Secondly, fuzzy if - then rules that can be able to adapt the variety of surroundings are developed. In order to verify the performance of proposed scheme, In the middle of fuzzy inference, the Mamdani's and the Larsen 's implication operators are utilized. Experimental results showed that proposed scheme can be applied to the variety of surroundings.