Microscope auto-focus window selection method based on artificial fish swarm algorithm

Abstract

The present invention relates to a microscope automatic focusing window selection method based on an artificial fish swarm algorithm. An area with the richest details in a whole image is taken as a focusing window selection basis, the artificial fish swarm algorithm is employed to perform search on a whole image to effectively improve the efficiency while ensuring the focusing precision. Image information formed by automatic focusing of a microscope is mapped into the artificial fish swarm algorithm to initialize parameters and initialize a bulletin board, a dynamic balance weighing factor strategy is introduced to update an artificial fish state; and initialized parameters are reset, and a terminal condition is checked. The image is subjected to binarization processing to remain information of an original map and greatly reduce the processing data amount; the dynamic balance weighing factor is introduced to regulate the step length and the field of view of the artificial fish in realtime to improve the efficiency of algorithm; aiming at the problem of the local optimal value of the artificial fish swarm algorithm, after each iteration, the initialized parameters are reset according to the solved optimized solution to effectively enhance the focusing timeliness and ensure the high rate of convergence and algorithm accuracy.

Description

technical field [0001] The invention relates to an image processing technology, in particular to a method for selecting a microscope auto-focus window based on an artificial fish swarm algorithm. Background technique [0002] The autofocus method based on the microscope system is easy to implement, and the selection of the focus window is an important part of the autofocus method. Selecting an appropriate focus window, that is, selecting the area with the richest image details, can not only reduce the calculation amount of the subsequent focus evaluation function, improve the real-time performance of the focus process, but also reduce the interference of background information on the subject information. The selection window of the traditional focus window algorithm is mainly concentrated in the center of the image, so when the main part is randomly distributed on the image, the region of interest cannot be accurately obtained, and it will be out of focus. Contents of the ...

AI Technical Summary

Problems solved by technology

[0003] Aiming at the problem that the traditional auto-focus window selection algorithm is not suitable for all images, the present invention proposes a microscope auto-focus window selection method based on the artificial fish swarm algorithm, applies the new artificial fish swarm algorithm to the focus window selection, and selects the The area with the richest details in the first image is used as the evaluation basis for the focusing evaluation function to improve the accuracy and efficiency of auto-focusing

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