| Issue |
MATEC Web Conf.
Volume 176, 2018
2018 6th International Forum on Industrial Design (IFID 2018)
|
|
|---|---|---|
| Article Number | 01041 | |
| Number of page(s) | 4 | |
| Section | Intelligent Design and Computer Technology | |
| DOI | https://doi.org/10.1051/matecconf/201817601041 | |
| Published online | 02 July 2018 | |
An improved method of microscopic image segmentation
Henan university of science and technology,
HeNan 471023,China.
* Corresponding author :afantasyericdong@163.com
In order to improve the effectiveness and accuracy of image processing in modern medical inspection, a segmentation image optimization algorithm of improved two-dimensional maximum entropy threshold based on genetic algorithm combined with mathematical morphology is proposed, in view of the microscopic cell images characteristic and the shortcomings of the traditional segmentation algorithm. Through theoretical analysis and contrast test, the segmentation method proposed is superior to the traditional threshold segmentation method in microscopic cell images, and the average segmentation time of the improved algorithm is 73% and 44% higher than the traditional two-dimensional maximum entropy threshold and the improved two-dimensional maximum entropy threshold.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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