• Title/Summary/Keyword: 마스크 감지

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Identification System Based on Partial Face Feature Extraction (부분 얼굴 특징 추출에 기반한 신원 확인 시스템)

  • Choi, Sun-Hyung;Cho, Seong-Won;Chung, Sun-Tae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.22 no.2
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    • pp.168-173
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    • 2012
  • This paper presents a new human identification algorithm using partial features of the uncovered portion of face when a person wears a mask. After the face area is detected, the feature is extracted from the eye area above the mask. The identification process is performed by comparing the acquired one with the registered features. For extracting features SIFT(scale invariant feature transform) algorithm is used. The extracted features are independent of brightness and size- and rotation-invariant for the image. The experiment results show the effectiveness of the suggested algorithm.

Face-Mask Detection with Micro processor (마이크로프로세서 기반의 얼굴 마스크 감지)

  • Lim, Hyunkeun;Ryoo, Sooyoung;Jung, Hoekyung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.3
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    • pp.490-493
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    • 2021
  • This paper proposes an embedded system that detects mask and face recognition based on a microprocessor instead of Nvidia Jetson Board what is popular development kit. We use a class of efficient models called Mobilenets for mobile and embedded vision applications. MobileNets are based on a streamlined architechture that uses depthwise separable convolutions to build light weight deep neural networks. The device used a Maix development board with CNN hardware acceleration function, and the training model used MobileNet_V2 based SSD(Single Shot Multibox Detector) optimized for mobile devices. To make training model, 7553 face data from Kaggle are used. As a result of test dataset, the AUC (Area Under The Curve) value is as high as 0.98.

Design and Implementation of Entry-level COVID-19 Digital Signage Player supporting Fever Detection, Face Mask Wearing Detection and KI-pass QR Code Checking (발열 감지, 안면 마스크 착용 검출, 전자출입명부 QR 코드 체킹을 지원하는 보급형 COVID-19 디지털 사이니지 플레이어 설계 및 구현)

  • Huy-Tran, Quoc Bao;Park, SangGun;Chung, SunTae
    • Journal of Korea Multimedia Society
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    • v.25 no.1
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    • pp.10-28
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    • 2022
  • In this paper, we present an entry-level COVID-19 stand-alone digitial signage player (CoSiP) which performs not only conventional digital signage functionalities but also fever detection, face mask wearing detection, and KI-pass QR code checking. The overall design of CoSiP is proposed, and implementation of a temperature checking algorithm using a low cost thermal sensor is elaborately presented. Through experiments over datasets and against a developed CoSiP device, it is shown that the fever detection, face mask wearing detection, KI-pass QR code checking as well as signage functionalities of the proposed CoSiP work properly and reliably.

Research on Human Posture Recognition System Based on The Object Detection Dataset (객체 감지 데이터 셋 기반 인체 자세 인식시스템 연구)

  • Liu, Yan;Li, Lai-Cun;Lu, Jing-Xuan;Xu, Meng;Jeong, Yang-Kwon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.17 no.1
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    • pp.111-118
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    • 2022
  • In computer vision research, the two-dimensional human pose is a very extensive research direction, especially in pose tracking and behavior recognition, which has very important research significance. The acquisition of human pose targets, which is essentially the study of how to accurately identify human targets from pictures, is of great research significance and has been a hot research topic of great interest in recent years. Human pose recognition is used in artificial intelligence on the one hand and in daily life on the other. The excellent effect of pose recognition is mainly determined by the success rate and the accuracy of the recognition process, so it reflects the importance of human pose recognition in terms of recognition rate. In this human body gesture recognition, the human body is divided into 17 key points for labeling. Not only that but also the key points are segmented to ensure the accuracy of the labeling information. In the recognition design, use the comprehensive data set MS COCO for deep learning to design a neural network model to train a large number of samples, from simple step-by-step to efficient training, so that a good accuracy rate can be obtained.

The Performance Improvement of Cognitive Radio Technology Based on UWB System (UWB 기반의 인지적 무선통신 기술의 성능 개선)

  • Seo, Yu-Jung;Ha, Deock-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2008.05a
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    • pp.921-924
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    • 2008
  • Recently, ultra-wideband(UWB) technology based on the transmission of short duration pulses has gained much interest for its application to wireless communications. Various wireless communication and wireless broadcast will require more efficient use of frequency. Cognitive radio technology is an intelligent technology which can sense the spectrum environment and adaptively adjust the parameters for wireless transmission. In this paper, by using Cognitive UWB, the spectrum efficiency of the transmission channels is largely improved, and the interference between the other systems can be effectively avoided.

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Study on Factors for Passenger Risk in Railway Vehicle (철도차량내 승객 위험요소 선정 연구)

  • Park, Won-Hee;Park, Sung-Joon;Kim, Hyo-Jin;Kim, HanSaem;Oh, Sechan
    • Journal of the Society of Disaster Information
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    • v.17 no.4
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    • pp.733-746
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    • 2021
  • Purpose: This study was conducted for the purpose of selecting important events from among various events that may pose a risk to railway passengers. For this purpose, opinions of various railroad vehicle passengers and railway operator workers were investigated and analyzed. Method: The survey was conducted on 1,000 men and women in their 20s and 60s and 429 workers at 11 company across the country. A survey was conducted on the dangerous situations that may occur in subways, general railroads and high-speed rail vehicles targeting passengers. For railway operator workers, the questionnaire is limited to subway vehicles. Result: Among the passenger risk factors(abnormal behavior and dangerous situations) selected based on the frequency and importance of occurrence of passenger risk factors, the main risk factors are selected 'car door jamming', 'sexual harassment', 'intoxicating behavior', 'fighting' /assault', 'wandering around', and 'not wearing a mask'. Conclusion: The major risk factors affecting passengers were selected by surveying passengers and railway operators. we plan to develop a CCTV detection system with AI technology that can quickly and continuously detect the major risk factors of railway vehicles selected as a result of this study.

A Dual Micro Gas Sensor Array with Nano Sized $SnO_2$ Thin Film (나노 박막을 이용한 듀얼 $SnO_2$ 마이크로 가스센서 어레이)

  • Chung Wan-Young
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.9
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    • pp.1641-1647
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    • 2006
  • A dual micro gas sensor way for detecting reducing gas and bad order was fabricated using nano sized $SnO_2$ thin film fabrication method. To make nano-sized thin gas sensitive $SnO_2$ thin rilm, thin tin metal layer $2500{\AA}$ thick was oxidized between 600 and $800^{\circ}C$ by thermal oxidation. The gas sensing layers such as $SnO_2,\;SnO_2(+Pt)\;and\;SnO_2(+CuO)$ were patterned by metal shadow mask for simple fabrication process on the silicon substrate. The micro gas sensors with $SnO_2(Pt)$ and $SnO_2(+CuO)$ showed good selectivity to CO gas among reducing gases and good sensitivity to $H_2S$ that is main component of bad odor, separately.

A Study on the Design of Content Addressable and Reentrant Memory(CARM) (Content Addressable and Reentrant Memory (CARM)의 설계에 관한 연구)

  • 이준수;백인천;박상봉;박노경;차균현
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.16 no.1
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    • pp.46-56
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    • 1991
  • In this paper, 16word X 8bit Content Addressable and Reentrant Memory(CARM) is described. This device has 4 operation modes(read, write, match, reentrant). The read and write operation of CARM is like that of static RAM, CARM has the reentrant mode operation where the on chip garbage collection is accomplished conditionally. Thus function can be used for high speed matching unit of dynamic data flow computer. And CARM also can encode matching address sequentially according to therir priority. CARM consists of 8 blocks(CAM cell, Sequential Address Encoder(S.A.E). Reentrant operation. Read/Write control circuit, Data/Mask Register, Sense Amplifier, Encoder. Decoder). Designed DARM can be used in data flow computer, pattern, inspection, table look-up, image processing. The simulation is performed using the QUICKSIM logic simulator and Pspice circuit simulator. Having hierarchical structure, the layout was done using the 3{\;}\mu\textrm{m} n well CMOS technology of the ETRI design rule.

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Algorithm for Detecting PSD Boundary Invasion in Subway PSD using Image Processing (영상처리를 이용한 지하철 스크린 도어의 경계선 침범인식 알고리듬 연구)

  • Baek, Woon-Seok;Lee, Ha-Woon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.13 no.5
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    • pp.1051-1058
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    • 2018
  • This paper propose image processing algorithm to prevent safety accidents near by subway platform screen door(PSD). First, edges of the subway PSD images are detected and the boundary line between PSD and subway platform is detected to decide people's approach to the PSD using Hough transform. To do this, we draw the boundary line between the PSD and platform, to detect the boundary line and to decide the people's approach to the detected line is completely connected or not. Generally, edge is the basic characteristic of image; thus, edge detection is very important in image processing applications and computer vision area. The conventional edge detection methods such as Roberts, Sobel, Prewitt, and Laplacian etc, which are using a fixed value of mask, and morphological gradient from the structuring element of view and Canny edge detector are widely used. In this paper, we propose the detection algorithm about the people's approach to the subway PSD to prevent the safety accidents by using Canny edge detector and Hough transform and the computer simulation shows the results.

Prediction of Semiconductor Exposure Process Measurement Results using XGBoost (XGBoost를 사용한 반도체 노광 공정 계측 결과 예측)

  • Shin, Jeong Il;Park, Ji Su;Shon, Jin Gon
    • Proceedings of the Korea Information Processing Society Conference
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    • 2021.05a
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    • pp.505-508
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    • 2021
  • 반도체 회로의 미세화로 단위 공정이 증가하면 TAT(turn-around time) 증가에 따른 제조 비용이 늘어난다. 반도체 공정 중 포토 공정은 마스크의 회로를 웨이퍼에 전사하는 공정으로 전사를 담당하는 노광장비의 성능에 의해 회로의 정확성이 결정된다. 이런 정확성을 검증하는 계측공정은 회로의 미세화가 진행될수록 필요성은 증가하나 TAT 증가의 주된 요인으로 최근 기계학습을 사용한 다양한 예측 모형들의 개발로 계측 결과를 예측하는 실험들이 진행되고 있다. 본 논문은 노광장비 센서들의 이상값을 감지하여 분류 후 계측공정을 진행하는 LFDC(Lithography Fault Detection and Classification) 시스템의 문제인 분류 성능이 떨어지는 것을 해결하기 위해 XGBoost를 사용하여 계측공정을 진행하지 않고 노광장비 센서의 이상값을 학습된 학습기를 통해 분류하여 포토 공정을 재진행하거나 다음 공정을 진행하는 방법을 실험하였다. 실험에서 사용된 계측 결과 예측 모형은 89%의 정확도를 확보하였고 반도체 데이터 특성인 심각한 불균형의 데이터에 대해서도 같은 정확도를 얻었다. 이런 결과는 노광장비 센서들의 이상값에 대해 89%는 정상으로 판단하였고 정상으로 판단한 웨이퍼를 실제 계측 시 예측과 같은 결과를 얻었다. 계측 결과 예측 모형을 사용하면 실제 계측을 진행하지 않고 노광장비 센서들의 이상값에 대한 판정을 할 수 있어 TAT 단축으로 제조 비용감소, 계측 장비 부하 감소 및 효율 향상을 할 수 있다. 하지만 본 논문에서는 90%의 성능을 보이는 계측 결과 예측 모형으로 여전히 10%에 대해서는 실제 계측이 필요한 문제에 대해 추후 더 연구가 필요하다.