• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.1
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• pp.75-83
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• 2008

We propose a welfare interface using multiple fecial features tracking, which can efficiently implement various mouse operations. The proposed system consist of five modules: face detection, eye detection, mouth detection, facial feature tracking, and mouse control. The facial region is first obtained using skin-color model and connected-component analysis(CCs). Thereafter the eye regions are localized using neutral network(NN)-based texture classifier that discriminates the facial region into eye class and non-eye class, and then mouth region is localized using edge detector. Once eye and mouth regions are localized they are continuously and correctly tracking by mean-shift algorithm and template matching, respectively. Based on the tracking results, mouse operations such as movement or click are implemented. To assess the validity of the proposed system, it was applied to the interface system for web browser and was tested on a group of 25 users. The results show that our system have the accuracy of 99% and process more than 21 frame/sec on PC for the $320{\times}240$ size input image, as such it can supply a user-friendly and convenient access to a computer in real-time operation.

• Korean Journal of Veterinary Service
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• v.41 no.1
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• pp.29-39
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• 2018

In this study, we developed a sensitive and specific reverse transcription loop-mediated isothermal amplification (RT-LAMP) assay for rapid visual detection of foot-and-mouth disease virus (FMDV) circulated in Korea. The RT-LAMP was completed in 40 min at $62^{\circ}C$ and the results of the assay were directly detected by naked eye without any detection process. The assay specifically amplified all 7 serotypes of FMDV RNAs but not amplified other viral and cellular nucleic acids. The sensitivity of the RT-LAMP was $10^2$, $10^3$ and $10^3TCID_{50}/mL$ for serotype O, A and Asia 1 FMDV, respectively, which was comparable to conventional reverse transcription polymerase chain reaction (RT-PCR) and relatively lower than that of real time quantitative RT-PCR (qRT-PCR). Clinical evaluation of the RT-LAMP using different serotypes of Korean and foreign FMDV strains showed a 100% (35/35) agreement with the results of the RT-PCR and qRT-PCR. These results indicated that RT-LAMP assay developed in this study could be a valuable diagnostic method for FMDV monitoring and surveillance.

• Journal of Korea Multimedia Society
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• v.20 no.3
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• pp.474-481
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• 2017

In Korea, foot-and-mouth disease has not been reported for several decades, but it began to develop again in 2000. For 2010~2011, when the worst occurred, 3.5 million animals were disposed of resulting in a loss of 2.8 trillion won. In order to prevent the harmful effects of foot-and-mouth disease, vaccination and housing management are being implemented. Despite these measures, foot-and-mouth disease is infected with air through the respiratory tract and accompanies fever after latency. Therefore, it is recognized that measuring and managing the body temperature of livestock at the early stage is the first step of managing this disease. In this paper, we propose a temperature monitoring system that can measure the body temperature by incorporating temperature sensor mounted in ear-tag of cattle and collect body temperature data of each individual cattle through BLE into the control server. The proposed body temperature monitoring system has various advantages such as easy installation without the help of livestock specialists and not damaging the organs of the livestock. So, it is possible to manage the abnormal symptom of cattle in real time and it is believed that the proposed monitoring system will revolutionize the prevention of foot-and-mouth disease.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1534-1538
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• 2005

In this paper, we propose a method to detect contours of a face, eyes, and a mouth of a person in the color image in order to make an avatar automatically. First, we use the HSI color model to exclude the effect of various light conditions, and find skin regions in the input image by using the skin color defined on HS-plane. And then, we use deformable templates and genetic algorithm (GA) to detect contours of a face, eyes, and a mouth. Deformable templates consist of B-spline curves and control point vectors. Those represent various shapes of a face, eyes and a mouth. GA is a very useful search algorithm based on the principals of natural selection and genetics. Second, the avatar is automatically created by using GA-detected contours and Fuzzy C-Means clustering (FCM). FCM is used to reduce the number of face colors. In result, we could create avatars which look like handmade caricatures representing user's identity. Our approach differs from those generated by existing methods.

• Journal of Korea Multimedia Society
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• v.23 no.12
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• pp.1454-1463
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• 2020

An important factor in eye-tracking PC interface for general paralyzed patients is the implementation of the mouse interface, for manipulating the GUI. With a successfully implemented mouse interface, users can generate mouse events exactly at the point of their choosing. However, it is difficult to define this interaction in the eye-tracking interface. This problem has been defined as the Midas touch problem and has been a major focus of eye-tracking research. There have been many attempts to solve this problem using blink, voice input, etc. However, it was not suitable for general paralyzed patients because some of them cannot wink or speak. In this paper, we propose a mouth-pop-up, eye-tracking mouse interface that solves the Midas touch problem as well as becoming a suitable interface for general paralyzed patients using a common RGB camera. The interface presented in this paper implements a mouse interface that detects the opening and closing of the mouth to activate a pop-up menu that the user can select the mouse event. After implementation, a performance experiment was conducted. As a result, we found that the number of malfunctions and the time to perform tasks were reduced compared to the existing method.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.5
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• pp.520-525
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• 2014

Generally, feature area detection methods are widely used for face expression recognition by detecting the feature areas of human eyes, eyebrows and mouth. In this paper, we proposed a face expression recognition method using the histograms of the face, eyes and mouth for many applications including robot technology. The experimental results show that the proposed method has a new type of face expression recognition capability compared to conventional methods.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.49-52
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• 2002

This paper presents a fast algorithm for face detection from color images on internet. We use Mahalanobis distance between standard skin color and actual pixel color on IQ color space to segment skin color regions. The skin color regions are the candidate face region. Further, the locations of eyes and mouth regions are found by computing average pixel values on horizontal and vertical pixel lines. The geometry of mouth and eye locations is compared to the standard face geometry to eliminate false face regions. Our Method is simple and fast so that it can be applied to face search engine for internet.

• Journal of Veterinary Science
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• v.24 no.3
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• pp.40.1-40.6
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• 2023

Analysis of the VP1 gene sequence of the foot and mouth disease virus (FMDV) is critical to understanding viral evolution and disease epidemiology. A standard set of primers have been used for the detection and sequence analysis of the VP1 gene of FMDV directly from suspected clinical samples with limited success. The study validated VP1-specific degenerate primer-based reverse transcription polymerase chain reaction (RT-PCR) for the qualitative detection and sequencing of serotype O FMDV lineages circulating in India. The novel degenerate primer-based RT-PCR amplifying the VP1 gene can circumvent the genetic heterogeneity observed in viruses after cell culture adaptation and facilitate precise viral gene sequence analysis from clinical samples.

• Journal of Korea Multimedia Society
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• v.10 no.12
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• pp.1566-1576
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• 2007

Camera pose information from 2D face image is very important for making virtual 3D face model synchronize with the real face. It is also very important for any other uses such as: human computer interface, 3D object estimation, automatic camera control etc. In this paper, we have presented a camera position determination algorithm from a single 2D face image using the relationship between mouth position information and face region boundary information. Our algorithm first corrects the color bias by a lighting compensation algorithm, then we nonlinearly transformed the image into $YC_bC_r$ color space and use the visible chrominance feature of face in this color space to detect human face region. And then for face candidate, use the nearly reversed relationship information between $C_b\;and\;C_r$ cluster of face feature to detect mouth position. And then we use the geometrical relationship between mouth position information and face region boundary information to determine rotation angles in both x-axis and y-axis of camera position and use the relationship between face region size information and Camera-Face distance information to determine the camera-face distance. Experimental results demonstrate the validity of our algorithm and the correct determination rate is accredited for applying it into practice.

• 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.