• The KIPS Transactions:PartB
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• v.9B no.6
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• pp.853-862
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• 2002

Face Detection can be defined as follows : Given a digitalized arbitrary or image sequence, the goal of face detection is to determine whether or not there is any human face in the image, and if present, return its location, direction, size, and so on. This technique is based on many applications such face recognition facial expression, head gesture and so on, and is one of important qualify factors. But face in an given image is considerably difficult because facial expression, pose, facial size, light conditions and so on change the overall appearance of faces, thereby making it difficult to detect them rapidly and exactly. Therefore, this paper proposes fast and exact face detection which overcomes some restrictions by using neural network. The proposed system can be face detection irrelevant to facial expression, background and pose rapidily. For this. face detection is performed by neural network and detection response time is shortened by reducing search region and decreasing calculation time of neural network. Reduced search region is accomplished by using skin color segment and frame difference. And neural network calculation time is decreased by reducing input vector sire of neural network. Principle Component Analysis (PCA) can reduce the dimension of data. Also, pose estimates in extracted facial image and eye region is located. This result enables to us more informations about face. The experiment measured success rate and process time using the Squared Mahalanobis distance. Both of still images and sequence images was experimented and in case of skin color segment, the result shows different success rate whether or not camera setting. Pose estimation experiments was carried out under same conditions and existence or nonexistence glasses shows different result in eye region detection. The experiment results show satisfactory detection rate and process time for real time system.

• Restorative Dentistry and Endodontics
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• v.22 no.2
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• pp.769-781
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• 1997

The tristimulus values of 180 extracted maxillary and mandibular anterior teeth were measured by colorimeter. And it were colnverted to Munsell color order system(Hue, Value, Chroma) and CIE $L^*a^*b^*$ color coordinates. The commonly used Vita, and Bioform shade guides, 2 composite resin shade guides(Prisma APH and Z-100), and a glass-ionomer shade guide(Fuji II) were compared with these teeth. At the middle facial surface, color distributions of teeth were Hue(0.56YR to 9.77Y), Value(2.46 to 7.9), and Chroma(0.14 to 2.02). And the aberaged values and standard deviations for $L^*a^*b^*$ were $63.18{\pm}10.44$, $1.11{\pm}1.66$, and $5.79{\pm}2.36$. The shade guide did not match well with the color space of the human teeth. Especially, the lacks of the Yellow-red Hues and higher values were prominent. Compare with other measurements, the Hues of the teeth measured in this study were broadly distributed(most of ranges in Y and YR were included), while the Value and chroma were shown to the lower.

• The Journal of Advanced Prosthodontics
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• v.7 no.6
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• pp.413-422
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• 2015

PURPOSE. To identify the most frequent natural tooth colors using the Easyshade Compact (Vita -Zahnfabrik) spectrophotometer on a sample of the Spanish population according to the 3D Master System. MATERIALS AND METHODS. The middle third of the facial surface of natural maxillary central incisors was measured with an Easyshade Compact spectrophotometer (Vita Zahnfabrik) in 1361 Caucasian Spanish participants aged between 16 and 89 years. Natural tooth color was recorded using the 3D Master System nomenclature. The program used for the present descriptive statistical analysis of the results was SAS 9.1.3. RESULTS. The results show that the most frequent dental color in the total sample studied is 3M1 (7.05%), followed by the intermediate shade 1M1.5 (6.91%) and 2L1.5 (6.02%). CONCLUSION. According to the research methodology used, and taking into account the limitations of this study, it can be proposed that the most frequent color among the Spanish population is 3M1; the most common lightness group is 2; the most frequent hue group according to the 3D Master System is M and the most frequent chroma group is 1.5.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.59-66
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• 2011

In this paper, we propose a face detection method based on color constancy and geometrical analysis. With the problem about the various colors of skin under scene illuminant, a color constancy method is applied to input images and geometrical analysis is used to detect face regions. At first, the candidates of face or hair are extracted from the image that a color constancy method is applied to, and are classified by some geometrical criterions. And then, face candidates which have some intersectional regions whose total is over a certain size, with hair candidates are selected as faces. Caltech Face DB was used to compare the performance of our method. Also, performance about scene illuminant was evaluated by images which have some illumination effects. The experiment results show that the proposed face detection method was applicable to various facial images because of high true-positive and low false-negative ration.

• 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㎓.

• The KIPS Transactions:PartB
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• v.17B no.6
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• pp.437-444
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• 2010

In this paper, we propose a method of analysing the relation between the patient's face color and his(her) kidney disease using image processing technology. This method is based on the ocular inspection which is one of the most famous diagnosis methods used in the oriental medical system. The way of processing and analysing the face image, which is for visualization and objectification of the color difference, is included. The objects are selected from the patients who suffer the kidney disease and use the hemodialyzer. Their facial images and clinical data are collected. From these data, we propose a hypothesis that the color of the patient's face is changed according to the patient's kidney state. At the same time, we present two algorithms of extracting the specific part of face which can identify the state of the patient's kidney and tracing the history of the color's change. This proposed method is evaluated through the practical experiments and their analysis.

• Journal of the Korea Society of Computer and Information
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• v.15 no.3
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• pp.27-35
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• 2010

Accurately extracting skin color regions is very important in various areas such as face recognition and tracking, facial expression recognition, adult image identification, health-care, and so forth. In this paper, we evaluate the performances of several skin color detection algorithms in indoor environments by changing the distance between the camera and the object as well as the background colors of the object. The distance is from 60cm to 120cm and the background colors are white, black, orange, pink, and yellow, respectively. The algorithms that we use for the performance evaluation are Peer algorithm, NNYUV, NNHSV, LutYUV, and Kimset algorithm. The experimental results show that NNHSV, NNYUV and LutYUV algorithm are stable, but the other algorithms are somewhat sensitive to the changes of backgrounds. As a result, we expect that the comparative experimental results of this paper will be used very effectively when developing a new skin color extraction algorithm which are very robust to dynamic real environments.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.299-302
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• 2001

The statistical analysis of the feature extraction and the neural networks are proposed to recognize a human face. In the preprocessing step, the normalized skin color map with Gaussian functions is employed to extract the region of face candidate. The feature information in the region of the face candidate is used to detect the face region. In the recognition step, as a tested, the 120 images of 10 persons are trained by the backpropagation algorithm. The images of each person are obtained from the various direction, pose, and facial expression. Input variables of the neural networks are the geometrical feature information and the feature information that comes from the eigenface spaces. The simulation results of$.$10 persons show that the proposed method yields high recognition rates.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.9
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• pp.822-826
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• 2001

The statistical analysis of the feature extraction and the neural networks are proposed to recognize a human face. In the preprocessing step, the normalized skin color map with Gaussian functions is employed to extract the region of face candidate. The feature information in the region of the face candidate is used to detect the face region. In the recognition step, as a tested, the 120 images of 10 persons are trained by the backpropagation algorithm. The images of each person are obtained from the various direction, pose, and facial expression. Input variables of the neural networks are the geometrical feature information and the feature information that comes from the eigenface spaces. The simulation results of 10 persons show that the proposed method yields high recognition rates.

• Journal of the Korean Society of Costume
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• v.61 no.2
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• pp.47-59
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• 2011

This study provides a systematic investigation about objective personal image consulting, tool development and image-making research by analyzing the status of the Korean image-consulting industry and education. For the research, we carried out literature surveys of books on image consulting and previous research reports. In particular, we surveyed image consulting businesses that have internet web sites, and educational institutes. The results of the survey are as follows: First, domestic image consulting businesses in Korea are investigated about 93 private companies and 4 associations. They do the image making, color consulting, and education for individuals and business. Second, professional image consulting education is carried out not only in the 93 private companies, but also in the continuing and professional studies for adults of 10 universities. Furthermore, more then 90 universities have specific academic programs related to the image consulting such as facial management, beauty coordination, cosmetology, stylists, fashion events, broadcasting stylists, and so on. Third, a typical image consulting job is the personal shoppers who assists VIP customers in department stores. Professionals and politicians have personal fashion stylists for their image making. Today, the job has expanded to public fashion therapist. Fourth, the contents of an image consulting education have appeared in similar industries and educations. These contents include fashion styles, personal color analysis, make-up, facial expressions, gestures, perfumes, accessories, etc. This study is based on research on the current Korean image-consulting industry, and will enable follow-up details to be implemented. using the basis of this study for a strategic self-image formation system.