CN112699901A - Plant species identification system based on Internet of things - Google Patents
Plant species identification system based on Internet of things Download PDFInfo
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Abstract
The invention discloses a plant species identification system based on the Internet of things, which comprises: the system comprises an Internet of things control module, an identification module and a processing module, wherein the Internet of things control module is used for uniformly receiving the acquisition information of the identification module and the processing module, the Internet of things control module comprises an image quality identification and judgment unit, an image processing unit, an image coding unit and a user terminal, and the image quality identification and judgment unit is used for identifying and judging the image quality of the uploaded plant image; the image processing unit is used for acquiring the segmentation image containing the plant when the image quality of the plant image is qualified, replacing a basic operation method, improving the identification speed, improving the accuracy of the acquired information by using the image quality identification and judgment unit, the image processing unit and the image coding unit in a matched mode, and directly comparing the acquired related information by using the data comparison unit to quickly obtain the accurate data of the acquired information.
Description
Technical Field
The invention belongs to the technical field of plant species identification, and particularly relates to a plant species identification system based on the Internet of things.
Background
When going out, beautiful flowers, ambitious trees or other interesting plants are often seen, so that the user can stop watching and taking pictures, and few people know what the plants are while enjoying, so that the user can regret the situation. With the continuous development of the technology level, the technologies in the aspects of image information extraction, feature matching, machine learning, data mining, image searching and the like are improved to a great extent in recent years. Therefore, the technologies can be utilized to help a user to realize the rapid discrimination of the plant species and simultaneously give the detailed information of the plant, so that the user only needs to use a mobile phone to transmit a picture, upload the picture to the cloud end through the system for comparison, and can know the plant more comprehensively according to the returned data.
At present, there are also many recognition algorithms and systems for plant species, which are based on searching and segmenting local regions of an image, then performing comparison analysis on the local image to match plant species, so as to realize recognition of plant species, but these algorithms and systems have slow recognition speed and large recognition error rate.
Disclosure of Invention
The invention aims to provide a plant species identification system based on the Internet of things, and aims to solve the problems that the identification algorithms and the identification systems are based on searching and segmenting local regions of images, then comparing and analyzing the local images, matching plant species and realizing identification of plant species, but the algorithms and the identification systems are slow in identification speed and high in identification error rate.
In order to achieve the purpose, the invention adopts the following technical scheme:
a plant species identification system based on the Internet of things comprises: the plant image recognition and judgment system comprises a scanning device, and an Internet of things control module, an identification module and a processing module which are arranged at the top of the scanning device, wherein the Internet of things control module is used for uniformly receiving the acquisition information of the identification module and the processing module, the Internet of things control module comprises an image quality recognition and judgment unit, an image processing unit, an image coding unit and a user terminal, and the image quality recognition and judgment unit is used for recognizing and judging the image quality of the uploaded plant image; the image processing unit is used for processing the uploaded plant image to obtain a segmentation image containing plants when the image quality of the plant image is qualified;
the identification module comprises a preprocessing unit, a feature extraction unit and a classification identification unit, wherein the preprocessing unit, the feature extraction unit and the classification identification unit sequentially transmit extracted information to the Internet of things control module through the processing module, and the Internet of things control module provides identification results.
Preferably, the preprocessing unit is used for converting the plant image into a binary image; the feature extraction is used for extracting relative features in the images to form a feature data matrix; the classification recognition is used for constructing a neural network model based on deep learning, and the model adopts a five-layer BP neural network, wherein four layers are fully connected, and the last layer is a layer; the model is trained for subsequent plant identification.
Preferably, the image processing performed by the processing module comprises image graying, binarization, noise removal and feature extraction, and after the internet of things control module obtains the data, the internet of things control module compares the data with an originally established database of plant leaf image information, and compares the similarity between the acquired image and the leaf image in the database through an image retrieval algorithm, so as to identify the type of the identified plant leaf.
Preferably, the internet of things control module comprises a CPU main chip with a built-in RF front end, and the CPU main chip comprises an antenna, a matching network, a high pass filter HPF, a low pass filter LPF, a balancing network C13, L1, C3, a receiving port RFI, and a transmitting port RFO.
Preferably, the processing module analyzes the plant image received by the identification module to obtain basic information of the collected plant image, the basic information further includes brightness, contrast, definition and pixel value of the plant image, the obtained basic information of the plant image is compared with a data value converted from basic information stored in the internet of things control module in advance to judge whether the image quality of the obtained plant image is matched with the stored image, if so, a matching value is obtained, and when the matching value is greater than or equal to 99%, the plant information is obtained.
Preferably, the data to be collected by the identification module includes a circumference concave-convex ratio, an area concave-convex ratio, an eccentricity, a shape parameter, a circularity, a narrow length, a rectangularity, a circumference length-width ratio and the like of the plant leaf.
Preferably, the image encoding means encodes the acquired divided image including the plant, and generates the encoding vector parameter of the plant and the encoding vector parameter of each part of the plant included in the divided image.
Preferably, the internet of things control module further comprises a data comparison unit and a type feedback unit, wherein the data comparison unit is used for comparing the obtained coding vector parameters of the plant and the coding vector parameters of each part of the plant with pre-stored plant standard vector parameters, and finally determining related data of the type of the plant.
Preferably, the type feedback unit is configured to feed back the determined plant type to the user terminal, and display the plant type on the user terminal.
Preferably, scanning device includes rotatory stand and mounting panel, the mounting panel rotates and installs in the stand top, identification module fixed mounting is in the mounting panel upper surface, stand bottom fixed mounting has the bottom plate, bottom plate bottom surface annular equidistance array has the inserted bar.
Preferably, the stand is the extending structure setting, the stand is including having internal thread hollow tube and threaded connection in the threaded rod of hollow tube, threaded connection has lock nut on the threaded rod surface.
The invention has the technical effects and advantages that: compared with the prior art, the plant type identification system based on the Internet of things provided by the invention has the advantages that the Internet of things control module is used for providing more extensive atlas memory and plant information data, a basic operation method is replaced, the identification speed is improved, the image quality identification and judgment unit, the image processing unit and the image coding unit are used in a matched mode, the accuracy of collected information is improved, the data comparison unit is used for directly comparing the collected related information, and the accurate data of the collected information is quickly obtained.
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Fig. 1 is a system block diagram of a plant species identification system based on the internet of things;
fig. 2 is a schematic perspective view of a scanning device according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. The specific embodiments described herein are merely illustrative of the invention and do not delimit the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a plant type identification system based on the Internet of things, which comprises a scanning device 1, and an Internet of things control module, an identification module and a processing module which are arranged at the top of the scanning device 1, wherein the Internet of things control module uniformly receives the acquisition information of the identification module and the processing module, the Internet of things control module comprises an image quality identification and judgment unit, an image processing unit, an image coding unit and a user terminal, and the image quality identification and judgment unit is used for identifying and judging the image quality of an uploaded plant image; and the image processing unit is used for processing the uploaded plant image to obtain a segmentation image containing the plant when the image quality of the plant image is qualified.
The recognition module comprises a preprocessing unit, a feature extraction unit and a classification recognition unit, the preprocessing unit, the feature extraction unit and the classification recognition unit sequentially transmit the extracted information to the Internet of things control module through the processing module, and the Internet of things control module provides a recognition result.
Specifically, the preprocessing unit is used for converting the plant image into a binary image; extracting features, namely extracting relative features in the images to form a feature data matrix; classifying and identifying, wherein the classifying and identifying is used for constructing a neural network model based on deep learning, the model adopts a five-layer BP neural network, four layers are all connected, and the last layer is a layer; the model is trained for subsequent plant identification.
Specifically, the image processing performed by the processing module comprises image graying, binaryzation, noise removal and feature extraction, after the internet of things control module obtains the data, the data is compared with an originally established database of plant leaf image information, and the similarity between the acquired image and the leaf image in the database is compared through an image retrieval algorithm, so that the type of the identified plant leaf is identified.
Specifically, the internet of things control module comprises a main CPU chip with an RF front end, and includes an antenna, a matching network, a high pass filter HPF, a low pass filter LPF, a balancing network C13, L1, C3, a receiving port RFI, and a transmitting port RFO.
Specifically, the processing module analyzes the plant image received by the identification module, acquires basic information of the acquired plant image, the basic information further comprises brightness, contrast, definition and pixel values of the plant image, compares the acquired basic information of the plant image with a data value converted from basic information stored in the internet of things control module in advance, judges whether the image quality of the acquired plant image is matched with the stored image, obtains a matching value if the image quality of the acquired plant image is matched with the stored image, and acquires the plant information when the matching value is greater than or equal to 99%.
Specifically, the data to be acquired by the identification module includes a circumference concave-convex ratio, an area concave-convex ratio, an eccentricity, a shape parameter, a circularity, a narrow length, a rectangle degree, a circumference length-width ratio and the like of the plant leaf;
specifically, the image encoding means encodes the acquired divided image including the plant, and generates the encoding vector parameter of the plant and the encoding vector parameter of each part of the plant included in the divided image
Specifically, the internet of things control module further comprises a data comparison unit and a type feedback unit, the data comparison unit is used for comparing the obtained coding vector parameters of the plant and the coding vector parameters of each part of the plant with the pre-stored plant standard vector parameters to finally determine related data of the type of the plant, and the type feedback unit is used for feeding the determined plant type back to the user terminal and displaying the plant type on the user terminal.
Specifically, scanning device 1 includes rotatory stand 101 and mounting panel 102, and mounting panel 102 rotates and installs on stand 101 top, and identification module fixed mounting has bottom plate 103 in mounting panel 102 upper surface, and bottom plate 103 bottom fixed mounting has the inserted bar 104 in the equidistant array of bottom plate 103 bottom surface annular, and stand 101 is the extending structure setting, and stand 101 is including having internal thread hollow tube and threaded connection in the threaded rod in the hollow tube, and threaded connection has lock nut on the threaded rod surface.
The method and the device have the advantages that the Internet of things control module is used for providing wider atlas memory and plant information data, a basic operation method is replaced, the identification speed is improved, the image quality identification and judgment unit, the image processing unit and the image coding unit are used in a matched mode, the accuracy of collected information is improved, the data comparison unit is used for directly comparing the collected related information, and the accurate data of the collected information is obtained quickly.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the embodiments or portions thereof without departing from the spirit and scope of the invention.
Claims (10)
1. The utility model provides a plant species identification system based on thing networking, includes scanning device (1) and sets up in thing networking control module, identification module and the processing module at scanning device (1) top, its characterized in that: the Internet of things control module is used for receiving collected information of the identification module and the processing module in a unified mode, the Internet of things control module comprises an image quality identification and judgment unit, an image processing unit, an image coding unit and a user terminal, and the image quality identification and judgment unit is used for identifying and judging the image quality of the uploaded plant image; the image processing unit is used for processing the uploaded plant image to obtain a segmentation image containing plants when the image quality of the plant image is qualified;
the identification module comprises a preprocessing unit, a feature extraction unit and a classification identification unit, wherein the preprocessing unit, the feature extraction unit and the classification identification unit sequentially transmit extracted information to the Internet of things control module through the processing module, and the Internet of things control module provides identification results.
2. The plant species identification system based on the internet of things as claimed in claim 1, wherein: the preprocessing unit is used for converting the plant image into a binary image; the feature extraction is used for extracting relative features in the images to form a feature data matrix; the classification recognition is used for constructing a neural network model based on deep learning, and the model adopts a five-layer BP neural network, wherein four layers are fully connected, and the last layer is a layer; the model is trained for subsequent plant identification.
3. The plant species identification system based on the internet of things as claimed in claim 1, wherein: the image processing performed by the processing module comprises image graying, binaryzation, noise removal and feature extraction, after the Internet of things control module obtains the data, the data is compared with an originally established database of plant leaf image information, and the similarity between the acquired image and the leaf image in the database is compared through an image retrieval algorithm, so that the type of the identified plant leaf is identified.
4. The plant species identification system based on the internet of things as claimed in claim 1, wherein: the Internet of things control module comprises a CPU main chip with a built-in RF front end, and the CPU main chip comprises an antenna, a matching network, a high pass filter HPF, a low pass filter LPF, a balance network C13, L1, C3, a receiving port RFI and a transmitting port RFO.
5. The plant species identification system based on the internet of things as claimed in claim 1, wherein: the processing module analyzes the plant image received by the identification module to acquire basic information of the acquired plant image, the basic information further comprises brightness, contrast, definition and pixel values of the plant image, the acquired basic information of the plant image is compared with a data value which is stored in advance and converted from the basic information of the Internet of things control module to judge whether the image quality of the acquired plant image is matched with the stored image, if so, a matching value is obtained, and when the matching value is greater than or equal to 99%, the plant information is acquired.
6. The plant species identification system based on the internet of things as claimed in claim 1, wherein: the data needing to be collected by the identification module comprise the circumference concave-convex ratio, the area concave-convex ratio, the eccentricity, the shape parameter, the circularity, the narrow length, the rectangularity, the circumference length-width ratio and the like of the plant leaf.
7. The plant species identification system based on the internet of things as claimed in claim 1, wherein: the image encoding means encodes the acquired divided image including the plant, and generates a coding vector parameter of the plant and coding vector parameters of each part of the plant included in the divided image.
8. The plant species identification system based on the internet of things as claimed in claim 1, wherein: the Internet of things control module further comprises a data comparison unit and a type feedback unit, wherein the data comparison unit is used for comparing the obtained coding vector parameters of the plant and the coding vector parameters of all parts of the plant with pre-stored plant standard vector parameters to finally determine related data of the type of the plant, and the type feedback unit is used for feeding back the determined plant type to the user terminal and displaying the plant type on the user terminal.
9. The plant species identification system based on the internet of things as claimed in claim 1, wherein: scanning device (1) is including rotatory stand (101) and mounting panel (102), mounting panel (102) are rotated and are installed in stand (101) top, identification module fixed mounting is in mounting panel (102) upper surface, stand (101) bottom fixed mounting has bottom plate (103), bottom plate (103) bottom surface annular equidistant array has inserted bar (104).
10. The internet of things-based plant species identification system of claim 9, wherein: stand (101) are extending structure setting, stand (101) are including having internal thread hollow tube and threaded connection in the threaded rod of hollow tube, threaded connection has lock nut on the threaded rod surface.
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| CN114328630A (en) * | 2022-01-24 | 2022-04-12 | 嘉应学院 | Equipment identification system based on thing networking |
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