Abstract
The traditional Snake algorithm cannot effectively detect the object edge of an image with non-convex shapes or low SNR. This paper studies the characteristics of this type of image with complex shape target or noise and presents an improved Snake algorithm. The traditional Snake function model and operation strategy are improved by increasing new control energy functions, and the influencing weight of these energy factors is discussed. At the same time, a dynamic arrangement for the Snake points is used to adapt different target shapes. The simulation results indicate that the new Snake model greatly decreases the dependence on the Snake point’s initial position and effectively overcomes noise influence. This method enhances the Snake algorithm’s ability of detecting object edge.
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