• Journal of the Institute of Convergence Signal Processing
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• v.6 no.1
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• pp.15-22
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• 2005

In this paper, we propose a face recognition system by using the CCD color image. We first get the face candidate image by using YCbCr color model and adaptive skin color information. And we use it initial curve of active contour model to extract face region. We use the Eye map and mouth map using color information for extracting facial feature from the face image. To obtain center point of Log-polar image, we use extracted facial feature from the face image. In order to obtain feature vectors, we use extracted coefficients from DCT and wavelet transform. To show the validity of the proposed method, we performed a face recognition using neural network with BP learning algorithm. Experimental results show that the proposed method is robuster with higher recogntion rate than the conventional method for the rotation and scale variant.

• The KIPS Transactions:PartB
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• v.16B no.4
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• pp.299-308
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• 2009

AAM(Active Appearance Model) is an algorithm to extract face feature points with statistical models of shape and texture information based on PCA(Principal Component Analysis). This method is widely used for face recognition, face modeling and expression recognition. However, the detection performance of AAM algorithm is sensitive to initial value and the AAM method has the problem that detection error is increased when an input image is quite different from training data. Especially, the algorithm shows high accuracy in case of closed lips but the detection error is increased in case of opened lips and deformed lips according to the facial expression of user. To solve these problems, we propose the improved AAM algorithm using lip feature points which is extracted based on a new lip detection algorithm. In this paper, we select a searching region based on the face feature points which are detected by AAM algorithm. And lip corner points are extracted by using Canny edge detection and histogram projection method in the selected searching region. Then, lip region is accurately detected by combining color and edge information of lip in the searching region which is adjusted based on the position of the detected lip corners. Based on that, the accuracy and processing speed of lip detection are improved. Experimental results showed that the RMS(Root Mean Square) error of the proposed method was reduced as much as 4.21 pixels compared to that only using AAM algorithm.

• Journal of the Korea Computer Graphics Society
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• v.24 no.2
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• pp.1-9
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• 2018

In this paper, we propose a method to restore corrupted black and white facial images to color. Previous studies have shown that when coloring damaged black and white photographs, such as old ID photographs, the area around the damaged area is often incorrectly colored. To solve this problem, this paper proposes a method of restoring the damaged area of input photo first and then performing colorization based on the result. The proposed method consists of two steps: BEGAN (Boundary Equivalent Generative Adversarial Networks) model based restoration and CNN (Convolutional Neural Network) based coloring. Our method uses the BEGAN model, which enables a clearer and higher resolution image restoration than the existing methods using the DCGAN (Deep Convolutional Generative Adversarial Networks) model for image restoration, and performs colorization based on the restored black and white image. Finally, we confirmed that the experimental results of various types of facial images and masks can show realistic color restoration results in many cases compared with the previous studies.

• The korean journal of orthodontics
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• v.46 no.4
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• pp.189-198
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• 2016

Objective: The purpose of this study was to analyze stress distributions in the roots, periodontal ligaments (PDLs), and bones around cylindrical and tapered miniscrews inserted at different angles using a finite element analysis. Methods: We created a three-dimensional (3D) maxilla model of a dentition with extracted first premolars and used 2 types of miniscrews (tapered and cylindrical) with 1.45-mm diameters and 8-mm lengths. The miniscrews were inserted at $30^{\circ}$, $60^{\circ}$, and $90^{\circ}$ angles with respect to the bone surface. A simulated horizontal orthodontic force of 2 N was applied to the miniscrew heads. Then, the stress distributions, magnitudes during miniscrew placement, and force applications were analyzed with a 3D finite element analysis. Results: Stresses were primarily absorbed by cortical bone. Moreover, very little stress was transmitted to the roots, PDLs, and cancellous bone. During cylindrical miniscrew insertion, the maximum von Mises stress increased as insertion angle decreased. Tapered miniscrews exhibited greater maximum von Mises stress than cylindrical miniscrews. During force application, maximum von Mises stresses increased in both groups as insertion angles decreased. Conclusions: For both cylindrical and tapered miniscrew designs, placement as perpendicular to the bone surface as possible is recommended to reduce stress in the surrounding bone.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.1
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• pp.1-7
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• 2006

In this paper, adaptive Facial Emotional Recognition system based on Gabor Wavelet Neural Network, considering six feature Points in face image to extract specific features of facial expression, is proposed. Levenberg-Marquardt-based training methodology is used to formulate initial network, including feature extraction stage. Therefore, heuristics in determining feature extraction process can be excluded. Moreover, to make an adaptive network for new user, Q-learning which has enhanced reward function and unsupervised fuzzy neural network model are used. Q-learning enables the system to ge optimal Gabor filters' sets which are capable of obtaining separable features, and Fuzzy Neural Network enables it to adapt to the user's change. Therefore, proposed system has a good on-line adaptation capability, meaning that it can trace the change of user's face continuously.

• Journal of the Korea Computer Graphics Society
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• v.23 no.5
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• pp.19-27
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• 2017

In this paper, we propose an automatic segmentation method of the mandible using shape-constrained information in cranio-maxillo-facial CBCT images. The proposed method consists of the following two steps. First, the mandible segmentation based on the global shape information is performed through the statistical shape model generated using the MDCT images. Second, improvement of mandible segmentation is performed considering the local shape information and intensity characteristics of the mandible. To evaluate the performance of the proposed method, the proposed method was evaluated qualitatively and quantitatively based on the results of manual segmentation by expert. Experimental results show that the Dice Similarity Coefficient of the proposed method was 95.64% and 90.97%, respectively, in the mandible body region including the narrow region of large curvature and the condyle region with large positional variance.

• Journal of Sasang Constitutional Medicine
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• v.23 no.2
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• pp.194-207
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• 2011

1. Objectives: This study is about a development of Sasang constitutional classification algorithm using facial information. 2. Methods: We analysed the datum of middle aged (20~48) women collected by multi-center researchers in 2007. And this study analysed the data of the measurement of the face by 3D-AFRA (3-Dimensional Automatic Face Recognition Apparatus) and the items of impression by SDQ. We used multiple comparison, exploratory discriminant analysis and clinical decision to select optimal 3D facial variables which will be input in discriminant analysis model. And we used univariate F values and stepwise discriminant function analysis to choose best impression variables. 3. Results and Conclusions: In this study, derived discriminant function's explanation power was 39% in female group. Diagnostic accuracy rate was 66.0% in female group. And in test sample, Sasang constitutional diagnostic accuracy rate was 56.9%. In this process we could help improve the objectification of Sasang constitution diagnosis.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.1
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• pp.163-170
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• 2022

This paper introduces a method of extracting facial features due to unrefined inputs in real life and improving the problem of not guaranteeing the ideal performance and speed of the object recognition model through a storage algorithm through weight summation. Many facial recognition processes ensure accuracy in ideal situations, but the problem of not being able to cope with numerous biases that can occur in real life is drawing attention, which may soon lead to serious problems in the face recognition process closely related to security. This paper presents a method of quickly and accurately recognizing faces in real time by comparing feature points extracted as input with a small number of feature points that are not overfit to multiple biases, using that various variables such as picture composition eventually take an average form.

• The Journal of Advanced Prosthodontics
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• v.15 no.1
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• pp.22-32
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• 2023

PURPOSE. Digital technology has enabled improvements in the fitting accuracy of denture bases via milling techniques. The aim of this study was to evaluate the trueness and precision of digital and analog techniques for manufacturing complete dentures (CDs). MATERIALS AND METHODS. Sixty identical CDs were manufactured using different production protocols. Digital and analog technologies were compared using the reference geometric approach, and the Δ-error values of eight areas of interest (AOI) were calculated. For each AOI, a precise number of measurement points was selected according to sensitivity analyses to compare the Δ-error of trueness and precision between the original model and manufactured prosthesis. Three types of statistical analysis were performed: to calculate the intergroup cumulative difference among the three protocols, the intergroup among the AOIs, and the intragroup difference among AOIs. RESULTS. There was a statistically significant difference between the dentures made using the oversize process and injection molding process (P < .001), but no significant difference between the other two manufacturing methods (P = .1227). There was also a statistically significant difference between the dentures made using the monolithic process and the other two processes for all AOIs (P = .0061), but there was no significant difference between the other two processes (P = 1). Within each group, significant differences among the AOIs were observed. CONCLUSION. The monolithic process yielded better results, in terms of accuracy (trueness and precision), than the other groups, although all three processes led to dentures with Δ-error values well within the clinical tolerance limit.

• Journal of Broadcast Engineering
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• v.28 no.2
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• pp.238-241
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• 2023

Recently deep learning models are widely used for various tasks such as facial recognition and face editing. Their training process often involves a dataset with imbalanced age distribution. It is because some age groups (teenagers and middle age) are more socially active and tends to have more data compared to the less socially active age groups (children and elderly). This imbalanced age distribution may negatively impact the deep learning training process or the model performance when tested against those age groups with less data. To this end, we propose an age-controllable face synthesis technique using a feature decomposition to classify age from facial images which can be utilized to synthesize novel data to balance out the age distribution. We perform extensive qualitative and quantitative evaluation on our proposed technique using the FFHQ dataset and we show that our method has better performance than existing method.