• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2011년도 한국컴퓨터종합학술대회논문집 Vol.38 No.1(C)
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• pp.405-408
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• 2011

In this paper, we propose a robot remote control system based on mouth tracking. The main idea behind the work is to help disabled people who cannot operate a joystick or keyboard to control a robot with their hands. The mouth detection method in this paper is mainly based on the Adaboost feature detection approach. By using the proposed new Haar-like features for detecting the corner of mouth, the speed and accuracy of detection are improved. Combined with the Kalman filter, a continuous and accurate mouth tracking has been achieved. Meanwhile, the gripping commands of the robot manipulator were also achieved by the recognition of the user.s mouth shape, such as 'pout mouth' or 'grin mouth'. To assess the validity of the method, a mouth detection experiment and a robot cargo transport experiment were applied. The result indicated that the system can realize a quick and accurate mouse tracking; and the operation of the robot worked successfully in moving and bringing back items.

• Journal of Veterinary Science
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• 제23권5호
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• pp.32.1-32.11
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• 2022

Background: Classical swine fever (CSF) is a severe infectious disease of pigs that causes significant economic losses to the swine industry. Objectives: This study developed a solid-phase blocking enzyme-linked immunosorbent assay (spbELISA) method for the specific detection of antibodies against the CSF virus (CSFV) in porcine serum samples. Methods: A spbELISA method was developed based on the recombinant E2 expressed in Escherichia coli. The specificity of this established spbELISA method was evaluated using reference serum samples positive for antibodies against other common infectious diseases. The stability and sensitivity were evaluated using an accelerated thermostability test. Results: The spbELISA successfully detected the antibody levels in swine vaccinated with the C-strain of CSFV. In addition, the detection ability of spbELISA for CSFV antibodies was compared with that of other commercial ELISA kits and validated using an indirect immunofluorescence assay. The results suggested that the spbELISA provides an alternative, stable, and rapid serological detection method suitable for the large-scale screening of CSFV serum antibodies. Conclusions: The spbELISA has practical applications in assessing the vaccination status of large pig herds.

• 한국인터넷방송통신학회논문지
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• 제14권3호
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• pp.89-97
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• 2014

본 논문에서는 운전자의 졸음 판단에 필요한 눈 깜빡임과 하품에 대해 실시간 빈도수 측정 프로그램을 제안한다. 사용자의 눈과 입의 개폐 빈도수 측정을 위해서 CCD 카메라 영상을 기반으로 OpenCV를 이용하여 얼굴을 검출한 후, 검출된 얼굴을 기반으로 눈동자 영역 추출 기술인 CDF(Cumulative Distribution Function)를 사용하여 눈의 위치를 찾아서 활성 윤곽(Active Contour) 기술을 이용하여 눈과 입의 영역을 추출한다. 추출된 눈과 입의 영역을 본 프로그램을 이용하여 각 각의 개폐 빈도수를 측정하며 결과 값을 분석하여 사용자의 졸음 판단을 위한 기반 기술로 활용한다.

• 한국동물위생학회지
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• 제35권4호
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• pp.255-261
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• 2012

Foot and mouth disease (FMD) is highly infectious disease of cloven-hoofed animals, particularly cattle, sheep, pigs and goats. Last outbreak reported in November, 2010 induced the enormous social and economical impacts. Culling of infected animals, movement control, and vaccination are the major control measures of FMD. The aim of this study was to detection foot-and-mouth disease virus (FMDV) in the soil and leachate from modeling burial for pig carcass as measured by real-time reverse transcriptase polymerase chain reaction (RT-PCR). FMDV and Coxsakievirus B1 (CVB1) were detected in soil by week 16 and Coxsakievirus B1 (CVB1) by weeks 12, respectively. FMDV and CVB1 also detected by weeks 8 in the leachate. Results from this study provides an evidence that FMDV could be inactivated for safe of pig carcasses infected with FMDV within 4 month in the carcass burial site.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 IWAIT
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• pp.425-428
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• 2009

We have researched and developed the caricature generation system PICASSO. PICASSO outputs the deformed facial caricature by comparing input face with prepared mean face. We specialized it as PICASSO-2 for exhibiting a robot at Aichi EXPO2005. This robot enforced by PICASSO-2 drew a facial caricature on the shrimp rice cracker with the laser pen. We have been recently exhibiting another revised robot characterized by a brush drawing. This system takes a couple of facial images with CCD camera, extracts the facial features from the images, and generates the facial caricature in real time. We experimentally evaluated the performance of the caricatures using a lot of data taken in Aichi EXPO2005. As a result it was obvious that this system were not sufficient in accuracy of eyebrow region extraction and mouth detection. In this paper, we propose the improved methods for eyebrow region extraction and mouth detection.

• 한국통신학회논문지
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• 제25권6B호
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• pp.1041-1049
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• 2000

A face recognition algorithm for the user identification procedure of automatic teller machine(ATM), as an application of the still image processing techniques is proposed in this paper. In the proposed algorithm, face recognition techniques, especially, face region detection, eye and mouth detection schemes, which can distinguish abnormal faces from normal faces, are proposed. We define normal face, which is acceptable, as a face without sunglasses or a mask, and abnormal face, which is non-acceptable, as that wearing both, or either one of them. The proposed face recognition algorithm is composed of three stages: the face region detection stage, the preprocessing stage for facial feature detection and the eye and mouth detection stage. Experimental results show that the proposed algorithm can distinguish abnormal faces from normal faces accurately from restrictive sample images.

• 한국멀티미디어학회논문지
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• 제10권12호
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• pp.1591-1600
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• 2007

Camera position information from 2D face image is very important for that make the virtual 3D face model synchronize to the real face at view point, and it is also very important for any other uses such as: human computer interface (face mouth), automatic camera control etc. We present an algorithm to detect human face region and mouth, based on special color features of face and mouth in $YC_bC_r$ color space. The algorithm constructs a mouth feature image based on $C_b\;and\;C_r$ values, and use pattern method to detect the mouth position. And then we use the geometrical relationship between mouth position information and face side boundary information to determine the camera position. Experimental results demonstrate the validity of the proposed algorithm and the Correct Determination Rate is accredited for applying it into practice.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제16권1호
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• pp.35-44
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• 2010

본 논문에서는 입력영상에서 적응적으로 피부색상 모델을 생성하여 얼굴을 탐지하는 방법을 제안한다. 제안하는 방법의 기본적인 절차는 먼저 눈의 특징을 인공신경망에 적용하여 눈 후보를 찾은 후, 그 주변의 색상을 이용하여 피부영역의 색상값 분포를 찾는다. 그 다음은 피부영역으로 검출된 색상값 분포를 이용하여 얼굴영역을 산출하고, 해당 얼굴영역 내에서 입 후보를 찾아 눈 후보와 입 후보의 구조적인 관계가 얼굴 구조와의 일치여부를 판단하여 얼굴영역을 검증하는 과정을 거친다. 이 방법은 눈을 찾아서 피부영역을 적응적으로 검출하기 때문에 기존의 얼굴탐지 방법들의 문제인 피부색상의 왜곡으로 인한 오검출을 해결하였다. 실험은 눈 탐지와, 피부 탐지, 입 탐지, 얼굴탐지에 대해 각각 수행하였다. 실험을 통하여 기존의 주요 방법들 보다 우수한 결과를 보였다.

• 한국산업융합학회 논문집
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• 제24권6_2호
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• pp.707-713
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• 2021

Symptoms of foot-and-mouth disease include fever and drooling a lot around the hoof, blisters in the mouth, poor appetite, blisters around the hoof, and blisters around the hoof. Research is underway on smart barns that remotely manage these symptoms through cameras. Visible light cameras can measure the condition of livestock such as blisters, but cannot measure body temperature. On the other hand, infrared thermal imaging cameras can measure body temperature, but it is difficult to measure the condition of livestock. In this paper, we propose an object detection system using deep learning-based livestock detection using visible and infrared thermal imaging composite camera modules for preemptive response

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.783-788
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• 2003

In this paper, we present a new approach to detect and recognize human face in the image from vision camera equipped on the mobile robot platform. Due to the mobility of camera platform, obtained facial image is small and pose-various. For this condition, new algorithm should cope with these constraints and can detect and recognize face in nearly real time. In detection step, ‘coarse to fine’ detection strategy is used. Firstly, region boundary including face is roughly located by dual ellipse templates of facial color and on this region, the locations of three main facial features- two eyes and mouth-are estimated. For this, simplified facial feature maps using characteristic chrominance are made out and candidate pixels are segmented as eye or mouth pixels group. These candidate facial features are verified whether the length and orientation of feature pairs are suitable for face geometry. In recognition step, pseudo-convex hull area of gray face image is defined which area includes feature triangle connecting two eyes and mouth. And random lattice line set are composed and laid on this convex hull area, and then 2D appearance of this area is represented. From these procedures, facial information of detected face is obtained and face DB images are similarly processed for each person class. Based on facial information of these areas, distance measure of match of lattice lines is calculated and face image is recognized using this measure as a classifier. This proposed detection and recognition algorithms overcome the constraints of previous approach [15], make real-time face detection and recognition possible, and guarantee the correct recognition irregardless of some pose variation of face. The usefulness at mobile robot application is demonstrated.