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Microscope automatic focusing window selection method based on artificial fish swarm algorithm

An artificial fish swarm algorithm and automatic focusing technology, applied in the field of image processing, can solve the problem of not being suitable for all images, and achieve the effect of improving algorithm efficiency, ensuring focusing accuracy, high convergence speed and algorithm accuracy

Inactive Publication Date: 2018-08-28
UNIV OF SHANGHAI FOR SCI & TECH
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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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  • Microscope automatic focusing window selection method based on artificial fish swarm algorithm
  • Microscope automatic focusing window selection method based on artificial fish swarm algorithm
  • Microscope automatic focusing window selection method based on artificial fish swarm algorithm

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Embodiment Construction

[0032] Combining artificial fish swarm algorithm and image processing technology for automatic focusing, such as figure 1 The algorithm flow chart of the autofocus shown in the figure, the specific implementation example is as follows:

[0033] 1) Map the image information of microscope autofocus to the artificial fish swarm algorithm, and define the artificial fish swarm scale X={x 1 , x 2 ,...,x i ,...x n}, where X corresponds to the entire image, and x i (i=1,...,n) is the variable of the individual to be optimized, corresponding to the position of the artificial fish. Initialize artificial fish swarm algorithm parameters: artificial fish swarm scale X, each artificial fish x i The initial position of the artificial fish; the visual range of the artificial fish Visual; the movable step of the artificial fish Step; the crowding factor δ; the maximum number of attempts Try_number of the artificial fish search; the current number of iterations k; the maximum number of ite...

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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 ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G02B21/24G06T7/00G06T7/11G06N3/00
CPCG02B21/244G06N3/006G06T7/0002G06T7/11G06T2207/30168
Inventor 江旻珊闫瑾张学典闫璐
Owner UNIV OF SHANGHAI FOR SCI & TECH
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