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Microalgae image classification method, system and device and storage medium

A microalgae and classification method technology, applied in biological neural network models, instruments, calculations, etc., can solve the problem that the accuracy of microalgae graphic classification cannot meet the requirements

Inactive Publication Date: 2019-09-27
SHANDONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, due to the similar shape and variety of many microalgae images, classic deep learning algorithms, such as AlexNet, VGGNet, GoogleNet, ResNet, etc., cannot meet the requirements for the classification accuracy of microalgae images

Method used

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  • Microalgae image classification method, system and device and storage medium
  • Microalgae image classification method, system and device and storage medium
  • Microalgae image classification method, system and device and storage medium

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Experimental program
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Embodiment 1

[0030] Embodiment 1, this embodiment provides a microalgae image classification method;

[0031] Microalgae image classification methods, including:

[0032] Extracting contour images from images of microalgae to be classified;

[0033] Extract texture images from microalgae images to be classified;

[0034] The contour image and texture image of the microalgae image to be classified are respectively input into the two input terminals of the pre-trained dual-channel convolutional neural network model, and the classification result of the microalgae image is output.

[0035] As one or more embodiments, the specific step of extracting the contour image of the microalgae image to be classified includes: using the Sobel edge detection algorithm to extract the edge of the microalgae image to be classified; and then performing an expansion operation on the image after the edge extraction , to obtain the contour image of the microalgae image to be classified.

[0036] As one or mo...

Embodiment 2

[0096] Embodiment 2, this embodiment provides a microalgae image classification system;

[0097] Image classification system for microalgae, including:

[0098] An outline image extraction module configured to extract an outline image from the microalgae image to be classified;

[0099] A texture image extraction module configured to extract texture images from microalgae images to be classified;

[0100] The classification module is configured to input the outline image and the texture image of the microalgae image to be classified into the two input ends of the pre-trained dual-channel convolutional neural network model, and output the classification result of the microalgae image.

Embodiment 3

[0101] Embodiment 3. This embodiment also provides an electronic device, including a memory, a processor, and computer instructions stored in the memory and run on the processor. When the computer instructions are executed by the processor, each step in the method is completed. For the sake of brevity, the operation will not be repeated here.

[0102] Described electronic device can be mobile terminal and non-mobile terminal, and non-mobile terminal comprises desktop computer, and mobile terminal comprises smart phone (Smart Phone, such as Android mobile phone, IOS mobile phone etc.), smart glasses, smart watch, smart bracelet, tablet computer , laptops, personal digital assistants and other mobile Internet devices that can communicate wirelessly.

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Abstract

The invention discloses a microalgae image classification method, system and device and a storage medium. The method comprises the steps of extracting a contour image of a microalgae image to be classified; extracting texture images from the microalgae images to be classified; and respectively inputting the contour image and the texture image of the microalgae image to be classified into two input ends of a pre-trained dual-channel convolutional neural network model, and outputting a classification result of the microalgae image.

Description

technical field [0001] The disclosure belongs to the field of image data processing, and in particular relates to a microalgae image classification method, system, device and storage medium. Background technique [0002] The statements in this section merely mention background art related to the present disclosure and do not necessarily constitute prior art. [0003] In the process of realizing the present disclosure, the inventors found that the following technical problems existed in the prior art: [0004] At present, artificial intelligence technology has made substantial breakthroughs in various fields (image processing, object detection, speech translation, etc.), and is booming at an explosive speed. The information-oriented and system-building smart ocean is the long-term starting point for realizing my country's ocean power strategy, and artificial intelligence technology is the core supporting technology for completing the smart ocean construction. From the persp...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/04
CPCG06N3/045G06F18/2431G06F18/214
Inventor 贾智平张余豪张志勇申兆岩刘珂
Owner SHANDONG UNIV
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