• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.7 no.1
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• pp.55-60
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• 2014

In this paper, we proposed a method for face region extraction by skin-color hue, saturation and facial feature extraction in natural images. The proposed algorithm is composed of lighting correction and face detection process. In the lighting correction step, performing correction function for a lighting change. The face detection process extracts the area of skin color by calculating Euclidian distances to the input images using as characteristic vectors color and chroma in 20 skin color sample images. Eye detection using C element in the CMY color model and mouth detection using Q element in the YIQ color model for extracted candidate areas. Face area detected based on human face knowledge for extracted candidate areas. When an experiment was conducted with 10 natural images of face as input images, the method showed a face detection rate of 100%.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1960-1963
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• 2003

For applications such as video surveillance and human computer interface, we propose an efficiently integrated method to detect and track faces. Various visual cues are combined to the algorithm: motion, skin color, global appearance and facial pattern detection. The ICA (Independent Component Analysis)-SVM (Support Vector Machine based pattern detection is performed on the candidate region extracted by motion, color and global appearance information. Simultaneous execution of detection and short-term tracking also increases the rate and accuracy of detection. Experimental results show that our detection rate is 91％ with very few false alarms running at about 4 frames per second for 640 by 480 pixel images on a Pentium IV 1㎓.

• Journal of Korea Multimedia Society
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• v.8 no.7
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• pp.916-923
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• 2005

In recent times, mobile phones that play an important role in voice communication have became increasingly exciting due to the ability to transmit multimedia contents. However, user's communication cost and service usage fees for digital context exchange are still prohibitive. In this paper, we consider the task of transmitting a facial image in the context of mobile avatar generation. We present image compression as a useful technique to reduce service usage costs of data exchange in mobile communications. In view of this we propose an image compression algorithm that performs better than existing techniques. The suggested algorithm in this paper uses the location of significant coefficient on the wavelet image by detecting facial region as well as the spatial correlation between decomposed bands by wavelet transformation. The algorithm perform well and archives an efficient compression ratio. The proposed method recognizes location information of significant coefficient in advance, thus it is more suitable than existing general compression methods for mobile avatar generation systems.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.1
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• pp.104-114
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• 1999

This paper proposes an efficient method for the automatic generation of personalized 3D face model from color image sequence. To detect a robust facial region in a complex background, moving color detection technique based on he facial color distribution has been suggested. Color distribution and edge position information in the detected face region are used to extract the exact 31 facial feature points of the facial description parameter(FDP) proposed by MPEG-4 SNHC(Synthetic-Natural Hybrid Coding) adhoc group. Extracted feature points are then applied to the corresponding vertex points of the 3D generic face model composed of 1038 triangular mesh points. The personalized 3D face model can be generated automatically in less then 2 seconds on Pentium PC.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.44 no.1
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• pp.18-24
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• 2018

Objectives: Foreign bodies (FBs) account for 3.8% of all pathologies of the head and neck region, and approximately one third of them are missed on initial examination. Thus, FBs represent diagnostic challenges to maxillofacial surgeons, rendering it necessary to employ an appropriate imaging modality in suspected cases. Materials and Methods: In this cross-sectional study, five different materials, including wood, metal, glass, tooth and stone, were prepared in three sizes (0.5, 1, and 2 mm) and placed in three locations (soft tissue, air-filled space and bone surface) within a sheep's head (one day after death) and scanned by panoramic radiography, cone-beam computed tomography (CBCT), and ultrasonography (US) devices. The images were reviewed, and accuracy of the detection modalities was recorded. The data were analyzed statistically using the Kruskal-Wallis, Mann-Whitney U-test, Friedman, Wilcoxon signed-rank and kappa tests (P<0.05). Results: CBCT was more accurate in detection of FBs than panoramic radiography and US (P<0.001). Metal was the most visible FB in all of modalities. US was the most accurate technique for detecting wooden materials, and CBCT was the best modality for detecting all other materials, regardless of size or location (P<0.05). The detection accuracy of US was greater in soft tissue, while both CBCT and panoramic radiography had minimal accuracy in detection of FBs in soft tissue. Conclusion: CBCT was the most accurate detection modality for all the sizes, locations and compositions of FBs, except for the wooden materials. Therefore, we recommend CBCT as the gold standard of imaging for detecting FBs in the maxillofacial region.

• 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%.

• JSTS:Journal of Semiconductor Technology and Science
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• v.13 no.1
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• pp.34-42
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• 2013

Human faces have been broadly studied in digital image and video processing fields. An appearance-based method, the adaptive boosting learning algorithm using integral image representations has been successfully employed for face detection, taking advantage of the feature extraction's low computational complexity. In this paper, we propose a face-detection postprocessing method that equalizes instantaneous facial regions in an efficient hardware architecture for use in real-time multimedia applications. The proposed system requires low hardware resources and exhibits robust performance in terms of the movements, zooming, and classification of faces. A series of experimental results obtained using video sequences collected under dynamic conditions are discussed.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.3
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• pp.23-35
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• 2002

Gaze detection is to locate the position on a monitor screen where a user is looking. In our work, we implement it with a computer vision system setting a single camera above a monitor and a user moves (rotates and/or translates) his face to gaze at a different position on the monitor. To detect the gaze position, we locate facial region and facial features(both eyes, nostrils and lip corners) automatically in 2D camera images. From the movement of feature points detected in starting images, we can compute the initial 3D positions of those features by camera calibration and parameter estimation algorithm. Then, when a user moves(rotates and/or translates) his face in order to gaze at one position on a monitor, the moved 3D positions of those features can be computed from 3D rotation and translation estimation and affine transform. Finally, the gaze position on a monitor is computed from the normal vector of the plane determined by those moved 3D positions of features. As experimental results, we can obtain the gaze position on a monitor(19inches) and the gaze position accuracy between the computed positions and the real ones is about 2.01 inches of RMS error.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.36T no.3
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• pp.26-31
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• 1999

In this paper, we propose a facial characteristic detection algorithm based on knowledge and object segmentation method for image communication. In this algorithm, under the condition of the same lumination and distance from the fixed video camera to human face, we capture input images of 256 $\times$ 256 of gray scale 256 level and then remove the noise using the Gaussian filter. Two images are captured with a video camera, One contains the human face; the other contains only background region without including a face. And then we get a differential image between two images. After removing noise of the differential image by eroding End dilating, divide background image into a facial image. We separate eyes, ears, a nose and a mouth after searching the edge component in the facial image. From simulation results, we have verified the efficiency of the Proposed algorithm.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.298-300
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• 2003

동영상이나 정지영상에서 사람의 얼굴을 검출 및 인식을 하는 여러 가지 알고리즘이 소개되고 있다. 본 논문에서는 신경망(Neural Network)과 얼굴의 기하학적 특징 중에 하나인 눈과 입을 사용하여 얼굴 영역을 추출하는 방법을 사용한다 신경망은 얼굴 인식을 비롯한 여러 분야에서 쓰이는 좋은 방법 중의 하나 이지만 신경망이 가지고 있는 특성상 많은 오차를 가질 수 있기 때문에 얼굴을 구성하고 있는 요소인 눈과 입을 사용해서 오차를 제거하는 방법을 제안한다.