Research on image segmentation technology based on genetic algorithms

The purpose of this paper is to use genetic algorithm(GA) to process image with bottom noise, and the processing effect is improved through the improvement of GA. Combining with image segmentation, this paper expounds the working mechanism of GA and the design methods of main modules such as fitness...

Full description

Saved in:
Bibliographic Details
Published inDiànzǐ jìshù yīngyòng Vol. 45; no. 10; pp. 92 - 95
Main Author An Ting
Format Journal Article
LanguageChinese
Published National Computer System Engineering Research Institute of China 01.10.2019
Subjects
adaptive
background noise
crossover
genetic algorithms
image segmentation
Online AccessGet full text

Cover

More Information
Summary:The purpose of this paper is to use genetic algorithm(GA) to process image with bottom noise, and the processing effect is improved through the improvement of GA. Combining with image segmentation, this paper expounds the working mechanism of GA and the design methods of main modules such as fitness calculation, selection, crossover and mutation, and gives the specific values of parameter setting. The key issues such as the relationship between generation gap and excellent individuals, the substitution relationship between individual among different generations, the selection method of intersection points and the selection of mutation positions, and the maintenance of population number are clarified. The image with bottom noise is processed by this algorithm, the results show that the target image can be separated from the background with noise by GA, but the processing time is 7.416 seconds. In order to improve the processing efficiency, the traditional algorithm is improved by adaptively adjusting the cross
ISSN:0258-7998
DOI:10.16157/j.issn.0258-7998.190452