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- Title
正余弦优化算法在多阈值图像分割中的应用.
- Authors
鲍小丽; 贾鹤鸣; 郎春博; 彭晓旭; 康立飞; 李金夺
- Abstract
Threshold selection has an important impact on the effect of image segmentation. In traditional image segmentation, there are some problems such as single segmentation result, weak flexibility and easy to fall into local optimum. In order to determine the optimal thresholds for image segmentation, a multilevel-thresholding image segmentation method based on sine cosine algorithm(SCA) is proposed in this paper. The method takes the between-class variance as the fitness function of the sine-cosine algorithm, updates the position of the current solution in each dimension by changing the sine function and cosine function. The candidate solution uses multiple random operators to carry out sine-cosine fluctuation around the optimal solution to complete each optimization process, and updates the optimum through iterative calculation. The optimal thresholds of image segmentation are determined by the location of the solution. Four standard test images are selected for experiment and compared with PSO algorithm in peak signal to noise ratio, structural similarity method, and optimization time. It shows the application of sine-cosine algorithm in image segmentation can obtain more accurate threshold and higher segmentation efficiency, which has a strong practicability.
- Subjects
THRESHOLDING algorithms; IMAGE segmentation; SIGNAL-to-noise ratio; SINE function; RANDOM operators; PROCESS optimization; COSINE function; LEVEL set methods
- Publication
Forest Engineering, 2019, Vol 35, Issue 4, p58
- ISSN
1006-8023
- Publication type
Article