摘要：

为快速准确地分割出图像中的感兴趣目标,提出改进的狼群算法并结合二维最大熵实现图像目标分割。在狼群算法的游走环节利用混沌系统动态调整惯性权重,在攻击环节对整个解空间进行混沌全局搜索,并将改进狼群算法与二维最大熵相结合优化准则函数。实验结果表明,该算法能够实现对目标图像的精确分割,与基本狼群算法结合二维最大熵分割相比速度更快,准确度更高。

关键词: 图像分割, 狼群算法, 二维最大熵, 混沌系统, 优化函数

Abstract:

In order to segment interested objects in image accurately and quickly,an improved Wolf Pack Algorithm(WPA) is proposed combined with 2D maximum entropy to realize the effective segmentation of image targets.In travel link of WPA,the chaotic systems is used dynamically to adjust the inertia weight.In the attack link,chaotic global search is finisned in the whole solution space.The criterion function is maximized by using the improved WPA combining the 2D maximum entropy.Experimental results show that the proposed algorithm can get accurate image segmentation effect.Compared with the 2D maximum entropy combining with the origin WPA,it can improve the speed and accuracy of image segmentation.

Key words: image segmentation, Wolf Pack Algorithm(WPA), 2D maximum entropy, chaotic system, optimal function

中图分类号: 

• TP311