许文祥,张国英,蒋 焱,陈路豪.基于二项分布的双窗OTSU的矿石分割模型[J].有色金属(矿山部分),2019,71(3):96-102.
基于二项分布的双窗OTSU的矿石分割模型
Ore segmentation model by Bi-window OTSU based on binomial distribution
  
DOI:10.3969/j.issn.1671-4172.2019.03.021
中文关键词:  OTSU阈值  类间方差  双窗  二值化  二项分布
英文关键词:OTSU threshold  variance between clusters  double window  binarization  binomial distribution
基金项目:国家自然科学基金资助项目(U1704242)
           
作者单位
许文祥 (中国矿业大学(北京)机电与信息工程学院,北京 100083)
张国英 (中国矿业大学(北京)机电与信息工程学院,北京 100084)
蒋 焱 (中国矿业大学(北京)机电与信息工程学院,北京 100085)
陈路豪 (中国矿业大学(北京)机电与信息工程学院,北京 100086)
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中文摘要:
      表面不均匀的矿石视频图像目标受光照、周围环境的影响,噪声严重,传统的阈值法不能准确有效的分割。而双窗OTSU方法计算代价过高,且双窗阈值取极值作为目标像素的最佳阈值,导致部分像素误分类。提出了基于二项分布优化的双窗OTSU算法,双窗模板大小取决于最大和最小目标尺寸。通过实验与数学理论证明方法的可行性与准确性,时间成本降低50%~80%。对于目标易分类的图像,分类精度提升6%左右;对于目标难以分类的图像,分类精度提升13%左右。算法自主确定窗口尺寸,增加其智能性,抗噪声干扰性强,降低了误分类率,时间成本大幅度降低。
英文摘要:
      Noise of uneven ore objects in images is seriously influenced by illumination and textures, causing it cannot be accurately and effectively segmented by traditional threshold method. The calculation cost of the double-Window OTSU method is too high, and the extreme value of the double-Window threshold is taken as the optimal threshold value of the target pixel, resulting in partial pixel misclassification. In this paper, a double-window OTSU algorithm based on binomial distribution optimization was presented, the size of the double window template depended on the maximum and minimum target sizes. The feasibility and accuracy of the proposed method were proved by experiment and mathematical theory, and the time cost was reduced by 50%~80% greatly. The classification accuracy was improved by about 6% for the image of object easy classification, about 13% for the image of object uneasy classification. The algorithm determined the size of the window independently, increased its intelligence and strong anti-noise, reduced the misclassification rate and greatly reduced the time cost.
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