• Journal of the Korea Society of Computer and Information
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• v.16 no.10
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• pp.93-100
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• 2011

The necessity of research on extracting information of face and facial components in animation characters have been increasing since they can effectively express the emotion and personality of characters. In this paper, we introduce a method to extract face and facial components of animation characters by defining a mesh model adequate for characters and by using dominant colors. The suggested algorithm first generates a mesh model for animation characters, and extracts dominant colors for face and facial components by adapting the mesh model to the face of a model character. Then, using the dominant colors, we extract candidate areas of the face and facial components from input images and verify if the extracted areas are real face or facial components by means of color similarity measure. The experimental results show that our method can reliably detect face and facial components of animation characters.

• The Journal of Korean Academy of Prosthodontics
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• v.33 no.1
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• pp.75-84
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• 1995

This study was designed as a reference of vertical dimension in prosthetic treatment. The author analyzed six facial measurements, namely, (1) the height of lower face at maximum intercuspal position, (2) the height of lower face at resting position, (3) midface, (4) external ear and lateral wall of orbit, (5) interpupillary distance, (6) distance between pupil and mouth in the 100 Won-kwang Univ. Dental collage students(50 : male, 50 : female), who have normal occlusion, no posterior prosthesis, no experience of orthodontic treatment, and no deformity of facial soft tissue and no temporomandibular dysfunction. The results of this study were as follows : 1. The length of midface was shortest and the inter-pupillary distance was longest in both male and female. 2. The length difference with the length of midface and lower face at maximum intercuspal position was 5.64mm in male and 2.23mm in female, so the lower face was longer, 3. The facial measuring component, similar to lower face at maximum intercuspation, was the length of between medial wall of external ear and lateral wall of orbit. It's difference was 1.3mm in male, 1.77mm in female, and the lower face was shorter. 4. The difference of lower facial length in resting position and maximum intercuspation was 2.48mm in male, 2.24mm in female, the length of resting position was therefore longer. 5. The most clost correlation with the height of maximum intercuspal positioning lower face was resting lower face in both groups.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.9
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• pp.1674-1680
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• 2017

In this paper, an embedded system for face authentication, which exploits high-dimensional local binary pattern (LBP) descriptor and joint Bayesian algorithm, is proposed. We also present a feasible embedded system for the proposed algorithm implemented with a Raspberry Pi 3 model B. Computer simulation for performance evaluation of the presented face authentication algorithm is carried out using a face database of 500 persons. The face data of a person consist of 2 images, one for training and the other for test. As performance measures, we exploit score distribution and face authentication time with respect to the dimensions of principal component analysis (PCA). As a result, it is confirmed that an embedded system having a good face authentication performance can be implemented with a relatively low cost under an optimized embedded environment.

• Journal of muscle and joint health
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• v.27 no.1
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• pp.31-40
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• 2020

Purpose: This study was done to examine the effect of a multi-component cessation program on bone union by comparing the union time between the experimental group and the control group. Methods: A non-equivalent control group posttest design was used. The subjects were 33 patients in the experimental group and 33 patients in the control group, 66 patients in total. The subjects of the experimental group were provided with a face-to-face multi-component smoking cessation program. After the discharge, telephone consultation was provided once a week for 10 weeks. Results: Bone union time was 51.6±10.9 days in the experimental group and 60.9±13.83 days in the control group (p=.003). Among 33 subjects who participated in the smoking cessation program, the average union period of the participants who succeeded in quitting smoking was 44.56 days, the participants who reduced smoking were 50.67 days, and failed to quit smoking group was 60.11 days (p=.006). Conclusion: This study indicated the importance of smoking cessation in patients with fracture and the decrease in the union time by providing smoking cessation education. If the multi-component smoking cessation program is used as a nursing intervention in clinical practice, it will be effective for bone union by increasing the smoking cessation rate of patients with fracture.

• Journal of Sasang Constitutional Medicine
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• v.8 no.1
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• pp.101-186
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• 1996

The clinical application of constitutional Diagnosis is the most important part of Sasang constitutional medicine. It has been studied in various way. However, the study of morphologic characteristics on the face is applied for the first time. For quantitative analysis of the correlation between the sasang constitution and the shape of the face, the head-facial part of 170 cases were measured by Martin's measurement and analysis of a) the measurement value of height and the component ratio from the Gnathion to each part of face by constitution. b) the measurement value of depth and the component ratio from T-projected to each part of the face by constitution. c) the measurement value of breadth and component ratio between each parts of the facial breadth by constitution. d) the ratio of square on every part of face by constitution. e) the characteristics on each part of the face by constitution. f) the contour line of the forehead. g) the result of discriminant analysis about the constitution. Authors obtained the results from the study as follows; 1. The characteristics of Taeum-IN (1) The measurement value of Height, Breadth, T-Projected had a tendency to maximum value in general. (2) The value of lower opthal height and the square of lower opthal part was maximum. (3) The value of Pronasal T-projected length and Subnasal T-projected length was minimum, so Taeum-In has characteristics of depression in middle face, nasal part. (4) In the ratio of Breadth, T-Projected, T-Projected was minimum. (5) It was maximum that the square of nose, Alare, Middle face, Lower face and it was minimum that the square of eye. The square of nose, Alare, Middle facc, Lower face was maximum and the square of eye was minimum. (6) The curvature of the eyebrow was minimum. (7) The projection of jaw (Pogonion T-projection length) was maximum. (8) The breadth of eye was minimum. (9) There was a tendency that the projection of the forehead to the right in general. 2. The characteristics of Soeum-In (1) In all cases of projected length the measurement value was minimum. (2) The value of lower opthal height and the square of lower opthal part was minimum. (3) By the Pupulare T-projected length, the value of Pronasal T-projected length and Subnasal T-projected length was minimum, so the Soeum In's face shape is flat. (4) The square of eye, mouth, forehead was maximum and the square of nose, Alare, Middle face, Lower face was minimum. (5) The curvature of the eyebrow was maximum. (6) The projection of mouth was minimum. (7) The jaw was flat. (8) The breadth of eye was maximum. (9) There was a tendency that the projection of the forehead to the left in general. 3. The characteristics of Soyang-In. (1) In most cases of 고경 length the measurement value was minimum. (2) By the Pupulare T-projected length, each ratio of projected length was maximum, so the Soyang-In's face shape has many protrusions (3) In the ratio of Breadth, T-Projected, T-Projected was maximum. (4) The square of mouth was minimum. (5) The inclination of the forehead was minimum. (6) The projection of mouth was maximum. (7) The breadth of eye was minimum. (8) There was a tendency that the projection of the forehead to the left in general. (9) The middle face was protruded. 4. Discriminant about the constitution. According to the result of discriminant, the accuracy probability of discriminant was 85.58% in total and Taeum-In was 90.5%, Soeum-In was 70.8%, Soyang-In was 89.5%. The accuracy probability of discriminant about 3 constitutional group increased by 49.03% than the accident probility 36.55% 5. Suggestion (1) The study which gather and analysis the data should be continued. (2) The study which subdivide the characteristics of each part of the face by the constitution should be continued. (3) The analysis method about Moire should be supplement. (4) The study about the morphologic characteristics of the whole body should be continued. (5) Computer program of constitution diagnosis should be developed. (6) To increase utility of this method, the measurement should be automation.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.3
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• pp.95-101
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• 2006

A face detection plays an important role in face recognition, video surveillance, and human computer interaction. In this paper, we propose a progressive threshold method to detect human faces in real time. The consecutive face images are acquired from camera and transformed into YCbCr color space images. The skin color of the input images are separated using a skin color filter in the YCbCr color space and some candidated face areas are decided by connected component analysis. The intensity equalization is performed to avoid the effect of many circumstances and an arbitrary threshold value is applied to get binary images. The eye area can be detected because the area is clearly distinguished from others in the binary image progressive threshold method searches for an optimal eye area by progressively increasing threshold from low values. After progressive thresholding, the eye area is normalized and verified by back propagation algorithm to finalize the face detection.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.1
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• pp.17-23
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• 2005

In this paper, we propose face recognition method using embedded data in super states segmentalized that is specification region exist to face region, hair, forehead, eyes, ears, nose, mouth, and chin. Proposed method defines super states that is specification area in normalized size (92×112), and embedded data that is extract internal factor in super states segmentalized achieve face recognition by PCA algorithm. Proposed method can receive specification data that is less in proposed image's size (92×112) because do orignal image to learn embedded data not to do all loaming. And Showed face recognition rate in image of 92×112 size averagely 99.05%, step 1 99.05%, step 2 98.93%, step 3 98.54%, step 4 97.85%. Therefore, method that is proposed through an experiment showed that the processing speed improves as well as reduce existing face image's information.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.1
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• pp.82-89
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• 2015

The researches of image recognition have been processed traditionally. Especially, face recognition technology has been received attractions with advance and applied to various areas according as camera sensor embedded into many devices such as smart phone. In this study, we design and develop a feature vector generation technique of face for making animation caricatures using methods for face detection which are previous stage of face recognition. At first, we detect both face region and detailed eye region of component element by Viola&Johns's realtime detection method which are called as ROI(Region Of Interest). And then, we generate feature vectors of eye region by utilizing factors as opposed to the periphery and by using appearance information of eye. At this point, we focus on the embedded information in many color spaces to overcome the problems which can be occurred by using one color space. We propose a feature vector generation method using information from many color spaces. Finally, we experiment the test of feature vector generation by the proposed method with enough quantity of sample picture data and evaluate the proposed method for factors of estimating performance such as error rate, accuracy and generation time.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.12
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• pp.71-83
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• 1996

This paper describes facial component detection and skew correction algorithm for face recognition. We use a priori knowledge and models about isolated regions to detect eye location from the face image captured in natural office environments. The relations between human face components are represented by several rules. We adopt an edge detection algorithm using sobel mask and 8-connected labelling algorith using array pointers. A labeled image has many isolated components. initially, the eye size rules are used. Eye size rules are not affected much by irregular input image conditions. Eye size rules size, and limited in the ratio between gorizontal and vertical sizes. By the eye size rule, 2 ~ 16 candidate eye components can be detected. Next, candidate eye parirs are verified by the information of location and shape, and one eye pair location is decided using face models about eye and eyebrow. Once we extract eye regions, we connect the center points of the two eyes and calculate the angle between them. Then we rotate the face to compensate for the angle so that the two eyes on a horizontal line. We tested 120 input images form 40 people, and achieved 91.7% success rate using eye size rules and face model. The main reasons of the 8.3% failure are due to components adjacent to eyes such as eyebrows. To detect facial components from the failed images, we are developing a mouth region processing module.

• Journal of KIISE:Software and Applications
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• v.31 no.2
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• pp.213-223
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• 2004

In this paper, we propose a new face detection method for real-time applications. It is based on the template-matching and appearance-based method. At first, we apply Min-max normalization with histogram equalization to the input image according to the variation of intensity. By applying the PCA transform to both the input image and template, PC components are obtained and they are applied to the LDA transform. Then, we estimate the distances between the input image and template, and we select one region which has the smallest distance. SVM is used for final decision whether the candidate face region is a real face or not. Since we detect a face region not the full region but within the $\pm$12 search window, our method shows a good speed and detection rate. Through the experiments with 6 category input videos, our algorithm shows the better performance than the existing methods that use only the PCA transform. and the PCA and LDA transform.