• Journal of Sasang Constitutional Medicine
• /
• v.19 no.2
• /
• pp.30-39
• /
• 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 Sasang Constitutional Medicine
• /
• v.20 no.1
• /
• pp.34-41
• /
• 2008

1. Objectives We had been developing a 3D Automatic Face Recognition Apparatus (3D-AFRA) in order to evaluate the external appearances with more objectivity. This apparatus provides a 3D image and numerical data on facial configuration, and this study aims to evaluate the accuracy of 3D-AFRA recognition. 2. Methods Each scanned pictures were pointed with the 3D Automatic Face Recognition Apparatus(3D-AFRA). And the results were compared with data pointed pictures with manual. And we analysed the difference between Automatic and manual by paired -test. 3. Results and conclusions In frontal face, the P-value was more than 0.05. In conclusion, We assessed that accuracy of recognition of 3D Automatic Face Recognition Apparatus(3D-AFRA) is considerably good. But we should develop methods of measurement for lateral face and indistinct points of frontal face.

• Journal of Sasang Constitutional Medicine
• /
• v.19 no.3
• /
• pp.51-61
• /
• 2007

1. Objectives The Face is an important standard for the classification of Sasang Constitutions. 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 Measurement of Facial Figure data error of 3D Automatic Face Recognition Apparatus(3D-AFRA) in Software Error Analysis. 2. Methods We scanned face status by using 3D Automatic Face Recognition Apparatus(3D-AFRA). And we measured lengths Between Facial Definition Parameters of facial figure data by Facial Measurement program. 2.1 Repeatability test We measured lengths Between Facial Definition Parameters of facial figure data restored by 3D-AFRA by Facial Measurement program 10 times. Then we compared 10 results each other for repeatability test. 2.2 Measurement error test We measured lengths Between Facial Definition Parameters of facial figure data by two different measurement program that are Facial Measurement program and Rapidform2006. At measuring lengths Between Facial Definition Parameters, we uses two measurement way. The one is straight line measurement, the other is curved line measurement. Then we compared results measured by Facial Measurement program with results measured by Rapidform2006. 3. Results and Conclusions In repeatability test, standard deviation of results is 0.084-0.450mm. And in straight line measurement error test, the average error 0.0582mm, and the maximum error was 0.28mm. In curved line measurement error test, the average error 0.413mm, and the maximum error was 1.53mm. In conclusion, we assessed that the accuracy and repeatability of Facial Measurement program is considerably good. From now on we complement accuracy of 3D-AFRA in Hardware and Software.

• Journal of Sasang Constitutional Medicine
• /
• v.19 no.1
• /
• pp.50-59
• /
• 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 Sasang Constitutional Medicine
• /
• v.19 no.2
• /
• pp.22-29
• /
• 2007

1. Objectives Sasang Contitutional Medicine, a part of the traditional Korean medical lore, treats illness through a constitutional typing system that categorizespeople into four constitutional types. A few of the important criteria for differentiating the constitutional types are external appearances, inner state of mind, and pathological patterns. We had been developing a 3D Automatic Face Recognition Apparatus (3D-AFRA) in order to evaluate the external appearances with more objectivity. This apparatus provides a 3D image and numerical data on facial configuration, and this study aims to evaluate the mechanical accuracy of the 3D-AFRA hardware. 2. Methods Several objects of different shapes (cube, cylinder, cone, pyramid) were each scanned 10 times using the 3D Automatic Face Recognition Apparatus (3D-AFRA). The results were then compared and analyzed with data retrieved through a laser scanner known for its high accuracy. The error rates were analyzed for each grid point of facial contour scanned with Rapidform2006 (Rapidform2006 is a 3D scanning software that collects grid point data for contours of various products and products and product parts through 3D scanners and other 3D measuring devices; the grid point data thusly acquired is then used to reconstruct highly precise polygon and curvature models). 3. Results and Conclusions The average error rate was 0.22mm for the cube, 0.22mm for the cylinder, 0.125mm for the cone, and 0.172mm for the pyramid. The visual data comparing error rates for measurement figures retrieved with Rapidform2006 is shown in $Fig.3{\sim}Fig.6$. Blue tendency indicates smaller error rates, while red indicates greater error rates The protruding corners of the cube display red, indicating greater error rates. The cylinder shows greater error rates on the edges. The pyramid displays greater error rates on the base surface and around the vertex. The cone also shows greater error around the protruding edge.

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

• Journal of Sasang Constitutional Medicine
• /
• v.20 no.3
• /
• pp.70-81
• /
• 2008

1. Objective Recently we have known 'First Impression' is the major factor to check the review point for the classification of sasangin. And we want to find out the objected data contribute to dignosis of female sasang constitution using Sasangins Face. 2. Methods We analysed the datum collected by multi-center researchers in 2007-2008. And this study analysed the datum of the measurement of the face by 3D-AFRA (3-Dimensional Automatic Face Recognition Apparatus) and the items of impression by SDQ. We used chi-square test to define the relationship between the item and sasang constitutions. We used independent samples t - test with classifying measuring variables of the face. 3. Results and Conclusion We put out specific female sasangin's constitutional measuring variables of face. The measuring variables of count is Taeyangin 30point, Soyangin 15point, Taeumin 32point, Soeumin 21point. There is the need to accumulate more accurate pictures about sasangin's external shape.

• Journal of Sasang Constitutional Medicine
• /
• v.24 no.4
• /
• pp.17-27
• /
• 2012

Objectives : This study proposes developing Sasang Medical Diagnosis Program using Facial form for increase in Sasang Constitution Diagnosis objectivity and putting the Diagnosis Program into practical use. The author presents a review of extant research on Sasang constitution diagnosis utilizing facial feature analysis and suggests an agenda for further research. Methods : For this thesis, a collection of dissertations on the subject of 'Usage of facial form for constitution diagnosis' published until September of 2012 such as RISS4U, OASIS, KISTI, Korean TK were reviewed. The final 33 dissertations were classified into two categories, basic or clinical research and then analyzed. Results : 9 out of 33 dissertations were of basic research and 24 were of clinical research. 1) As result of review of references, a uniform tendency was found in facial form according to Sasang Constitution. 2) In the grade of practical use, facial element is repeatedly used and the facial element of important use has constitutional differences. 3) Standard faces per Sasang Constitution were derived as result of 2-dimensional research. 4) 3-dimensional research focused on improvement of accuracy and reliability of 3D-AFRA, and there has been an attempt to develop a prototype for identification. Conclusions : For practical use of facial feature in Sasang Constitution Diagnosis, 1) Standardization of diagnosis through establishing Sasang Medical Diagnosis clinical protocol must be preceded. After the standardization, practical purpose and direction of facial form in general may be decided. 2) Information on high quality facial form of constitutional and conditional patients must be collected to form extensive database. 3) Subdivided symptomatology, as well as Sasang Constitution must be considered for diagnosis in order for diagnosis technique to acquire clinical practicality.