基于蒙特卡洛模拟的图像二值化增强算法

Zheng Han, Bin Su, Yan ge Li, Yang fan Ma, Wei dong Wang, Guang qi Chen

研究成果: Contribution to journalArticle査読

6 被引用数 (Scopus)

抄録

We proposed an enhanced image binarization method. The proposed solution incorporates Monte-Carlo simulation into the local thresholding method to address the essential issues with respect to complex background, spatially-changed illumination, and uncertainties of block size in traditional method. The proposed method first partitions the image into square blocks that reflect local characteristics of the image. After image partitioning, each block is binarized using Otsu's thresholding method. To minimize the influence of the block size and the boundary effect, we incorporate Monte-Carlo simulation into the binarization algorithm. Iterative calculation with varying block sizes during Monte-Carlo simulation generates a probability map, which illustrates the probability of each pixel classified as foreground. By setting a probability threshold, and separating foreground and background of the source image, the final binary image can be obtained. The described method has been tested by benchmark tests. Results demonstrate that the proposed method performs well in dealing with the complex background and illumination condition.

寄稿の翻訳タイトルAn enhanced image binarization method incorporating with Monte-Carlo simulation
本文言語中国語 (繁体字)
ページ(範囲)1661-1671
ページ数11
ジャーナルJournal of Central South University
26
6
DOI
出版ステータス出版済み - 6 1 2019

All Science Journal Classification (ASJC) codes

  • 工学(全般)
  • 金属および合金

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