Improved Active Contour Model by using the honey bee mating optimization

This paper improves the HBMO-SNAKE algorithm. The way is to adjust step of original algorithm as well as replace model parameters. The improved model choose queen flying speed simulate active contour energy and uses mating probability formula to calculate probability candidate control points are selected. The improved model also through calculating the fitness value of candidate control points to decide whether or not to replace the control points. This approach avoids the random number, mutation ratio and mutation variation generated when choose candidate control points. Therefore, the improved model solves the problems that original algorithm parameter redundancy and algorithm slow execution speed, so that the efficiency of the image edge detection substantially increased.