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Figure 3 shows an example of lip image and its components before and after illumination equalization.
If the absolute value of ordinate difference between Q1 and Q2 is greater than half the height of lip image, we deem the mouth is open.
We suppose the mouth is closed if the absolute value of ordinate difference between Q1 and Q2 is less than half the height of lip image.
When the absolute value of ordinate difference between Q1 and Q2 is greater than half the height of lip image, we consider the mouth is open.
Prior to classification of lip image, we use segmentation algorithm based on level set model to get the lip images in face.
An example of lip image segmentation is shown in the Figure 3. Experimental results on five hundred lip images show that the hybrid approach produces more accurate segmentation [ 11].
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Most variance of lip images during speaking is along opening and closing of lips.
Results presented in Figure 1c show that this has resulted in synthesized opening and closing of lip images.
More quantitative assessment of curve estimation is feasible in the case of lip images, as discussed in Section 5.
They are also applied to a collection of lip images where possible differences in shape between males and females are of interest.
In this study, we explore diagnosis of Traditional Chinese Medicine based on lip Images by combining imaging features from color component, textural and moment features, and assess the significance of each feature in classification.
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