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结合局部能量与改进的符号距离正则项的图像目标分割算法

韩明 刘教民 孟军英 震洲 王敬涛

韩明, 刘教民, 孟军英, 震洲, 王敬涛. 结合局部能量与改进的符号距离正则项的图像目标分割算法[J]. 电子与信息学报, 2015, 37(9): 2047-2054. doi: 10.11999/JEIT141473
引用本文: 韩明, 刘教民, 孟军英, 震洲, 王敬涛. 结合局部能量与改进的符号距离正则项的图像目标分割算法[J]. 电子与信息学报, 2015, 37(9): 2047-2054. doi: 10.11999/JEIT141473
Han Ming, Liu Jiao-min, Meng Jun-ying, Wang Zhen-zhou, Wang Jing-tao. Local Energy Information Combined with Improved Signed Distance Regularization Term for Image Target Segmentation Algorithm[J]. Journal of Electronics and Information Technology, 2015, 37(9): 2047-2054. doi: 10.11999/JEIT141473
Citation: Han Ming, Liu Jiao-min, Meng Jun-ying, Wang Zhen-zhou, Wang Jing-tao. Local Energy Information Combined with Improved Signed Distance Regularization Term for Image Target Segmentation Algorithm[J]. Journal of Electronics and Information Technology, 2015, 37(9): 2047-2054. doi: 10.11999/JEIT141473

结合局部能量与改进的符号距离正则项的图像目标分割算法

doi: 10.11999/JEIT141473
基金项目: 

河北省自然科学基金(F2012208004),河北省教育厅高等学校科学研究计划自然科学重点项目(ZD20132013)和河北省科技支撑计划项目(14210302D)

Local Energy Information Combined with Improved Signed Distance Regularization Term for Image Target Segmentation Algorithm

  • 摘要: 针对传统C-V模型对颜色不均匀图像分割失败并且对初始轮廓和位置敏感问题,以及现有符号距离正则项存在周期性振荡和局部极值问题。该文提出结合局部能量信息和改进的符号距离正则项的图像目标分割算法。首先,将全局图像信息扩展到HSV空间,并使用局部能量项信息分析每个像素及其领域内的统计特性,从而在较少的迭代次数内有效分割颜色分布不均匀图像。其次,改进现有符号距离正则项,改进后的符号距离正则项在避免水平集函数的重新初始化的同时,提高了计算效率,保证了水平集函数演化过程的稳定性。然后,定义阈值判断法的水平集函数演化的终止准则,使曲线准确演化到目标轮廓。该算法与同类模型的对比实验表明该模型具有较高的分割精度和对初始轮廓的鲁棒性。
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出版历程
  • 收稿日期:  2014-11-24
  • 修回日期:  2015-03-23
  • 刊出日期:  2015-09-19

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