• Journal of Korea Multimedia Society
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• v.11 no.1
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• pp.34-43
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• 2008

This paper presents a system for recognizing sunglasses and a mask of an ATM (Automatic Teller Machine) user. The proposed system extracts firstly facial contour, then from this extraction results it estimates the regions of eyes and mouth. Finally, it recognizes sunglasses and a mouth using Histogram Indexing based on those regions. We adopt a face shape model to be able to extract facial contour and to estimate the regions of eyes and mouth when those regions are occluded by sunglasses and a mask. To improve the fitting accuracy of the shame model, we adopt 2-step face detection method and conduct fitting several times by varying the initial position of the model instance. To achieve a good performance of the face detection method based on a background model, we enable the system to automatically update the background model. In experiment, we present some experiments on setting parameters of the system with images taken from in our laboratory, and demonstrate the results of recognizing sunglasses and a mask.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.17-19
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• 2021

본 논문에서는 코로나19 사태에 대비하여 실시간으로 마스크를 제대로 쓴 사람과 제대로 쓰지 않은 사람을 구분하는 시스템을 제안한다. 이 시스템을 사용하기 위하여 모델 학습 시에 합성곱 신경망(CNN : Convolutional Neural Networks)를 사용한다. 학습된 모델을 토대로 영상에 적용 시 하르 특징 분류기(Haar Cascade Classifier)로 얼굴을 탐지하여 마스크 여부를 판단한다.

• Archives of Plastic Surgery
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• v.36 no.4
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• pp.469-474
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• 2009

Purpose: A lower facial contouring surgery has become a commonly performed procedure in Asia. Currently, mandibular angle sagittal ostectomy and botulinum toxin type A treatment are main procedures for aesthetic correction of a broad lower face. There are a few date to show the differences in the mandibular contouring changes between mandibular angle splitting ostectomy and botulinum toxin type A treatment. Facial golden mask is easy to apply, inexpensive, and relatively objective for evaluation of facial contour analysis. This study was designed specifically to compare the changes in lower face width after two different forms of lower facial contouring procedure using facial golden mask. Methods: Seventeen patients, aged 18 to 55 years (mean, 28.6 years), 15 women and 2 men, consented to the study and receive a contouring procedure of lower face. The patients were classified in to 2 groups. In group A, the sample consisted of 10 patients with a prominent squared mandibular angle and mandibular angle splitting ostectomy was performed. In group B, the sample consisted of 7 patients with masseteric hypertrophy and botulinum toxin type A treatment was performed. Photographs of the face were taken to record the facial change at preoperative and postoperative. The postoperative photographs were taken to considered maximal effect at 2 years after surgery in group A and 4.8 months after treatment in group B. The authors applied the facial golden mask to preoperative and postoperative photographs and horizontal ratio, which compares facial width with golden mask width, were calculated. We made an analysis of the result of horizontal ratio using SPSS. Results: Overall average horizontal ratio of pre- and postoperative photos of group A were 1.24 and 1.11, whereas overall average horizontal ratio of pre- and postoperative photos of group B were 1.19 and 1.12. The horizontal ratio decreased 10.24% in group A and 5.93% in group B. There was a statistically significant change in before and after treatment, but there was no significant change in comparing the group A and group B. Conclusions: The result from this study suggest that mandibular angle sagittal ostectomy and botulinum toxin type A treatment showed relatively satisfactory clinical effects on lower facial contouring treatment. There was no statistical significant difference within two lower facial contouring treatment. Facial golden mask is easy to apply, inexpensive, and relatively objective, so we think that facial golden mask is a good method for evaluation of lower facial contouring treatment.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.4
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• pp.283-288
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• 2001

In this paper, we proposed a method for extracting facial characteristics of human being in an image. Given a pair of gray level sample images taken with and without human being, the face of human being is segmented from the image. Noise in the input images is removed with the help of Gaussian filters. Edge maps are found of the two input images. The binary edge differential image is obtained from the difference of the two input edge maps. A mask for face detection is made from the process of erosion followed by dilation on the resulting binary edge differential image. This mask is used to extract the human being from the two input image sequences. Features of face are extracted from the segmented image. An effective recognition system using the discrete wave let transform (DWT) is used for recognition. For extracting the facial features, such as eyebrows, eyes, nose and mouth, edge detector is applied on the segmented face image. The area of eye and the center of face are found from horizontal and vertical components of the edge map of the segmented image. other facial features are obtained from edge information of the image. The characteristic vectors are extrated from DWT of the segmented face image. These characteristic vectors are normalized between +1 and -1, and are used as input vectors for the neural network. Simulation results show recognition rate of 100% on the learned system, and about 92% on the test images.

• Clean Technology
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• v.4 no.1
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• pp.60-67
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• 1998

As workers' health and welfare are becoming increasingly important, there are needs for protecting workers from being exposed to dust particles in workplace. One of the simplest ways to protect workers is to wear a one-time-use mask of the 3M type. Although conventional masks are convenient to use, they provide low filtration efficiency simply because of air leaks through interface between the face and the mask. In this study, a new type of mask is developed and tested. The air which is filtered first using high efficiency particulate air(HEPA) filter is supplied to the nose area of workers' face. The developed mask was tested for filtration efficiency and for workers' acceptance. Very good results were obtained for both accounts.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.300-302
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• 2021

Usage of a face mask has become mandatory in many countries after the COVID-19. This paper described to develop a IoT based smart mask system for monitoring face mask. The system developed in this paper has two main units, a sensor module, and a smartphone application. The sensor module consists of four components: temperature and humidity sensor, a heart rate sensor, and a BLE chip. This components work as a unit to collect data and stream them through an I2C port over BLE to a connected mobile device. The smartphone application is an Android application developed for smart phones. It enables the Android device to communicate with the sensor to receive sensor data, process, store and display results.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.3
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• pp.76-79
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• 2014

Face recognition is very challenging because of the unexpected changes of pose, expression, and illumination. Facial detection in the mobile environments has additional difficulty since the computational resources are very limited. This paper discusses face detection based on frequency domain matched filtering in the mobile environments. Face detection is performed by a linear or phase-only matched filter and sequential verification stages. The candidate window regions are selected by a number of peaks of the matched filtering outputs. The sequential stages comprise a skin-color test and an edge mask filtering tests, which aim to remove false alarms among selected candidate windows. The algorithms are built with JAVA language on the mobile device operated by the Android platform. The simulation and experimental results show that real-time face detection can be performed successfully in the mobile environments.

• Journal of the Korea Society of Computer and Information
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• v.15 no.2
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• pp.55-64
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• 2010

This paper proposes a face detection method using Free Rectangle feature which possesses a quick execution time and a high efficiency. The proposed mask of Free Rectangle feature is composed of two separable rectangles with the same area. In order to increase the feature diversity, Haar-like feature generally uses a complex mask composed of two or more rectangles. But the proposed feature mask can get a lot of very efficient features according to any position and scale of two rectangles on the feature window. Moreover, the Free Rectangle feature can largely reduce the execution time since it is defined as the only difference of the sum of pixels of two rectangles irrespective of the mask type. Since it yields a quick detection speed and good detection rates on real world images, the proposed face detection method based on Adaboost algorithm is easily applied to detect another object by changing the training dataset.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.731-740
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• 2021

This study applied LDA topic modeling analysis to collect and analyze news media big data related to face masks in the three waves of the COVID-19 pandemic in Korea. The results empirically show that media reports focused on mask production and distribution policies in the first wave and the mandatory mask wearing in the second wave. In contrast, more reports on trivial, gossipy events consist of the media coverage in the second and third waves. The findings imply that Korea's governmental interventions to address the shortage of face masks and to regulate mask wearing were successful relatively in a short time. In contrast, the study also reports that there may be relative less number of science-based news reports like the ones on the effectiveness of face masks or different levels of filter types. This study exemplifies how a big data analysis can be applied to evaluate and enhance public health communication.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.27 no.4
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• pp.191-195
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• 2017

The microstructures of nonwoven fabric with and without nanofibers used as a filter for air purification type mask were investigated using scanning electron microscope. Moreover, we proposed a new mask design which is effective in the improvement of the fine dust blocking property. When comparing to nonwoven fabrics of which an average diameter was $25{\mu}m$, the nanofibers formed by the electrospinning process had a tight mesh structure arranged irregularly with a relatively large specific surface area, which could be associated with their much smaller diameter ranging from 25 to 120 nm. Such a prominent structural feature at nanofibers led to mechanical adsorption of fine particles, resulting in enhancement of filtering behavior maintaining high permeability. In addition to the excellent performance of the mask filter, wearing the mask properly is expected to maximize the blocking property of fine dust. To meet such a requirement, a new mask design that can be closely attached to the face in order to effectively block fine dust entering the gap between the face and the mask.