• Journal of Sasang Constitutional Medicine
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• v.19 no.2
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• pp.30-39
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• 2007

1. Objectives The Face is an important standard for the classification of Sasang Constitution. We are developing 3D Automatic Face Recognition Apparatus(3D-AFRA) to analyse the facial characteristics. This apparatus show us 3D image and data of man's face and measure facial figure data. So we should examine the figure restoration error of 3D Automatic Fare Recognition Apparatus(3D-AFRA) in hardware Error Analysis. 2. Methods We scanned Face status by using 3D Automatic Face Recognition Apparatus(3D-AFRA). And also we scanned Face status by using laser scanner(vivid 9i). We compared facial shape data be restored by 3D Automatic Face Recognition Apparatus(3D-AFRA) with facial shape data that be restorated by 3D laser scanner. And we analysed the average error and the maximum error of two data. 3. Results and Conclusions In frontal face, the average error was 0.48mm. and the maximum error was 4.60mm. In whole face, the average error of was 0.99mm. And the maximum error was 6.64mm. In conclusion, We assessed that accuracy of 3D Automatic Face Recognition Apparatus(3D-AFRA) is considerably good.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.2
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• pp.321-327
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• 1999

In this progressed super-impose individual recognition system, the photograph of a skull was caught by CCD-camcoder with the MPEG, and an ante-mortem photograph was read by scanner. These two images were processed and superimposed using horizontal angle and vertical angle of face using the forensic dental medicine theory. The enhancement of super-impose individual recognition by anatomical references was performed on the two superimposed images of the same angle using the facial triangle and histogram analysis scheme.

• Journal of Sasang Constitutional Medicine
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• v.19 no.1
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• pp.50-59
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• 2007

1. Objectives The Face is an important standard for the classification of Sasang Contitutions. Now We are developing 3D Automatic Face Recognition Apparatus to analyse the facial characteristics. This apparatus show us 3D image of man's face and measure facial figure. We should examine accuracy of position recognition in 3D Automatic Face Recognition Apparatus(3D-AFRA). 2. Methods We took a photograph of Face status with Land Mark by using 3D-AFRA. And We scanned Face status by using laser scanner(vivid 700). We analysed error average of distance between Facial Definition Points. We compare the average between using 3D-AFRA and using laser scanner. So We examined the accuracy of position recognition in 3D-AFRA at indirectly. 3. Results and Conclusions The error average of distance between Right Pupil and The Other Facial Definition Points is 0.5140mm and the error average of distance between Left Pupil and The Other Facial Definition Points is 0.5949mm in frontal image of face. The error average of distance between Left Pupil and The Other Facial Definition Points is 0.5308mm and the error average of distance between Left Tragion and The Other Facial Definition Points is 0.6529mm in laterall image of face. In conclusion, We assessed that accuracy of position recognition in 3D-AFRA is considerably good.

• Journal of Biomedical Engineering Research
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• v.37 no.2
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• pp.68-74
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• 2016

In this study, we investigated the rotational characteristics which were comprised of directionality and linearity of target registration error (TRE) as a study in advance to enhance the accuracy of contour-based registration in neuronavigation. For the experiment, two rigid head phantoms that have different faces with specially designed target frame fixed inside of the phantoms were used. Three-dimensional coordinates of facial surface point cloud and target point of the phantoms were acquired using computed tomography (CT) and 3D scanner. Iterative closest point (ICP) method was used for registration of two different point cloud and the directionality and linearity of TRE in overall head were calculated by using 3D position of targets after registration. As a result, it was represented that TRE had consistent direction in overall head region and was increased in linear fashion as distance from facial surface, but did not show high linearity. These results indicated that it is possible for decrease TRE by controlling orientation of facial surface point cloud acquired from scanner, and the prediction of TRE from surface registration error can decrease the registration accuracy in lesion. In the further studies, we have to develop the contour-based registration method for improvement of accuracy by considering rotational characteristics of TRE.

• Archives of Plastic Surgery
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• v.35 no.2
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• pp.201-204
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• 2008

Purpose: Now the CT scanner and PACS program proved to be an excellent instrument for detection and localization of most facial foreign bodies above certain minimum levels of detectability. The severity of injury in penetrating trauma on the face is often underestimated in physical examination. Wood, with its porous consistency and organic nature, provides a good medium for microbial agents. This is a report of our recent experience with wooden foreign bodies in the parotid gland imaged with CT. Methods: A 9-year-old boy was referred for evaluation of possible retained foreign body within his face. One day earlier, he had fallen, face down approximately 1 miter onto ground. He had subsequently undergone an exploration of his right parotido-masseteric area at an outside hospital with repair of a right facial laceration. Enhanced 2 mm axial and coronal CT scans were obtained through the face. Axial and coronal CT images were obtained with a General Electric(Milwaukee, Wis) 9800 CT scanner at 130 kV, 90 mA, with a 2 mm section thickness. Results: We finally decided the linear "gas" attenuation was a foreign body because of its linear configuration, which did not conform to that of an anatomic structure, and on the basis of articles that described a wood foreign body in the orbit as having the appearance of air. We found that wood was hypoattenuating($-464{\pm}27HU$). Conclusion: We recommend this type of software program for CT scanning for any patient with an injury on the face in which a foreign body is suspected.

• Journal of the korean academy of Pediatric Dentistry
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• v.47 no.1
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• pp.17-24
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• 2020

The purpose of this study was to evaluate the accuracy and precision of the three-dimensional (3D) imaging system of children's facial soft tissue by comparing linear measurements. The subjects of the study were 15 children between the ages of 7 and 12. Twenty-three landmarks were pointed on the face of each subject and 16 linear measurements were directly obtained 2 times using an electronic caliper. Two sets of 3D facial images were made by the 3D scanner. The same 16 measurements were obtained on each 3D image. In the accuracy test, the total average difference was 0.9 mm. The precision of 3D photogrammetry was almost equivalent to that of direct measurement. Thus, 3D photogrammetry by the 3D scanner in children had sufficient accuracy and precision to be used in clinical setting. However, the 3D imaging system requires the subject's compliance for exact images. If the clinicians provide specific instructions to children while obtaining 3D images, the 3D device is useful for investigating children's facial growth and development. Also the device can be a valuable tool for evaluating the results of orthodontic and orthopedic treatments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.3
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• pp.427-433
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• 2001

This paper proposes a web-based 3 dimensional face modeling system that makes a realistic facial model efficiently without any 30 scanner or camera that uses in the traditional methods. Without expensive image-input equipments, we can easily create 3B models only using front and side images. The system is available to make 3D facial models as we connect to the facial modeling server on the WWW which is independent from specific platforms and softwares. This system will be implemented using Java 3D API, which includes the functions and conveniences of developed graphic libraries. It is a Client/server architecture which consists of user connection module and 3D facial model creating module. Clients connect with the facial modeling server, input two facial photographic images, detects the feature points, and then create a 3D facial model modifying generic facial model with the points according to the procedures using only the web browser.

• Journal of Oriental Medical Thermology
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• v.5 no.1
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• pp.78-86
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• 2006

Objectives: To examine any potential relationships between the types of alopecia and the facial heat distribution in patients with alopecia Methods: 183 patients with alopecia participated in this study to provide facial heat distribution measured by the Infrared Thermography Scanner (ITS, Nec San-ei Instruments Ltd, Japan). The thermography scan was used in a light-and heat-protected room after 20 minutes’of resting period. 1.5m of distance maintained between the patients and ITS. Results: Specificity in the type of facial heat distribution was found as follow. 1. Types of facial heat distribution can be classified as T-type and diffused patterns. 2. There was a significant difference in the pattern of facial heat distribution among different types of alopecia (p=0.002): facial heat distribution appeared T-type in Androgenic Alopecia, Alopecia Areata, and Telogen Effluvium (71.3%, 85.7%, 70.4%), whereas diffused pattern was dominant in Seborrheic Alopecia(55.6%). 3. There was a significant difference in the pattern of facialheat distribution between men and women (p<0.001): While the T-type and diffused type were equally appeared in men (50.6%: 49.4%), T-type was dominant in women (88.0% vs. 12.0%). Conclusions: We conclude that the pattern of facial heat distribution differs depends on the types of alopecia and gender. These differences may provide useful information for the diagnosis and clinical therapy for this population.

• Archives of Craniofacial Surgery
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• v.16 no.1
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• pp.1-10
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• 2015

Facial symmetry is an important component of attractiveness. However, functional symmetry is favorable to aesthetic symmetry. In addition, fluctuating asymmetry is more natural and common, even if patients find such asymmetry to be noticeable. However, fluctuating asymmetry remains difficult to define. Several studies have shown that a certain level of asymmetry could generate an unfavorable image. A natural profile is favorable to perfect mirror-image profile, and images with canting and differences less than $3^{\circ}-4^{\circ}$ and 3-4 mm, respectively, are generally not recognized as asymmetry. In this study, a questionnaire survey among 434 medical students was used to evaluate photos of Asian women. The students preferred original images over mirror images. Facial asymmetry was noticed when the canting and difference were more than $3^{\circ}$ and 3 mm, respectively. When a certain level of asymmetry is recognizable, correcting it can help to improve social life and human relationships. Prior to any operation, the anatomical component for noticeable asymmetry should be understood, which can be divided into hard tissues and soft tissue. For diagnosis, two-and three-dimensional (3D) photogrammetry and radiometry are used, including photography, laser scanner, cephalometry, and 3D computed tomography.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.748-753
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• 2012

In this paper, Face recognition algorithm is designed based on optimized pRBFNNs pattern classifier using three-dimensional scanner. Generally two-dimensional image-based face recognition system enables us to extract the facial features using gray-level of images. The environmental variation parameters such as natural sunlight, artificial light and face pose lead to the deterioration of the performance of the system. In this paper, the proposed face recognition algorithm is designed by using three-dimensional scanner to overcome the drawback of two-dimensional face recognition system. First face shape is scanned using three-dimensional scanner and then the pose of scanned face is converted to front image through pose compensation process. Secondly, data with face depth is extracted using point signature method. Finally, the recognition performance is confirmed by using the optimized pRBFNNs for solving high-dimensional pattern recognition problems.