[Edge detection and modeling in frontal facial contour image for plastic surgery].

[OBJECTIVE] To find a new method for edge detection and modeling in frontal facial contour image.

[METHODS] Searching circle-based edge detection algorithm was developed on the basis of Sobel edge detector. Apriori knowledge of the facial contour and searching limitations as the minimum curvature radius, concave-convex property, and maximum edge disconnected distance were used to detect the edge of frontal facial contour. The frontal facial contour model was established with least squares curve fitting methods, and the relationship between the model rank and model precision was analyzed.

[RESULTS] The edge detected by the new method was consistent with the actual edge of the facial contour and the irrelevant edge was well eliminated. Variation of the 2,4,10 time models from the actual image were compared, which identified the 10 time model as the best one.

[CONCLUSION] The effectiveness and practicability of this new method for edge detection and modeling has been tested, which provides a theoretic basis for designing facial contouring image system.