• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.2
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• pp.349-356
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• 2020

This paper introduces the implementation of a driver's condition warning system using eye aspect ratio to prevent a car accident. The proposed driver's condition warning system using eye aspect ratio consists of a camera, that is required to detect eyes, the Raspberrypie that processes information on eyes from the camera, buzzer and vibrator, that are required to warn the driver. In order to detect and recognize driver's eyes, the histogram of oriented gradients and face landmark estimation based on deep-learning are used. Initially the system calculates the eye aspect ratio of the driver from 6 coordinates around the eye and then gets each eye aspect ratio values when the eyes are opened and closed. These two different eye aspect ratio values are used to calculate the threshold value that is necessary to determine the eye state. Because the threshold value is adaptively determined according to the driver's eye aspect ratio, the system can use the optimal threshold value to determine the driver's condition. In addition, the system synthesizes an input image from the gray-scaled and LAB model images to operate in low lighting conditions.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.5
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• pp.457-464
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• 2009

The weak classifier of AdaBoost algorithm is a central classification element that uses a single criterion separating positive and negative learning candidates. Finding the best criterion to separate two feature distributions influences learning capacity of the algorithm. A common way to classify the distributions is to use the mean value of the features. However, positive and negative distributions of Haar-like feature as an image descriptor are hard to classify by a single threshold. The poor classification ability of the single threshold also increases the number of boosting operations, and finally results in a poor classifier. This paper proposes a weak classifier that uses multiple criterions by adding a probabilistic criterion of the positive candidate distribution with the conventional mean classifier: the positive distribution has low variation and the values are closer to the mean while the negative distribution has large variation and values are widely spread. The difference in the variance for the positive and negative distributions is used as an additional criterion. In the learning procedure, we use a new classifier that provides a better classifier between them by selective switching between the mean and standard deviation. We call this new type of combined classifier the "Mixed Weak Classifier". The proposed weak classifier is more robust than the mean classifier alone and decreases the number of boosting operations to be converged.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.3
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• pp.55-63
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• 2008

This paper presents a panorama background generation and object tracking technique using a Pan-Tilt-Zoom camera. The proposed method estimates local motion vectors rapidly using phase correlation matching at the prespecified multiple local regions, and it makes minimized estimation error by vector quantization. We obtain the required image patches, by estimating the overlapped region using local motion vectors, we can then project the images to cylinder and realign the images to make the panoramic image. The object tracking is performed by extracting object's motion and by separating foreground from input image using background subtraction. The proposed PTZ-based object tracking method can efficiently generated a stable panorama background, which covers up to 360 degree FOV The proposed algorithm is designed for real-time implementation and it can be applied to many commercial applications such as object shape detection and face recognition in various surveillance video systems.

• Phonetics and Speech Sciences
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• v.2 no.2
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• pp.37-42
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• 2010

The purpose of this study is to first discriminate and assess those infants who appear healthy in appearance but who could face possible risk factors in the future and, secondly, to identify those infants who may have difficulties in their developmental stages. The subjects of this study consisted of 35 full-term infants (39-40 weeks) and 33 pre-term infants (34-35 weeks). The infants' voices were recorded for three minutes, for which EDIROL by Roland and a stand-type microphone made by SONY were used. This was done to discern the value of the Breath unit (B-unit) and the fundamental frequencies ($F_0$). It was found that there were significant differences in terms of F0 since the pre-term infants had higher F0 than the full-term infants, showing a result of 436.4 Hz for the full-term infants and 460 Hz for the pre-term infants (p<.05) There was an average rate of 4.01 for the full-term infants and 4.02 (SD=1.69) for the pre-term infants in shimmer. For NHR, it was observed .44 for the full-term infants and .50 for the pre-term infants, thus revealing no significant differences in these observations. This study shows that the crying of newborn babies is related to their physical conditions and it is a sensatory response to these conditions. Furthermore, this study could be helpful for the early detection and measurement of newborn babies who look clinically healthy but could be at risk through acoustic and physiological analyses.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.3
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• pp.60-68
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• 2007

In this paper, we propose an automatic facial expressions recognition system to analyze facial expressions (happiness, disgust, surprise and neutral) using tree structures based on heuristic rules. The facial region is first obtained using skin-color model and connected-component analysis (CCs). Thereafter the origins of user's eyes are localized using neural network (NN)-based texture classifier, then the facial features using some heuristics are localized. After detection of facial features, the facial expression recognition are performed using decision tree. To assess the validity of the proposed system, we tested the proposed system using 180 facial image in the MMI, JAFFE, VAK DB. The results show that our system have the accuracy of 93%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.3
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• pp.482-488
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• 2009

Mobile Ad-hoc Networks provide communication without a centralized infrastructure, which makes them suitable for communication in disaster areas or when quick deployment is needed. On the other hand, they are susceptible to malicious exploitation and have to face different challenges at different layers due to its open Ad-hoc network structure which lacks previous security measures. Denial of service (DoS) attack is one that interferes with the radio transmission channel causing a jamming attack. In this kind of attack, an attacker emits a signal that interrupts the energy of the packets causing many errors in the packet currently being transmitted. In harsh environments where there is constant traffic, a jamming attack causes serious problems; therefore measures to prevent these types of attacks are required. The objective of this paper is to carry out the simulation of the jamming attack on the nodes and determine the DoS attacks in OPNET so as to obtain better results. We have used effective anomaly detection system to detect the malicious behaviour of the jammer node and analyzed the results that deny channel access by jamming in the mobile Ad-hoc networks.

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.116-120
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• 2008

Smart Camera provides intelligent vision functionalities which can interpret captured video, extract context-aware information and execute a necessary action in real-timeliness in addition to the functionality of network cameras which transmit the compressed acquired videos through networks. Intelligent vision algorithms demand tremendous computations so that real-time processing of computation of intelligent vision algorithms as well as compression and transmission of videos simultaneously is too much burden for a single CPU. Davinci processor of Texas Instruments is a popular ASSP(Application Specific Standard Product) which has dual core architecture of ARM core and DSP core and provides various I/O interfaces as well as networking interface and video acquiring interface necessary for developing digital video embedded applications. In this paper, we report the results of designing and implementing S/W for Davinci-based smart camera. We implement a face detection as an example of vision application and verify the implementation works well. In the future, for the development of a smart camera with more broad and real-time vision functionalities, it is necessary to study about more efficient vision application S/W architecture and optimization of vision algorithms on DSP core of Davichi processor.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.254-260
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• 2019

Recently, a self-camera that generates and distributes a large amount of moving images has been rapidly increasing due to the appearance of SNS such as Facebook, Instagram, and Tweet using mobile. In particular, the amount of SNS connections using mobile phones is significantly increasing in terms of usage, number of connections, and usage time. However, the use of a self-recording system using a smartphone by itself is extremely limited not only in terms of usage but also in frequency of use. In addition, the conventional unattended recording system is a very expensive system that automatically records and tracks an object to be photographed using an infrared signal. Therefore, this paper developed a low cost unmanned recording system using mobile phone. The system consists of a commercial mobile camera, a servomotor for moving the camera from side to side, a microcontroller for controlling the motor, and a commercial wireless Bluetooth earset for video audio input. And it is an unmanned automation system using mobile, and anyone can record image by self image tracking.

• Journal of Genetic Medicine
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• v.15 no.2
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• pp.92-96
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• 2018

Chronic mucocutaneous candidiasis (CMC) is characterized by increased susceptibility to chronic and recurrent infections of the skin, mucous membranes, and nails by Candida species. It is a primary immunodeficiency disorder that is difficult to diagnose because of its heterogeneous clinical manifestations and genetic background. A 20-month-old boy who did not grow in height for 3 months was diagnosed as having hypothyroidism and he had hepatitis which was found at 5 years old. He presented with persistent oral thrush and vesicles on the body, the cause of which could not be identified from laboratory findings. No microorganism was detected in the throat culture; however, the oral thrush persisted. Immunological tests showed that immunoglobulin (Ig) subclass IgG and cluster of differentiation (CD)3, CD4, and CD8 levels were within normal limits. We prescribed oral levothyroxine and fluconazole mouth rinse. The patient was examined using diagnostic exome sequencing at the age of 6 years, and a c.1162A>G (p.K388E) STAT1 gene mutation was identified. A diagnosis of CMC based on the STAT1 gene mutation was, thus, made. At the age of 8 years, the boy developed a malar-like rash on his face. We conducted tests for detection of antinuclear antibodies and anti-dsDNA antibodies, which showed positive results; therefore, systemic lupus erythematosus (SLE) was also suspected. Whole exome sequencing is important to diagnose rare diseases in children. A STAT1 gene mutation should be suspected in patients with chronic fungal infections with a thyroid disease and/or SLE.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.11
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• pp.1337-1342
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• 2019

Medical institutions face the challenge of securing competitiveness among medical institutions due to the rapid spread of ICT convergence, and managing data that is growing at an enormous rate due to the emergence of big data and the emergence of the Internet of Things. The big data paradigm of the medical community is not just about large data or tools and processes for processing and analyzing it, but also means a computerized shift in the way people live, think and study. As the medical data is recently released, the demand for the use of medical data is increasing. Therefore, the research on disease detection system based on public data using open source that can help rational and efficient decision making was conducted. As a result of the experiment, unlike a simple disease inquiry or a symptom inquiry about a single disease provided by a public institution, related diseases are searched by a symptom or a cause.