For face portraits generated by computer processing is one of the research direction in computer vision, with the widely used in the area of the science exhibition, and the use of computer vision technology research in industrial production and daily life. In this paper, the face portrait generation system based on computer vision generated automatically according to user’s frontal faces. The main contents and results of this paper: Researched face detection algorithm. Firstly, this paper analyzed the common color space theory. Secondly, we introduce the method of face detection based on skin color and Haar-like features face detection. Then based on Haar-like features face detection, we extracted facial region accurately. Researched face region landmark positioning algorithm. Researched Point Distribution Model (PDM), Active Shape Model (ASM), and Active Appearance Model (AAM). In combination with the ASM is faster than AAM, this paper using ASM accurately extracts the face region key points. This improves the overall effectiveness of face portrait. Researched non-face region contour generation algorithm. Introduced the algorithm of image segmentation, and by using the probability on the edge of the image segmentation model, to edge detection, obtained outline non-face region. Researched key point linearization algorithm. In order to generate more realistic portraits, we using the Bezier curve interpolation algorithm, and generating to a number of vector lines by the image edge pixel points. The system refers in this paper was tested on front images in CAS-PEAL face database. The result shows that the system is robust for different person’s face and different age range faces.
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