Journal of System Simulation
Abstract
Abstract: In order to accurately segment the multi-objective image whose objective area is too small, and the background gray value is similar to the objective, a threshold segmentation algorithm based on statistical curve difference method is proposed. The mountain model of multi-objective gray image is established and the gray image is normalized. The number of connected area is counted by threshold division. The statistical curve is plotted with the horizontal coordinate being the gray level with equal interval, and the vertical coordinate being the counting result. The threshold point is the point where the difference value of the statistical curve is close to zero. Experiment results show that the proposed method is more accurate than the Otsu and the maximum entropy threshold segmentation method.
Recommended Citation
Zhu, Yuanfei; Zhang, Sixiang; Wei, Zhou; Wang, Xiaochen; and Li, Zhidong
(2020)
"Multi-Objective Image Threshold Segmentation Based on Statistical Curve Difference Method,"
Journal of System Simulation: Vol. 29:
Iss.
11, Article 44.
DOI: 10.16182/j.issn1004731x.joss.201711044
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol29/iss11/44
First Page
2927
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.201711044
Last Page
2933
CLC
TP311
Recommended Citation
Zhu Yuanfei, Zhang Sixiang, Zhou Wei, Wang Xiaochen, Li Zhidong. Multi-Objective Image Threshold Segmentation Based on Statistical Curve Difference Method[J]. Journal of System Simulation, 2017, 29(11): 2927-2933.
DOI
10.16182/j.issn1004731x.joss.201711044
Included in
Artificial Intelligence and Robotics Commons, Computer Engineering Commons, Numerical Analysis and Scientific Computing Commons, Operations Research, Systems Engineering and Industrial Engineering Commons, Systems Science Commons