Rice seedling and seedling stage weed image semantic segmentation method, system and device and medium

A semantic segmentation and seedling technology, applied in the field of image processing and deep learning, can solve the problems of weak robustness and long training time, and achieve the effect of ensuring accuracy and integrity and good segmentation effect.

Inactive Publication Date: 2019-04-12
SOUTH CHINA AGRI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the deep stacked network model structure has shortcomings such as long training time and weak robustness for large sample image data.

Method used

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  • Rice seedling and seedling stage weed image semantic segmentation method, system and device and medium
  • Rice seedling and seedling stage weed image semantic segmentation method, system and device and medium
  • Rice seedling and seedling stage weed image semantic segmentation method, system and device and medium

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Embodiment 1

[0067] Such as figure 1 As shown, the present embodiment provides a method for semantic segmentation of images of rice seedlings and seedling weeds, the method comprising the following steps:

[0068] S1. Acquiring color sample images of rice seedlings and seedling weeds.

[0069] This embodiment first obtains the color sample image (i.e. RGB sample image) of rice seedlings and weeds at the seedling stage, which can be obtained by collecting, for example, taking a color sample image of rice seedlings and weeds at the seedling stage under natural conditions, or It can be searched and obtained from the database, for example, the color sample images of rice seedlings and seedling weeds are stored in the database in advance, and the color sample images of rice seedlings and seedling weeds can be obtained by searching the database.

[0070] S2. Generate a label sample image corresponding to the color sample image; wherein, the label sample image has labels of pixel types correspon...

Embodiment 2

[0114] Such as Figure 7 As shown, the present embodiment provides a semantic segmentation system for rice seedlings and seedling weed images, the system includes an acquisition module, a generation module, a sample division module, a data set formation module, a construction module and a semantic segmentation module, each module The specific functions are as follows:

[0115] The acquisition module is used to acquire color sample images of rice seedlings and weeds at seedling stage.

[0116] The generation module is used to generate a label sample image corresponding to the color sample image; wherein, the label sample image has labels of pixel types corresponding to rice seedlings, seedling weeds and background.

[0117] The sample division module is used to divide the color sample images and their corresponding label sample images into training samples and test samples.

[0118] The data set forming module is used to perform preprocessing and data amplification on all sam...

Embodiment 3

[0132] This embodiment provides a computer device, which can be a computer, such as Figure 9 As shown, it includes a processor, memory, input device, display, and network interface connected by a system bus. Among them, the processor is used to provide computing and control capabilities, and the memory includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database, and the internal memory is a non-volatile storage medium. Operating system and computer program in the operation provide environment, when computer program is executed by processor, realize the rice seedling of above-mentioned embodiment 1 and seedling stage weed image semantic segmentation method, as follows:

[0133] Obtain color sample images of rice seedlings and seedling weeds;

[0134] Generate a label sample image corresponding to the color sample image; wherein, the label sample image has a pixel type label corres...

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Abstract

The invention discloses a rice seedling and seedling stage weed image semantic segmentation method, system and equipment device and a medium. The method comprises the steps of acquiringthat color sample images of rice seedlings and seedling stage weeds are acquired; gGenerating a label sample image corresponding to the color sample image; D; dividing the color sample image and the label sample image corresponding to the color sample image into a training sample and a test sample; P; preprocessing and data amplification are carried out on all the samples to form a training data set and a test data set; constructing a rice seedling and seedling stage weed image semantic segmentation model based on a full convolutional neural network; classifying pixels of the color images of the rice seedlings and the weeds in the seedling stage by using the rice seedling and seedling stage weed image semantic segmentation model, and outputting the rice seedling and seedling stage weed segmentation images to realize semantic segmentation of the rice seedlings and the weed images in the seedling stage. According to the method, characteristics with high robustness can be learned and extracted from samples, and semantic segmentation of rice seedlings and seedling weed images is realized.

Description

technical field [0001] The present invention relates to a method for semantic segmentation of images of rice seedlings and weeds at the seedling stage, in particular to a method, system, computer equipment and storage medium for image semantic segmentation of rice seedlings and weeds at the seedling stage, belonging to the technical field of image processing and deep learning. Background technique [0002] Precise spraying of pesticides can effectively save 40-60% of pesticide consumption without affecting the weed control effect. The identification of rice seedlings and weeds at the seedling stage is the basis for the selection of herbicide spraying objects and drug types, and the basis for precise control and management of weeds in rice fields. Therefore, how to quickly and accurately identify rice seedlings and weeds at the seedling stage is of great significance . [0003] Because in the past rice seedlings and seedling weed identification process, often rely on manual ...

Claims

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Application Information

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IPC IPC(8): G06K9/34G06N3/04G06N3/08
CPCG06N3/08G06V10/26G06N3/045
Inventor 蒋郁邓向武齐龙马旭郑文汉龚浩邓若玲刘闯陶明李秀昊
Owner SOUTH CHINA AGRI UNIV
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