• Journal of Information Processing Systems
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• v.9 no.1
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• pp.141-156
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• 2013

In this paper we propose a method to detect human faces in color images. Many existing systems use a window-based classifier that scans the entire image for the presence of the human face and such systems suffers from scale variation, pose variation, illumination changes, etc. Here, we propose a lighting insensitive face detection method based upon the edge and skin tone information of the input color image. First, image enhancement is performed, especially if the image is acquired from an unconstrained illumination condition. Next, skin segmentation in YCbCr and RGB space is conducted. The result of skin segmentation is refined using the skin tone percentage index method. The edges of the input image are combined with the skin tone image to separate all non-face regions from candidate faces. Candidate verification using primitive shape features of the face is applied to decide which of the candidate regions corresponds to a face. The advantage of the proposed method is that it can detect faces that are of different sizes, in different poses, and that are making different expressions under unconstrained illumination conditions.

• The Journal of Internal Korean Medicine
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• v.28 no.3
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• pp.560-569
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• 2007

Objectives : Ryodoraku is a physiological function test using electric current, and is closely related to skin sympathetic tone. Pulse analysis is known to reflect cardiovascular reactivity. There has been no report on the correlation between ryodoraku and pulse analysis in respiratory diseases. The present study examined the diagnostic values of ryodoraku and pulse analysis for respiratory disease patients Methods : For this study, we conducted ryodoraku and pulse analysis in 103 people including 79 respiratory disease outpatients who visited the $5^{th}$ Internal Department of the Oriental Medicine Hospital of Kyung Hee University during the period from January 1, 2003 to July 25, 2006, and 24 volunteers who did not have any respiratory symptoms or disease history. The respiratory disease patients were divided into five sub-groups according to their symptom: cough-sputum group, wheezing-dyspnea group ' nasal symptoms group. cold-prone group, and fatigue prone group. We compared the disease groups with the control group in six items as follows : mean ryodoraku, mean H1, mean elastic index, the percentage of those with mean ryodoraku below $40{\mu}A$, the percentage of those with HI beyond the physiological range, and the ratio of left : right of elastic index Results and Conclusions : Ryodoraku and pulse analysis were found to have a high value as quantitative diagnosis tools reflecting individuals' weakness and firmness. The results of this research suggest that ryodoraku and pulse analysis have value as tools for diagnosing respiratory diseases.