Lip motion features such as lip width and lip length provide important information to identify persons or recognize commands. Lip motion features have advantage for the theft of registration data because the registration data is changeable like passwords as needed. In addition, such technologies employ a common video camera or a webcam so that they can communalize the interface, which then becomes a system that can be used for both personal authentication and command recognition. However, lip motion features have obscurity, so that the increase in the number of users may result in reduced identification and recognition accuracy. Therefore, developing a method based on result of analysis of lip shape feature is important in order to establish a high reliability personal authentication and command recognition system. Lip shape is a unique body feature to individuals. In this paper, we analyze lip shapes in local region, and develop a grouping method for personal authentication and command recognition system. Lip area is divided into local regions A to C. Region A is a rectangular region that subsumed oral fissure. Region B and region C are the rectangular areas over and under the region A, respectively. After dividing regions, we measure the size of six parts in each region and calculate lip shape features. Next, we analyze lip shape features( i.e., upper and lower lip thickness, oral fissure shape, and aspect ratio). The analysis results show each features were divisible into three groups. Therefore, 27 categories were set and classification was done with fuzzy-reasoning. In the experiment for 52 persons, over 80 percent of subjects were well classified as similar categories. Experiment results suggest that grouping method using the proposed features is useful to narrow down authentication targets. In addition, it was shown that the proposed method classified lip shapes more clearly than k-means clustering.
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