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A method for automatic detection of Trichomonas leucorrhea based on moving target recognition

A moving target and automatic detection technology, applied in the field of image processing, can solve the problems of difficult classification of morphological features and difficult segmentation of trichomonas microscopic images, etc., and achieve the effect of accurate segmentation

Active Publication Date: 2019-06-21
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

[0005] The present invention proposes a solution to solve the problems that trichomonas microscopic images are difficult to segment and morphological features are difficult to classify. At the same time, the traditional Kalman background reconstruction method is improved, which can effectively suppress the noise caused by illumination changes, lens movement and focal length changes, and accurately Segment background and foreground regions

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  • A method for automatic detection of Trichomonas leucorrhea based on moving target recognition
  • A method for automatic detection of Trichomonas leucorrhea based on moving target recognition

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[0047] Below in conjunction with accompanying drawing, the visual scheme of the present invention is described in detail:

[0048] Step 1: Smear the leucorrhea sample on a glass slide, put it under the microscope, obtain the best shooting distance and keep it fixed;

[0049] Step 2: Use the microscope camera to collect continuous and clear sample image sequences under the same field of view;

[0050] Step 3: use the first image of the image sequence in step 2 as the background image in the Kalman background reconstruction method;

[0051] Step 3-1: Extract the first image of the image sequence;

[0052] Step 3-2: Perform Gaussian filtering on the image, use a circular neighborhood with a radius of 10, and parameter σ equal to 2 to filter out noise and obtain a background image.

[0053] Step 4: Extract the follow-up image collected in step 2, obtain the difference image after the difference between the current follow-up image and the background image, and obtain the undeterm...

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Abstract

The invention discloses a method for automatic detection of trichomonas leucorrhea based on moving target recognition, which belongs to the field of image processing. The method obtains sample images continuously, and then processes the sample images to obtain the foreground and background of the image. By analyzing the foreground and background of the continuous images, the trichomonas area is identified where the foreground and background change, and then according to the trichomonas Morphological characteristics further identified Trichomonas. Therefore, the present invention improves the traditional Kalman background reconstruction method, can effectively suppress the noise caused by illumination changes, lens movement and focal length changes, and accurately segment background and foreground regions.

Description

technical field [0001] The invention belongs to the field of image processing, in particular a method for automatically detecting trichomonas in leucorrhea by adopting a moving target recognition method. Background technique [0002] Microscopic examination of trichomonas is a routine item in leucorrhea examination, and it is an important criterion for judging whether leucorrhea is abnormal. The commonly used detection method for trichomonas in hospitals is manual microscopic examination, which is not efficient and is prone to missed detection. In order to solve the problems of low manual efficiency and error-prone, many applications of automatic detection of biological cells have been proposed. A computer vision method commonly used at present is: first segment the microscopic image, extract a single cell, further analyze the various morphological characteristics of each cell, and finally use an appropriate feature classification method to classify the cells to identify th...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01N21/84G06T7/10G06T7/194
CPCG01N21/84G06T2207/10061
Inventor 刘霖王祥舟胡静蓉郝如茜张正龙韩翠张静刘娟秀倪光明杜晓辉刘永
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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