Intelligent bacterium colony counting method

A counting method and intelligent colony technology, applied in the field of computer vision, can solve problems such as experimenter fatigue

Active Publication Date: 2017-02-22
SHANGHAI MARITIME UNIVERSITY
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  • Application Information

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Problems solved by technology

[0004] The technical problem to be solved by the present invention is to overcome the disadvantage that the traditional colony counting method adop

Method used

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  • Intelligent bacterium colony counting method
  • Intelligent bacterium colony counting method
  • Intelligent bacterium colony counting method

Examples

Experimental program
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Embodiment 1

[0078] This embodiment implements a specific implementation process of an intelligent colony counting method.

[0079] 1. The image acquisition module is used to receive images containing statistical colonies. The received images can be images collected after directly calling the camera, or imported images that have already been captured into the system. The images are usually gray degree image M, if the read-in image is a color RGB image M c , you need to convert the color image M c Convert to grayscale image and pass to edge filtering module.

[0080] The color image M c The transformation method for converting to a grayscale image M is: for the original color image M c The R, G, and B components corresponding to each pixel on M are represented by i and j without loss of generality, then the gray value of the corresponding pixel on M is M(i,j)=0.3 ×B(i,j)+0.59×G(i,j)+0.11×R(i,j), where M(i,j) is an integer, if the result is a decimal, only the integer part is taken, so t...

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Abstract

Provided is an intelligent bacterium colony counting method. An image collection module, an edge filtering module, a binary processing module, an image segmentation module, a characteristic matching module, a result display module and a parameter interaction setting module are included; the image collection module reads in an image of bacterium colonies to be counted; the edge filtering module determines a distribution area of the counting bacterium colonies, and sets points beyond the area as a background; the binary processing module converts an image in the counting area into a binary image; the image segmentation module divides the image in the counting area into independent image blocks, and each block includes only one bacterium colony; the characteristic matching module implements characteristic matching according to a bacterium colony image selected by a user and each image block obtained by segmentation, and an image which succeeds in matching is a bacterium colony image; the result display module displays a matching result, and adjusts the matching result according to selection of the user; and the parameter interaction setting module interacts with the user, reminds the user of input, and receives the result input by the user.

Description

technical field [0001] The invention relates to the field of computer vision, in particular to a method for counting the number of colonies in photos using an image processing method in the field of computer vision. Background technique [0002] In biological experiments, it is often necessary to count the number of colonies in the petri dish. The traditional method is to count the number of colonies manually. This method is time-consuming and laborious, and it is also easy to cause mental fatigue to the experimenter. [0003] The present invention uses a computer image processing method to count and count the colonies in the culture dish. Since images are easy to extract nowadays, the image-based colony counting method has high applicability. The present invention adopts an image feature matching method, so that a large number of wrong colonies can be eliminated. Contents of the invention [0004] The technical problem to be solved by the present invention is to overcome...

Claims

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Application Information

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IPC IPC(8): G06M11/00G06K9/00G06K9/38G06K9/46
CPCG06M11/00G06V20/695G06V20/698G06V10/28G06V10/40
Inventor 刘昱昊
Owner SHANGHAI MARITIME UNIVERSITY
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