• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.6
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• pp.49-59
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• 2008

SIFT(Scale Invariant Feature Transform) is an algorithm to extract vectors at pixels around keypoints, in which the pixel colors are very different from neighbors, such as vortices and edges of an object. The SIFT algorithm is being actively researched for various image processing applications including 3-D image constructions, and its most computation-intensive stage is a keypoint localization. In this paper, we develope a fixed-point model of the keypoint localization and propose its efficient hardware architecture for embedded applications. The bit-length of key variables are determined based on two performance measures: localization accuracy and error rate. Comparing with the original algorithm (implemented in Matlab), the accuracy and error rate of the proposed fixed point model are 93.57% and 2.72% respectively. In addition, we found that most of missing keypoints appeared at the edges of an object which are not very important in the case of keypoints matching. We estimate that the hardware implementation will give processing speed of $10{\sim}15\;frame/sec$, while its fixed point implementation on Pentium Core2Duo (2.13 GHz) and ARM9 (400 MHz) takes 10 seconds and one hour each to process a frame.

• Journal of Sasang Constitutional Medicine
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• v.26 no.4
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• pp.350-364
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• 2014

Objectives This study was aimed to find the significant features of face form according to the Taeeumin and Soyangin by analyzing the three-dimensional face information data. Also, making standard face of the Taeeumin and Soyangin was an object of this study. Methods We collected three-dimensional face data of patients aged between 20~45 years old diagnosed by a specialist of Sasang constitutional medicine. The data were collected using a 3D scanner, Morpheus 3D(Morpheus Corporation, KOREA). Extracting a face feature point total of 64, was set to 332 pieces(height, angle, ratio, etc.) of each variable between feature points. ANOVA test were used to compare the characteristics of subjects according to the Taeeumin and Soyangin. Results When not to consider gender, the Taeeumin and Soyangin were different from the 18 items(3 items in the ear, 9 items in the eye, 1 item in the nose, 1 item in the mouth, 4 items in the jaw). When to consider gender, the Taeeumin and Soyangin men were different from the 6 items(1 item in the ear, 2 items in the nose, 3 items in the face). And the Taeeumin and Soyangin women were different from 17 items(1 item in the ear, 10 items in the eye, 2 items in the nose, 1 item in the mouth, 3 items in the face). Conclusions These results show Taeeumin's face(both men and women) width of the right and left is larger than the length of the top and bottom. Compared to men of Soyangin, men of Taeeumin has greater wings of the nose. Compared to women of Soyangin, women of Taeeumin has longer length of the eye. Soyangin's face(both men and women) length of the top and bottom is larger than the width of the right and left. Compared to men of Taeeumin, men of Soyangin has smaller wings of the nose. Compared to women of Taeeumin, women of Soyangin has more stereoscopic facial features at the top and bottom of the lateral face. Also, by accumulating three-dimensional face data, this study modeled the standard facial features by Taeeumin and Soyangin. These results may be helpful in the development of Sasang constitutional diagnostics utilizing the characteristics of the facial form at later.