• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.1
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• pp.97-106
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• 2014

CCTV(Closed Circuit television) is one of the widely used physical security technologies and video acquisition device installed at specific point with various purposes. Recently, as the CCTV capabilities improve, facial recognition from the information collected from CCTV video is under development. However, in case these technologies are exploited, concerns on major privacy infringement are high. Especially, a computer connected to a particular space images taken by the camera in real time over the Internet has emerged to show information services. In the privacy law, safety measures which is related with biometric template are notified. Accordingly, in this paper, for the protection of privacy video information in the video surveillance system, the technical and managerial requirements for video information security are suggested.

• Journal of Korea Multimedia Society
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• v.15 no.1
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• pp.40-50
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• 2012

Face recognition is a biometric technology used to identify individuals based on facial feature information. Previous studies of face recognition used features including the eye, mouth and nose; however, there have been few studies on the effects of using other facial components, such as the eyebrows and chin, on recognition performance. We measured the recognition accuracy affected by these facial components, and compared the differences between computer-based and human-based facial recognition methods. This research is novel in the following four ways compared to previous works. First, we measured the effect of components such as the eyebrows and chin. And the accuracy of computer-based face recognition was compared to human-based face recognition according to facial components. Second, for computer-based recognition, facial components were automatically detected using the Adaboost algorithm and active appearance model (AAM), and user authentication was achieved with the face recognition algorithm based on principal component analysis (PCA). Third, we experimentally proved that the number of facial features (when including eyebrows, eye, nose, mouth, and chin) had a greater impact on the accuracy of human-based face recognition, but consistent inclusion of some feature such as chin area had more influence on the accuracy of computer-based face recognition because a computer uses the pixel values of facial images in classifying faces. Fourth, we experimentally proved that the eyebrow feature enhanced the accuracy of computer-based face recognition. However, the problem of occlusion by hair should be solved in order to use the eyebrow feature for face recognition.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1485-1490
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• 2004

Recently, we have remarkable developments in intelligent robot systems. The remarkable features of intelligent robot are that it can track user, does face recognition and vital for many surveillance based systems. Advantage of face recognition when compared with other biometrics recognition is that coerciveness and contact that usually exist when we acquire characteristics do not exist in face recognition. However, the accuracy of face recognition is lower than other biometric recognition due to decrease in dimension from of image acquisition step and various changes associated with face pose and background. Factors that deteriorate performance of face recognition are many such as distance from camera to face, lighting change, pose change, and change of facial expression. In this paper, we implement a new 3D active camera system to prevent various pose variation that influence face recognition performance and propose face recognition algorithm for intelligent surveillance system and mobile robot system.

• The Journal of the Korea Contents Association
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• v.15 no.7
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• pp.591-600
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• 2015

Recently high interest in health and fitness has led to vibrant researches for the active fitness system to learn and enjoy the exercise program for oneself. In this paper, we design and implement the active spinning training system which enables user to have self-learning and experience of customized spinning training program by the biometric and movement information acquired from user's physiological signals. The proposed system provides the appropriate difficulty of spinning program which reflects the concordance rate of spinning dance gestures and the amount of exercising by analyzing the physical status of participant from his brain and pulse waves and recognizing the skeletal movement in real time. For the higher exercise effect, the system offers a virtual personal trainer to show the correct poses and controls the level of difficulty depending on the concordance rate of participant's motions. The experiment with various participants through the proposed system shows that it is able to help users in getting the available exercise effect in comparatively short time.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.5
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• pp.1187-1199
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• 2015

Recently, as high-quality sensors are being developed, it is available to conveniently measure any kind of data. Healthcare services are being combined with Internet of things (IoTs). And applications that use user's data which are remotely measured, such as heart rate, blood oxygen level, temperature are emerging. The typical example is applications that find ideal spouse by using a user's genetic information, or indicate the presence or absence of a disease. Such information is closely related to the user's privacy, so biometric information must be protected. That is, service provider must provide the service while preserving user's privacy. In this paper, we propose a scheme which enables privacy-preserving outlier detection in Healthcare Service.

• Journal of the Korea Convergence Society
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• v.11 no.4
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• pp.151-156
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• 2020

The purpose of this study is to design a process for developing wearable sports helmet devices by utilizing IoT server technology, focusing on sports where helmet wear is essential at sports sites. This enables customized training of athletes by continuously accumulating personal biometric information during training, checking players' condition based on data, and informing them of injury prevention and dangerous situations. In addition, the wearable device that can be useful when the training place is likely to damage the physical health due to heat waves or extremes can provide a foundation for improving the performance. Since such technology can be applied not only to the sports field but also to the society such as the industrial field or the underprivileged, it can be expected to be expandable.

• Journal of Venture Innovation
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• v.2 no.2
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• pp.21-29
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• 2019

In the public certificate technology commonly used in Korea, users have a cumbersome problem of always resetting when they forget their password. In this paper, as a solution to this problem, we propose a secure authentication certificate password recovery protocol using blockchain, PKI, and DID for distributed storage. DID is a schema for protecting block ID in blockchain system. The private key used in the PKI is configured as a user's biometric, for example, a fingerprint, so that it can completely replace the memory of the complex private key. To this end, based on the FIDO authentication technology that most users currently use on their smartphones, the process of authenticating a user to access data inside the block minimizes the risk of an attacker taking over the data.

• Journal of the Korea Convergence Society
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• v.9 no.8
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• pp.1-8
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• 2018

In the field of biometric security such as face and iris recognition, it is essential to extract facial features such as eyes and lips. In this paper, we have studied a method of detecting eye and lip region in face image using faster R-CNN. The faster R-CNN is an object detection method using deep running and is well known to have superior performance compared to the conventional feature-based method. In this paper, feature maps are extracted by applying convolution, linear rectification process, and max pooling process to facial images in order. The RPN(region proposal network) is learned using the feature map to detect the region proposal. Then, eye and lip detector are learned by using the region proposal and feature map. In order to examine the performance of the proposed method, we experimented with 800 face images of Korean men and women. We used 480 images for the learning phase and 320 images for the test one. Computer simulation showed that the average precision of eye and lip region detection for 50 epoch cases is 97.7% and 91.0%, respectively.

• The Korean Journal of Ecology
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• v.27 no.1
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• pp.15-20
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• 2004

With attention to different human activities around Anzali wetland and introduction of different pollutants containing heavy metals into this water ecosystem and absorption and accumulation of heavy metals in shell and muscle of Astacus leptodactylus which is native benthose of Anzali wetland and enjoys food and economic importance; Sampling of waters and sediments from 18 stations and shell and muscle of Astacus leptodactylus from 5 stations had been conducted. After biometric evaluation of Astacus leptodactylus, the chemical analysis of the samples by using international and standard methods and then their heavy metals content was determined by Atomic Absorpotion Spectrophotometer (AAS), model P.U 9400 philips. Result of the analysis stated that; 1) The mean values of Cr, Zn, Pb, Ni, V in Anzali waters were 6.4, 184.5, 28.8, 28.9, 47.1 ($\mu$ gr/lit) respectively, which comparing to the international standards, is not suitable for drinking, but it can be used for agricultural and aquacultural purposes. Even though the concentration of heavy metals in sediments were high, there are in range of acceptable limit for aquatics organisms; 2) Comparatively, the concentration of heavy metals in shell and muscle of Astacus leptodactylus in Anzali wetland (Cr, Zn, Pb, Ni, V in shell were 3.48, 109.3, 14.13, 7.17, 36.2 and in muscle were 2.98, 131.98, 3.12, 4.77, 9.05 ppm respectively) were more than what is determined for Aras dam (in shell were 1.6, 224.3, 7.8, 7.6, 10.3 and in muscle were 1.4, 60.2, 0.45, 2.7, 4.4 mg/kgr respectively); 3) For all samples, concentration of heavy metals in all Astacus leptodactylus in Anzali wetland and Aras dam, was at tolerance level for human consumption; 4) There was no association with significant difference between weight and size of Astacus leptodactylus with absorption and accumulation of heavy metals; but there was a significant association between heavy metals content in water and in sediments, and in sediments, shell and muscle of Astacus leptodactylus in Anzali wetland.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.4
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• pp.349-354
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• 2014

PIN(Personal Identification Number)-based identification method has been used to identify the user of smart cards. However, this type of identification method has several problems. Firstly, PIN can be forgotten by owners of the card. Secondly, PIN can be used by others illegally. Furthermore, the possibility of hacking PIN can be high because this PIN type matching process is performed on terminal. Thus, in this paper we suggest a new identification method which is performed on smart card using face feature information. The proposed identification method uses low-sized face feature vectors and simple matching algorithm in order to get around the limits in computing capability and memory size of smart card.