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结合遗传算法的局部最小误差孔穴图像分割法
引用本文:孙鹏飞,任洪娥,董本志.结合遗传算法的局部最小误差孔穴图像分割法[J].计算机工程与应用,2012,48(7):169-171.
作者姓名:孙鹏飞  任洪娥  董本志
作者单位:东北林业大学,哈尔滨,150040
基金项目:国家自然科学基金(No.30972314); 国家林业局“948”创新项目(No.2006-4-c03); 东北林业大学研究生科技创新项目(No.GRAM09)
摘    要:针对遗传算法和最小误差分割法各自的优缺点,将最小误差分割法与遗传算法进行改进并且相互结合,提出了一种结合遗传算法的局部最小误差孔穴图像分割法。该方法利用局部图像信息确定最佳阈值范围,并根据模拟退火思想对个体适应度进行自适应的调整,从而避免了早熟现象,提高了运算速度。实验结果表明:该方法不但能够准确地分割出孔穴图像,而且运算速度较快,是一种有效的孔穴图像分割方法。

关 键 词:阈值分割  最小误差法  遗传算法  局部阈值  孔穴图像

Partial minimum error thresholding method of cavity image combined with genetic algorithm
SUN Pengfei , REN Hong'e , DONG Benzhi.Partial minimum error thresholding method of cavity image combined with genetic algorithm[J].Computer Engineering and Applications,2012,48(7):169-171.
Authors:SUN Pengfei  REN Hong'e  DONG Benzhi
Affiliation:Northeast Forest University, Harbin 150040, China
Abstract:According to the advantages and disadvantages of the genetic algorithm and the minimum error thresholding method, a partial minimum error thresholding method of cavity image combined with genetic algorithm is developed by improving and combining genetic algorithm with minimum error thresholding method. This method uses the partial information of the cavity image to confirm the best threshold range, and uses simulated annealing algorithm to adjust the individual fitness degree, thus the premature convergence is avoided and the operation speed is improved. The results show that this method can segment the cavity image fast and accurately, and it is an effective method of cavity image segmentation.
Keywords:threshold segmentation  minimum error thresholding method  genetic algorithm  local threshold  cavity image
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