Microscope image-based astronomical algal cell statistical method

A technology of algae cells and statistical methods, which is applied in the field of star rod algae cell statistics, can solve the problems of missed detection and false detection, and achieve the effect of eliminating false detection data, reducing data labeling work, and improving efficiency

Active Publication Date: 2022-07-22
生态环境部长江流域生态环境监督管理局生态环境监测与科学研究中心
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Problems solved by technology

[0003]The existing method is to directly mark the stellate algae cells, and then use the deep learning model to detect the number of star stem algae cells in the image, which is prone to missed detection and the false detection problem

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  • Microscope image-based astronomical algal cell statistical method
  • Microscope image-based astronomical algal cell statistical method
  • Microscope image-based astronomical algal cell statistical method

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Embodiment 1

[0088] refer to figure 1 , the invention discloses a method for statistics of star rod algae cells based on microscope images, which comprises the following steps:

[0089] (1) Image preprocessing: operations to denoise and enhance contrast on grayscale images;

[0090] (2) Image binarization: detect the binary image of star rod algal cells from the grayscale image;

[0091] (3) Detection of star rod algal cells: find straight lines from the binary image, then cluster these straight lines according to angles, and find the minimum enclosing rectangle of the algal cells through the endpoint coordinates of the parallel line segments;

[0092] ⑷Verify the attribute data of star rod algae cells: Calculate its middle line segment through the smallest enclosing rectangle, and use the middle line to represent star rod algae cells. Combined with information such as the angle, length and intersection coordinates of the line segment, the data that does not conform to the characteristic...

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Abstract

The invention discloses a microscopy image-based astronomical algal cell statistical method, which comprises the following steps of: acquiring an algal image, preprocessing the algal image, denoising and enhancing the contrast ratio of the image; carrying out binarization processing on the enhanced grayscale image to obtain a binary image; based on the binary image, astronomical algal cell detection is carried out, attribute data of astronomical algal cells are obtained, and whether characteristics of the astronomical algal cells are met or not is verified according to the attribute data; and counting the detection data meeting the characteristics of the astrophe astrophe cells to obtain the number of the astrophe astrophe cells. The method does not need to directly detect the astronomical algal cells in a deep learning model, reduces the data labeling work, improves the efficiency of model training and model optimization, and has wide applicability.

Description

technical field [0001] The invention belongs to the technical field of water ecological environment monitoring, and in particular relates to a method for statistics of star rod algae cells based on microscope images. Background technique [0002] Use microscopes and high-definition industrial cameras to collect algal images, and then identify the star rod algae and its pixel coordinates through the deep learning detection model. It is necessary to design an image pattern recognition method to count the number of cells of the star rod algae in the image. [0003] The existing method is to directly label the star rod algae cells, and then use the deep learning model to detect the number of star rod algae cells in the image, which is prone to problems of missed detection and false detection. Therefore, the present invention proposes a statistic method of star rod algae cells based on microscope images to solve the problems existing in the prior art. SUMMARY OF THE INVENTION ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T5/00G06T5/10G06T5/40
CPCG06T7/0002G06T5/10G06T5/40G06T2207/20061G06T2207/10056G06T2207/30242G06T5/90G06T5/70
Inventor 王英才李斌胡圣张晶彭玉李书印方标
Owner 生态环境部长江流域生态环境监督管理局生态环境监测与科学研究中心
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