An enhanced image binarization method incorporating with Monte-Carlo simulation

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. T...

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Bibliographic Details
Published in:Journal of Central South University 2019-06, Vol.26 (6), p.1661-1671
Main Authors: Han, Zheng, Su, Bin, Li, Yan-ge, Ma, Yang-fan, Wang, Wei-dong, Chen, Guang-qi
Format: Article
Language:English
Subjects:
Algorithms
Computer simulation
Engineering
Illumination
Image enhancement
Metallic Materials
Monte Carlo simulation
Simulation
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Summary: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.
ISSN:2095-2899
2227-5223
DOI:10.1007/s11771-019-4120-9