• Title/Summary/Keyword: 마스크 기법

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Mask detection in complex scenes using an ensemble of YOLO models (YOLO 모델 앙상블을 이용한 복잡한 장면에서의 Mask Detection 기법)

  • Hu, Xufeng;Lim, Hyunseok;Gwak, Jeonghwan
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2022.01a
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    • pp.97-98
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    • 2022
  • 코로나바이러스-19 팬데믹 이후 매일 수만 명의 환자가 발생하고 있다. 보건당국은 사람들의 생활 안전을 보호하기 위해 공항, 정류장 등 공공장소에서는 반드시 마스크를 착용하라고 지시하고 있다. 마스크를 착용하는 목적은 감염으로부터 신체를 보호하고 바이러스 전파와 확산을 막기 위한 것이다. 공공장소에서는 많은 인원에 대한 일괄적인 마스크 착용 검사를 하기 어렵고, 육안으로 확인하는 마스크 착용 검사 방법은 인파가 몰리는 장소에서 검사 효율이 떨어지며 누락되는 경우도 많이 발생한다. 본 연구에서는 입력 이미지에 존재하는 얼굴 영역을 YOLOv4와 YOLOv5 모델을 통해 예측하여 마스크의 착용 여부를 판단하되, 앙상블 기법을 적용하여 보다 효과적인 BB(Bounding Box) 추출 및 마스크 착용 탐지 기법을 적용한다. 따라서 공공장소의 마스크 착용실태를 효과적으로 모니터링 할 수 있는 방법을 제안한다.

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Mask Estimation Based on Band-Independent Bayesian Classifler for Missing-Feature Reconstruction (Missing-Feature 복구를 위한 대역 독립 방식의 베이시안 분류기 기반 마스크 예측 기법)

  • Kim Wooil;Stern Richard M.;Ko Hanseok
    • The Journal of the Acoustical Society of Korea
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    • v.25 no.2
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    • pp.78-87
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    • 2006
  • In this paper. we propose an effective mask estimation scheme for missing-feature reconstruction in order to achieve robust speech recognition under unknown noise environments. In the previous work. colored noise is used for training the mask classifer, which is generated from the entire frequency Partitioned signals. However it gives a limited performance under the restricted number of training database. To reflect the spectral events of more various background noise and improve the performance simultaneously. a new Bayesian classifier for mask estimation is proposed, which works independent of other frequency bands. In the proposed method, we employ the colored noise which is obtained by combining colored noises generated from each frequency band in order to reflect more various noise environments and mitigate the 'sparse' database problem. Combined with the cluster-based missing-feature reconstruction. the performance of the proposed method is evaluated on a task of noisy speech recognition. The results show that the proposed method has improved performance compared to the Previous method under white noise. car noise and background music conditions.

Efficiency Assessment of Analysing Coastal Geomorphic Landscape Change by Satellite Image Interpretation (위성영상을 이용한 해안습지 지형경관 변화 분석의 효율성 평가)

  • 박의준;구자용
    • Journal of the Korean Geographical Society
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    • v.38 no.5
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    • pp.822-834
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    • 2003
  • It is difficult to analyse geomorphic landscape changes effectively by a field survey. A satellite image interpretation may play an important role to overcome such a problem. The purpose of this study is to assess the accuracy of different method to identify geomorphic landscape change by using satellite imagery. The study area is the Yongjong coastal wetland in which a huge man-made environmental change occured to build a new international airport in the past decade. These changes may be summarized that a coastal landscape has been changed to a terrestrial landscape, and also a natural landscape to a man-made landscape. In order to detect these changes, we applied three different satellite interpreting methods, including a binary change mask using band difference. a binary change mask using normalized band difference. and a binary change mask using NDVI. We concluded that a binary change mask using NDVI is the best method among three different methods analysing the coastal geomorphic-landscape changes.

Enhanced image detail control using Multi Channel Unsharp Mask Technique (멀티채널 언샤프 마스크 기법을 이용한 영상 세부제어)

  • Cho, Hyun-Ji;Nam, Doohee
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.15 no.1
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    • pp.165-170
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    • 2015
  • The unsharp mask technique emphasize the boundary of the image by adding the boundary of the original image. This technique improves quality by emphasize its boundaries but produce rough image from image noise. The multi channel unsharp mask is possible to enhance entire contrast of the image by applying at least two channels of unsharp mask. However, There is limitations to strengthen boundaries even if the scale strongly applies the multi channel unsharp mask technique. To solve this problem, linear scaling to nonlinear scaling by applying exponential function to existing multi channel unsharp mask technique. Experimental results show enhanced contrast for desired area because of control scaling in details compared with existing unsharp mask technique.

Robust Head Pose Estimation for Masked Face Image via Data Augmentation (데이터 증강을 통한 마스크 착용 얼굴 이미지에 강인한 얼굴 자세추정)

  • Kyeongtak, Han;Sungeun, Hong
    • Journal of Broadcast Engineering
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    • v.27 no.6
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    • pp.944-947
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    • 2022
  • Due to the coronavirus pandemic, the wearing of a mask has been increasing worldwide; thus, the importance of image analysis on masked face images has become essential. Although head pose estimation can be applied to various face-related applications including driver attention, face frontalization, and gaze detection, few studies have been conducted to address the performance degradation caused by masked faces. This study proposes a new data augmentation that synthesizes the masked face, depending on the face image size and poses, which shows robust performance on BIWI benchmark dataset regardless of mask-wearing. Since the proposed scheme is not limited to the specific model, it can be utilized in various head pose estimation models.

An X-masking Scheme for Logic Built-In Self-Test Using a Phase-Shifting Network (위상천이 네트워크를 사용한 X-마스크 기법)

  • Song, Dong-Sup;Kang, Sung-Ho
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.44 no.2
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    • pp.127-138
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    • 2007
  • In this paper, we propose a new X-masking scheme for utilizing logic built-in self-test The new scheme exploits the phase-shifting network which is based on the shift-and-add property of maximum length pseudorandom binary sequences(m-sequences). The phase-shifting network generates mask-patterns to multiple scan chains by appropriately shifting the m-sequence of an LFSR. The number of shifts required to generate each scan chain mask pattern can be dynamically reconfigured during a test session. An iterative simulation procedure to synthesize the phase-shifting network is proposed. Because the number of candidates for phase-shifting that can generate a scan chain mask pattern are very large, the proposed X-masking scheme reduce the hardware overhead efficiently. Experimental results demonstrate that the proposed X-masking technique requires less storage and hardware overhead with the conventional methods.

The Object Based Image Masking Algorithm (객체기반 초상권 보호 영상처리 알고리듬)

  • 윤호석;임재혁;전우성;원치선
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 1999.11b
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    • pp.93-98
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    • 1999
  • 본 논문에서는 영상 내 존재하는 의미 있는 객체단위로 초상권을 보호하는 기법을 제안한다. 제안된 방법은 초상권 보호 객체선택 단계와 객체에 마스크를 적용하는 단계 그리고 마스크가 적용된 객체를 추적하는 단계로 나누어진다. 초상권 보호 객체선택 단계에서는 블록분류(block classification) 및 워터쉐드(watershed) 알고리듬을 이용하여 분할된 결과영상을 얻고 이를 이용하여 사용자가 원하는 객체를 마우스로 클릭함으로써 손쉽게 초상권 보호법을 적용시킬 객체를 추출할 수 있다. 이렇게 정의된 객체는 다음 단계에서 마스크를 적용 받게 된다. 첫 번째 프레임에서 마스크가 적용되면 다음 프레임부터는 객체추적과정에서 연된 화면사이의 움직임 및 밝기정보에 의해 객체를 추적, 계속 마스크를 적용함으로써 초상권을 보호할 수 있다. 제안된 알고리듬은 초상권 보호를 위한 모자이크 처리 시 화질 저하에 따른 시청자의 화면 거부감을 최소화시키고, 반자동영상분할 알고리듬을 사용하여 객체 단위로 초상권 마스크를 적용하여 초상권 보호대상물을 놓치지 않고 추적할 수 있어 신뢰도를 높일 수 있는 장점을 가지고 있다.

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A Study on Face Masks Distribution System based on the Blockchain Decentralized Identity (블록체인 분산신원증명에 기반한 공적마스크 중복구매 확인 시스템에 대한 연구)

  • Noh, Siwan;Jang, Seolah;Rhee, Kyune-Hyune
    • Proceedings of the Korea Information Processing Society Conference
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    • 2020.05a
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    • pp.214-217
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    • 2020
  • 2020년 1월 국내에 신종 코로나 바이러스의 확산으로 인해 보건 마스크의 수요가 급증하고 이에 따라 마스크의 가격이 폭등하자 정부가 건강보험정보를 기반으로 보건용 마스크 판매에 관여하는 공적 마스크 5부제를 시행해 왔다. 하지만 건강보험 가입정보에 의존적인 신원 인증 시스템으로 인해 유학생 등 건강보험 미가입자의 경우 마스크의 구입이 어렵고 개인정보 접근 문제 등으로 판매채널의 확장이 어려운 문제가 있었다. 본 논문에서는 건강보험과 같은 특정 신원정보 시스템에 의존하지 않고 중앙기관이 발행하는 신뢰할 수 있는 모든 신원정보(여권, 외국인등록증 등)에 기반하여 사용자가 스스로 자신의 신원정보 속성을 블록체인을 통해 관리하는 방법을 제안한다. 또한 제안 방법에 대해 디지털신원 기법을 평가할 수 있는 지표를 기반으로 자체 평가를 수행한다.

Eigenvoice Adaptation of Classification Model for Binary Mask Estimation (Eigenvoice를 이용한 이진 마스크 분류 모델 적응 방법)

  • Kim, Gibak
    • Journal of Broadcast Engineering
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    • v.20 no.1
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    • pp.164-170
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    • 2015
  • This paper deals with the adaptation of classification model in the binary mask approach to suppress noise in the noisy environment. The binary mask estimation approach is known to improve speech intelligibility of noisy speech. However, the same type of noisy data for the test data should be included in the training data for building the classification model of binary mask estimation. The eigenvoice adaptation is applied to the noise-independent classification model and the adapted model is used as noise-dependent model. The results are reported in Hit rates and False alarm rates. The experimental results confirmed that the accuracy of classification is improved as the number of adaptation sentences increases.

Gate-Level Conversion Methods between Boolean and Arithmetic Masks (불 마스크와 산술 마스크에 대한 게이트 레벨 변환기법)

  • Baek, Yoo-Jin
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.46 no.11
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    • pp.8-15
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    • 2009
  • Side-channel attacks including the differential power analysis attack are often more powerful than classical cryptanalysis and have to be seriously considered by cryptographic algorithm's implementers. Various countermeasures have been proposed against such attacks. In this paper, we deal with the masking method, which is known to be a very effective countermeasure against the differential power analysis attack and propose new gate-level conversion methods between Boolean and arithmetic masks. The new methods require only 6n-5 XOR and 2n-2 AND gates with 3n-2 gate delay for converting n-bit masks. The basic idea of the proposed methods is that the carry and the sum bits in the ripple adder are manipulated in a way that the adversary cannot detect the relation between these bits and the original raw data. Since the proposed methods use only bitwise operations, they are especially useful for DPA-securely implementing cryptographic algorithms in hardware which use both Boolean and arithmetic operations. For example, we applied them to securely implement the block encryption algorithm SEED in hardware and present its detailed implementation result.