• 한국멀티미디어학회논문지
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• 제21권2호
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• pp.108-116
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• 2018

In this paper, we propose an image enhancement method based on Multi-Scale Retinex theory that designs Unsharp Masking Filter (UMF) and emphasizes the contrast ratio adaptively. Unsharp Masking (UM) technique emphasizes image sharpness and improves contrast ratio by adding high frequency component to the original image. The high frequency component is obtained by differentiating between original image and low frequency image. In this paper, we present how to design an UMF kernel and to adaptively apply it to increase the contrast ratio according to multi-scale retinex theory which resembles human visual system. Experimental results show that the proposed method has better quantitative performance indexes such as PSNR, ambe & SSIM and better qualitative feature like halo artifact suppression.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2001년도 추계학술대회 논문집
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• pp.186-189
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• 2001

The main method in micro-etching process, used in manufacturing semiconductors, electronic components, circuits, is Photo Masking method that exposes and develops on the photo-sensitivity solutions or films. This method enables one to process highly precisely, $\pm$0.03 mm in end line location area. But this has limits in a high speed / wide width process, difficulties in endless masking, and the problem of high price. We have developed the direct masking method to make use of Gravure printing, widely used in grocery packing sheet printing. We made cylinder tools to influence the masking quality by laser stream process. We have confirmed that the end line location accuracy in the line width of the product is improved from 0.12 mm to $\pm$0.07 mm level, after etching process.

• The Journal of the Acoustical Society of Korea
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• 제18권3E호
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• pp.3-8
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• 1999

In speech recognition for real-world applications, the performance degradation due to the mismatch introduced between training and testing environments should be overcome. In this paper, to reduce this mismatch, we provide a hybrid method of spectral subtraction and residual noise masking. We also employ multiple model approach to obtain improved robustness over various noise environments. In this approach, multiple model sets are made according to several noise masking levels and then a model set appropriate for the estimated noise level is selected automatically in recognition phase. According to speaker independent isolated word recognition experiments in car noise environments, the proposed method using model sets with only two masking levels reduced average word error rate by 60% in comparison with spectral subtraction method.

• ETRI Journal
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• 제33권2호
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• pp.267-274
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• 2011

This paper proposes an efficient masking method for the block cipher SEED that is standardized in Korea. The nonlinear parts of SEED consist of two S-boxes and modular additions. However, the masked version of these nonlinear parts requires excessive RAM usage and a large number of operations. Protecting SEED by the general masking method requires 512 bytes of RAM corresponding to masked S-boxes and a large number of operations corresponding to the masked addition. This paper proposes a new-style masked S-box which can reduce the amount of operations of the masking addition process as well as the RAM usage. The proposed masked SEED, equipped with the new-style masked S-box, reduces the RAM requirements to 288 bytes, and it also reduces the processing time by 38% compared with the masked SEED using the general masked S-box. The proposed method also applies to other block ciphers with the same nonlinear operations.

• Journal of Information Processing Systems
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• 제19권6호
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• pp.767-777
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• 2023

In modern society, user privacy is emerging as an important issue as closed-circuit television (CCTV) systems increase rapidly in various public and private spaces. If CCTV cameras monitor sensitive areas or personal spaces, they can infringe on personal privacy. Someone's behavior patterns, sensitive information, residence, etc. can be exposed, and if the image data collected from CCTV is not properly protected, there can be a risk of data leakage by hackers or illegal accessors. This paper presents an innovative approach to "machine learning based reversible chaotic masking method for user privacy protection in CCTV environment." The proposed method was developed to protect an individual's identity within CCTV images while maintaining the usefulness of the data for surveillance and analysis purposes. This method utilizes a two-step process for user privacy. First, machine learning models are trained to accurately detect and locate human subjects within the CCTV frame. This model is designed to identify individuals accurately and robustly by leveraging state-of-the-art object detection techniques. When an individual is detected, reversible chaos masking technology is applied. This masking technique uses chaos maps to create complex patterns to hide individual facial features and identifiable characteristics. Above all, the generated mask can be reversibly applied and removed, allowing authorized users to access the original unmasking image.

• 정보보호학회논문지
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• 제26권6호
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• pp.1431-1441
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• 2016

ARX 구조를 가지는 블록암호알고리즘에 마스킹 대응기법을 적용할 경우 연산별 마스킹 방식의 차이로 인하여 방식 간 안전한 변환이 반드시 필요하다. 그러나 마스킹 변환 시 발생되는 많은 연산량으로 인하여 ARX 기반 알고리즘에 마스킹 대응기법을 적용하는 것은 AES와 같이 하나의 마스킹 방식을 적용하는 알고리즘보다 상대적으로 비효율적이라고 알려져 있다. 본 논문에서는 현재까지 제안된 다양한 마스킹 변환 기법을 이용하여 1차 부채널분석에 안전한 LEA를 설계하고 32비트 플랫폼에 구현한다. 이를 바탕으로 대응기법의 예상되는 이론적 연산량과 실제 측정한 연산량간 발생하는 차이점에 대해 구현관점에서 살펴본다. 아울러 T-test를 활용하여 본 논문에서 구현한 대응기법이 실제 안전한지를 실험적으로 검증한다.

• 정보보호학회논문지
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• 제29권4호
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• pp.709-718
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• 2019

CHAM은 자원이 제한된 환경에 적합하도록 설계된 경량 블록 암호 알고리즘으로서 안전성과 연산 성능면에서 우수한 특성을 보인다. 그러나 이 알고리즘도 부채널 공격에 대한 취약성을 그대로 내재하고 있기 때문에 마스킹 기법과 같은 대응 기법이 적용되어야 한다. 본 논문에서는 32비트 마이크로프로세서 Cortex-M3 플랫폼에서 부채널 공격에 대응하는 마스킹 기법이 적용된 CHAM 알고리즘을 구현하고 성능을 비교 분석한다. 또한, CHAM 알고리즘이 라운드 수가 많아 연산 효율이 감소되는 점을 고려하여 축소 마스킹 기법을 적용하여 성능을 평가하였다. 축소 라운드 마스킹이 적용된 CHAM-128/128은 구현 결과 마스킹이 없는 경우에 비해 약 4배 정도의 추가 연산이 필요함을 확인하였다.

• 정보보호학회논문지
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• 제19권4호
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• pp.21-28
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• 2009

전력분석 공격이 소개되면서 다양한 대응법들이 제안되었고 그러한 대응법들 중 블록 암호의 경우, 암/복호화 연산, 키 스케줄 연산 도중 중간 값이 전력 측정에 의해 드러나지 않도록 하는 마스킹 기법이 잘 알려져 있다. 블록 암호의 마스킹 기법은 비선형 연산에 대한 비용이 가장 크며, 따라서 AES의 경우 가장 많은 비용이 드는 연산은 S-box의 역원 연산이다. 이로 인해 마스킹 역원 연산에 대한 비용을 단축시키기 위해 다양한 대응법들이 제안되었고, 그 중 Zakeri의 방법은 복합체 위에서 정규 기저를 사용한 가장 효율적인 방법으로 알려져 있다. 본 논문에서는 복합체 위에서의 마스킹 역원 연산 방식을 변형, 중복되는 곱셈을 발견함으로써 기존 Zakeri의 방법보다 총 게이트 수가 10.5% 절감될 수 있는 마스킹 역원 방법을 제안한다.

• Journal of Information Processing Systems
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• 제19권3호
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• pp.323-333
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• 2023

Facial expression recognition can aid in the development of fatigue driving detection, teaching quality evaluation, and other fields. In this study, a facial expression recognition method was proposed with a residual masking reconstruction network as its backbone to achieve more efficient expression recognition and classification. The residual layer was used to acquire and capture the information features of the input image, and the masking layer was used for the weight coefficients corresponding to different information features to achieve accurate and effective image analysis for images of different sizes. To further improve the performance of expression analysis, the loss function of the model is optimized from two aspects, feature dimension and data dimension, to enhance the accurate mapping relationship between facial features and emotional labels. The simulation results show that the ROC of the proposed method was maintained above 0.9995, which can accurately distinguish different expressions. The precision was 75.98%, indicating excellent performance of the facial expression recognition model.

• Journal of Multimedia Information System
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• 제4권2호
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• pp.65-73
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• 2017

This paper proposes a method to improve the image quality by designing Unsharp Mask Filter (UMF) based on Retinex theory which controls the frequency pass characteristics adaptively. Conventional unsharp masking technique uses blurring image to emphasize sharpness of image. Unsharp Masking(UM) adjusts the original image and sigma to obtain a high frequency component to be emphasized by the difference between the blurred image and the high frequency component to the original image, thereby improving the contrast ratio of the image. In this paper, we design a Unsharp Mask Filter(UMF) that can process the contrast ratio improvement method of Unsharp Masking(UM) technique with one filtering. We adaptively process the contrast ratio improvement using Unsharp Mask Filter(UMF). We propose a method based on Retinex theory for adaptive processing. For adaptive filtering, we control the weights of Unsharp Mask Filter(UMF) based on the human visual system and output more effective results.