Microorganism recognition system and method based on Django and image feature matching

An image feature and identification system technology, applied in the field of microbial identification, can solve problems such as limited environment and inability to apply to the masses, and achieve the effect of reducing the difficulty of teaching

Inactive Publication Date: 2022-01-21
SHANGHAI JINSHAN DISTRICT YOUTH ACTIVITY CENT
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Problems solved by technology

However, the application environment of this patent is limited and cannot be applied to the general public

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  • Microorganism recognition system and method based on Django and image feature matching
  • Microorganism recognition system and method based on Django and image feature matching
  • Microorganism recognition system and method based on Django and image feature matching

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Embodiment

[0051] According to the microbial identification system based on Django and image feature matching provided by the present invention, it includes: using Django and MySQL to build a microbial sample library website, the user can upload the identified and classified microbial samples to the system database through the browser, when the user uses After an image is acquired by the electron eyepiece microscope, it can be uploaded through this website, and the background of the system uses the SURF algorithm to match the existing data in the library, and finally obtains a list of microbial category acquaintances.

[0052]When building the microbial database, choose OpenCV, and choose the SURF algorithm with faster speed and more accurate recognition on the local feature algorithm. It is an improvement to SIFT, and its main feature is fast. In addition, on the visual interface, the form of a Django-based website is chosen, which is convenient for deployment and use.

[0053] Said Ope...

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Abstract

The invention provides a microorganism recognition system and method based on Django and image feature matching. The system comprises: a module M1, which is used for building a microorganism sample library website by using Django and MySQL; a module M2, which is used for uploading identified and classified microorganism samples to the sample library through a browser; a module M3, which is used for, when a user uses an electronic eyepiece microscope to obtain an image and uploads the image to the website, matching existing data in the sample library through an SURF algorithm, and finally obtaining a microbial category similarity list. According to the invention, common microorganisms in microscope image information are automatically identified and displayed in a visual interface, students learn more about microorganisms through their own observation, and the learning method is easier to accept by the students and is more comprehensive compared with a traditional method in the prior art, such as obtaining microorganism identity information from image data.

Description

technical field [0001] The invention relates to the technical field of microbial identification, in particular to a microbial identification system and method based on Django and image feature matching. Background technique [0002] As ancient organisms on earth, the role of microorganisms cannot be underestimated. However, the public's knowledge of microbes often only comes from the classroom. Through the school survey, 88.68% of the students think that the education of microbes is more important. The current teaching methods in microbiology courses require relatively high teacher experience, but there are not many teachers with high teaching experience, and new teachers also need to learn in order to accumulate experience. As far as students are concerned, the traditional microscope eyepieces currently used by students are too small for detailed observation. All kinds of students have different needs for knowledge. For children with strong learning ability, they are curi...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06V20/69G06Q50/20
CPCG06Q50/20
Inventor 顾宇昂陆广琴
Owner SHANGHAI JINSHAN DISTRICT YOUTH ACTIVITY CENT
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