Ore segmentation model by Bi-window OTSU based on binomial distribution
  
View Full Text  View/Add Comment  Download reader
DOI:10.3969/j.issn.1671-4172.2019.03.021
KeyWord:OTSU threshold; variance between clusters; double window; binarization; binomial distribution
           
AuthorInstitution
XU Wenxiang (中国矿业大学(北京)机电与信息工程学院,北京 )
ZHANG Guoying (中国矿业大学(北京)机电与信息工程学院,北京 )
JIANG Yan (中国矿业大学(北京)机电与信息工程学院,北京 )
CHEN Luhao (中国矿业大学(北京)机电与信息工程学院,北京 )
Hits: 1174
Download times: 0
Abstract:
      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.
Close