• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.3
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• pp.526-534
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• 2006

In this paper we propose a new algorithm to detect the irises of both eyes from a human face. Using the separability filter, the algorithm first extracts blobs(intensity valleys) as the candidates for the irises. Next, for each pair of blobs. the algorithm computes a cost usings Hough transform and separability later to measure the fit of the pair of blobs to the image. And then, the algorithm selects a pair of blobs with the smallest cost as the irises of both eyes. As the result of the experiment using 150 faces images without spectacles, the success rate of the proposed algorithm was 97.3% for the best case and 95.3% for the worst case.

• IE interfaces
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• v.19 no.3
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• pp.174-180
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• 2006

This paper deals with the robot system of recognizing human's expression from a detected human's face and then showing human's emotion. A face detection method is as follows. First, change RGB color space to CIElab color space. Second, extract skin candidate territory. Third, detect a face through facial geometrical interrelation by face filter. Then, the position of eyes, a nose and a mouth which are used as the preliminary data of expression, he uses eyebrows, eyes and a mouth. In this paper, the change of eyebrows and are sent to a robot through serial communication. Then the robot operates a motor that is installed and shows human's expression. Experimental results on 10 Persons show 78.15% accuracy.

• Journal of Korea Multimedia Society
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• v.8 no.11
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• pp.1421-1431
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• 2005

There are two methods in 3-D sound reproduction: a surround system, like 3.1 channel method and a binaural system using 2-channel method. The binaural system utilizes the sound localization principle of a human using two ears. Generally, a crosstalk between each channel of 2-channel loudspeaker system should be canceled to produce a natural 3-D sound. To solve this problem, it is necessary to trace a head movement. In this paper, we propose a new algorithm to correctly trace the head movement of a listener. The Proposed algorithm is based on the detection of face and eye. The face detection uses the intensity of an image and the position of eyes is detected by a mathematical morphology. When the head of the listener moves, length of borderline between face area and eyes may change. We use this information to the tracking of head movement. A computer simulation results show That head movement is effectively estimated within +10 margin of error using the proposed algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.227-232
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• 2003

Non-intrusive methods based on active remote IR illumination for eye tracking is important for many applications of vision-based man-machine interaction. One problem that has plagued those methods is their sensitivity to lighting condition change. This tends to significantly limit their scope of application. In this paper, we present a new real-time eye detection and tracking methodology that works under variable and realistic lighting conditions. eased on combining the bright-pupil effect resulted from IR light and the conventional appearance-based object recognition technique, our method can robustly track eyes when the pupils are not very bright due to significant external illumination interferences. The appearance model is incorporated in both eyes detection and tracking via the use of support vector machine and the mean shift tracking. Additional improvement is achieved from modifying the image acquisition apparatus including the illuminator and the camera.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.447-450
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• 2013

This paper proposes the way to prevent drowsy driving by recognizing drivers eyes and yawn using a front camera. The method uses the Viola-Jones algorithm to detect eyes area and mouth area from detection face region. In the eyes area, it uses the Hough transform to recognize eye circle in order to distinguish drowsy driving. In the mouth area, it determines whether for the driver to yawn through a sub-window testing by applying a HSV-filter and detecting skin color of the tongue. The test result shows that the recognition rate of yawn reaches up to 90%. It is expected that the method introduced in this paper might contribute to reduce the number of drowsy driving accidents.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.8
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• pp.839-844
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• 2009

In this paper, a real-time eye tracking method using fast face detection is proposed. Most of the current eye tracking systems have operational limitations due to sensors, complicated backgrounds, and uneven lighting condition. It also suffers from slow response time which is not proper for a real-time application. The tracking performance is low under complicated background and uneven lighting condition. The proposed algorithm detects face region from acquired image using elliptic Hough transform followed by eye detection within the detected face region using Haar-like features. In order to reduce the computation time in tracking eyes, the algorithm predicts next frame search region from the information obtained in the current frame. Experiments through simulation show good performance of the proposed method under various environments.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.575-578
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• 1999

The principal features of a face are as follows : skin-tone, symmetry, and requisites such as shape of ellipse, eyes, nose, mouth. Also, faces have different size, various shape and position. In case of application of face recognition and detection without preprocessing, efficiency of the performance is decreased. In addition, face itself, complex background, image quality, etc. are included. Therefore, previous face recognition methods are implemented on the base of specific constraints of the face image. In this paper, we propose the efficient and automatic face detection algorithm for minimizing influence such as complex background, image quality, etc. This face detection technique consists of skin-tone, candidate face region and face region extractions.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.12
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• pp.1667-1670
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• 2014

This paper describes a method for detecting the pupil region and identification of the eye status for driver drowsiness detection system. This program detects a driver's face and eyes using viola-jones face detection algorithm and extracts the pupil area by utilizing mean values of each row and column on the eye area. The proposed method uses binary images and the number of black pixels to identify the eye status. Experimental results showed that the accuracy of classification eye status(open/close) was above 90%.

• BMB Reports
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• v.38 no.4
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• pp.399-406
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• 2005

A sensitive method for detection of Hepatitis A virus (HAV) by utilizing gold-DNA probe on an array was developed. Amino- modified oligodeoxynucleotides at the 5' position were arrayed on an activated glass surface to function as capture probes. Sandwich hybridization occurred among capture probes, the HAV amplicon, and gold nanoparticle-supported oligonucleotide probes. After a silver enhancement step, signals were detected by a standard flatbed scanner or just by naked eyes. As little as 100 fM of HAV amplicon could be detected on the array. Therefore, the array technology is an alternative to be applied in detection of HAV due to its low-cost and high-sensitivity.

• BMB Reports
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• v.39 no.3
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• pp.247-252
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• 2006

A rapid method for the detection of Hepatitis E Virus (HEV) was developed by utilizing nano-gold labeled oligonucleotide probes, silver stain enhancement and the microarray technique. The 5'-end -$NH_2$ modified oligonucleotide probes were immobilized on the surface of the chip base as the capture probe. The detection probe was made of the 3'-end -SH modified oligonucleotide probe and nano-gold colloid. The optimal concentrations of these two probes were determined. To test the detection sensitivity and specificity of this technique, a conservative fragment of the virus RNA was amplified by the RT-PCR/PCR one step amplification. The cDNA was hybridized with the capture probes and the detection probes on microarray. The detection signal was amplified by silver stain enhancement and could be identified by naked eyes. 100 fM of amplicon could be detected out on the microarray. As the results, preparation of nano-gold was improved and faster. Development time also was shortened to 2 min. Thus, considering high efficiency, low cost, good specificity and high sensitivity, this technique is alternative for the detection of HEV.