Method for recognizing image of plant leaf

A plant leaf and image recognition technology, applied in the field of plant leaf image recognition, can solve the problems of lack of representativeness, impact of matching effect, quality and quantity to be improved, etc., achieve high recognition rate and improve credibility

Inactive Publication Date: 2010-12-15
GUANGZHOU UNIVERSITY OF CHINESE MEDICINE
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AI Technical Summary

Problems solved by technology

Therefore, the quality and quantity of the features taken by this method need to be improved
[0007] Second, there is no mention of the selection or calculation of standard samples for each plant leaf in the database
However, there is still a certain degree of variation between the leaves of plants

Method used

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  • Method for recognizing image of plant leaf
  • Method for recognizing image of plant leaf
  • Method for recognizing image of plant leaf

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Experimental program
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Embodiment

[0044] like figure 1 As shown, the image recognition method of the plant leaf of the present invention comprises the following steps:

[0045] 1) Start the system, then go to step 2).

[0046] 2) In the process of using this method, it is divided into two situations: "training the system (software system programmed according to this method) with known types of training sets" and "using the system to classify unknown plants". Therefore, this step is specifically as follows: first determine whether a professional needs to input a training set of known types to the system, or whether an ordinary user inputs a blade to be identified; if it is the former, go to step 3), if it is the latter, go to step 7 ).

[0047] Among them, steps 3) to 6) are called the learning phase of the system; steps 7) to 12) are called the working phase of the system. It should be added that at the beginning of the system's use, it is necessary to input a known type of training set to the system throug...

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Abstract

The invention discloses a method for recognizing an image of a plant leaf. The method comprises a training stage and a recognition stage. The training stage comprises the following steps of: inputting an image training set of the plant leaf; and storing a training result after performing batch preprocessing, batch feature extraction and neural network classifier training by using a system. The recognition stage comprises the following steps of: allowing a user to input a single image of the plant leaf of which the variety is unknown to the system and mark the leaf base point coordinate and leaf apex point coordinate of the leaf; performing preprocessing and feature extraction on the single image by using the system; and classifying by using the neural network classifier, outputting a plant variety list and attaching detailed graphics and text information to each item of the list. The method has the advantages of outputting a plurality of high-accuracy candidate results, greatly enhancing recognition credibility, supporting a scalar quantity of leaf features as well as leaf features in complex forms (such as a matrix form) and increasing the recognition rate of the plant leaf.

Description

technical field [0001] The invention relates to the technical field of automatic plant classification, in particular to a method for identifying plant leaf images. Background technique [0002] Plants have been closely related to humans for thousands of years. With the progress of human civilization, plants have been damaged more and more seriously. Therefore, it is of great significance to identify and classify plants and establish a plant digital resource library to help protect plants. The plant leaf digital image machine recognition algorithm will undoubtedly greatly speed up the classification of plants. [0003] Due to the complex three-dimensional geometric features of flowers, fruits, stems and branches, the identification of leaves is relatively simple and effective for machines. Stephen Gang Wu et al. used a probabilistic neural network (PNN, full name Probabilistic Neural Network) to classify and identify plant leaves. Experiments show that the recognition rat...

Claims

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Application Information

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IPC IPC(8): G06K9/66G06N3/08
Inventor 高理文林小桦
Owner GUANGZHOU UNIVERSITY OF CHINESE MEDICINE
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