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結(jié)合局部能量與改進的符號距離正則項的圖像目標分割算法

韓明 劉教民 孟軍英 震洲 王敬濤

韓明, 劉教民, 孟軍英, 震洲, 王敬濤. 結(jié)合局部能量與改進的符號距離正則項的圖像目標分割算法[J]. 電子與信息學(xué)報, 2015, 37(9): 2047-2054. doi: 10.11999/JEIT141473
引用本文: 韓明, 劉教民, 孟軍英, 震洲, 王敬濤. 結(jié)合局部能量與改進的符號距離正則項的圖像目標分割算法[J]. 電子與信息學(xué)報, 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 & 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 & Information Technology, 2015, 37(9): 2047-2054. doi: 10.11999/JEIT141473

結(jié)合局部能量與改進的符號距離正則項的圖像目標分割算法

doi: 10.11999/JEIT141473
基金項目: 

河北省自然科學(xué)基金(F2012208004),河北省教育廳高等學(xué)??茖W(xué)研究計劃自然科學(xué)重點項目(ZD20132013)和河北省科技支撐計劃項目(14210302D)

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

  • 摘要: 針對傳統(tǒng)C-V模型對顏色不均勻圖像分割失敗并且對初始輪廓和位置敏感問題,以及現(xiàn)有符號距離正則項存在周期性振蕩和局部極值問題。該文提出結(jié)合局部能量信息和改進的符號距離正則項的圖像目標分割算法。首先,將全局圖像信息擴展到HSV空間,并使用局部能量項信息分析每個像素及其領(lǐng)域內(nèi)的統(tǒng)計特性,從而在較少的迭代次數(shù)內(nèi)有效分割顏色分布不均勻圖像。其次,改進現(xiàn)有符號距離正則項,改進后的符號距離正則項在避免水平集函數(shù)的重新初始化的同時,提高了計算效率,保證了水平集函數(shù)演化過程的穩(wěn)定性。然后,定義閾值判斷法的水平集函數(shù)演化的終止準則,使曲線準確演化到目標輪廓。該算法與同類模型的對比實驗表明該模型具有較高的分割精度和對初始輪廓的魯棒性。
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出版歷程
  • 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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