计算机科学 ›› 2015, Vol. 42 ›› Issue (6): 303-307.doi: 10.11896/j.issn.1002-137X.2015.06.064
何玲娜,曹建伐,郑河荣
HE Ling-na, CAO Jian-fa and ZHENG He-rong
摘要： 大多数经典活动轮廓模型只具有某些方面的优势,不能同时满足处理复杂图像的要求,对此提出一种具有多重分割特性的分割模型。模型通过引入差分图像,将差分图像的BGFRLS模型作为全局控制项,以保证模型能够最大限度地检测到所有的目标边缘；其次,将长度项设为局部项,使得分割进一步精确化,并将Li方法中的惩罚项加入到模型中,避免了重新初始化水平集函数,提高了分割效率；最后,模型在全局控制项和局部控制项之间引入了自适应权值,避免了过多的参数设置。通过上述方法使得模型具有如下优点:1)具有更强的全局分割性；2)可以分割灰度不均匀的图像,而且能够有效地检测出虚弱目标边缘；3)算法具有一定鲁棒性,能够克服一定噪声。实验表明,该模型在保证分割效率的前提下可以分割灰度不均匀的图像,而且能够有效检测出虚弱目标边缘,此外还具有更强的全局分割性,并能抵御一定噪声。
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