CN109871455B - Color separation method and system for carbonized bamboo chips - Google Patents
Color separation method and system for carbonized bamboo chips Download PDFInfo
- Publication number
- CN109871455B CN109871455B CN201910079753.9A CN201910079753A CN109871455B CN 109871455 B CN109871455 B CN 109871455B CN 201910079753 A CN201910079753 A CN 201910079753A CN 109871455 B CN109871455 B CN 109871455B
- Authority
- CN
- China
- Prior art keywords
- carbonized bamboo
- color
- bamboo chips
- image data
- color separation
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Landscapes
- Image Analysis (AREA)
- Spectrometry And Color Measurement (AREA)
Abstract
The invention discloses a color separation method and system for carbonized bamboo chips. Wherein the method comprises the following steps: collecting color image data samples of historical carbonized bamboo chips, establishing a color separation model based on the color image data of the carbonized bamboo chips according to the collected color image data samples of the historical carbonized bamboo chips, carrying out color separation on the current carbonized bamboo chips according to the established color separation model based on the color image data of the carbonized bamboo chips, and screening out the carbonized bamboo chips with inconsistent colors in the current carbonized bamboo chips according to the color separation result of the color separation on the current carbonized bamboo chips. In this way, can realize need not the manual work and can carry out the colour separation to the carbonization bamboo chip automatically, improve colour separation efficiency and colour separation rate of accuracy, the colour uniformity ability of the carbonization bamboo chip after automatic colour separation obtains the guarantee, can ensure the colour quality of bamboo product.
Description
Technical Field
The invention relates to the technical field of carbonized bamboos, in particular to a color separation method and system for carbonized bamboo chips.
Background
Bamboo is a branch of gramineae, is perennial, has various varieties, is distributed in tropical, subtropical and warm-warm areas, has the reputation of bamboo kingdom in China, and is rich in bamboo resources. According to statistics, the area of the bamboo forest in the world is about 2200 million hectares, while the area of the bamboo forest in China is 720 million hectares, which accounts for about one third, and is second in the world and only second in India. More than 70 genus and 1200 species of global bamboo plants; however, there are about 35 bamboo plants in China, nearly 400. The annual output of the bamboo forest all over the world is 1600 ten thousand tons, and the annual output of the bamboo forest in China reaches over 800 ten thousand tons and almost accounts for half of the world bamboo output; is the first place in the world. So in our country, bamboo is also called "second forest". The area distribution of the moso bamboo in the bamboo forest area in China is the largest, and the range is the widest. Wherein, the bamboo forest area of Fujian, Jiangxi and Zhejiang provinces occupies half of the whole country.
With the improvement of living standard, bamboo product industries such as bamboo sheet summer sleeping mat, bamboo sheet artistic engineering and bamboo sheet building are becoming hot points of public attention, however, when developing bamboo products, the problems of 'mildew, rot and moth damage' of bamboo materials, namely three-proofing treatment of mildew resistance, corrosion resistance and moth resistance, must be solved firstly. The bamboo material has a composition similar to wood, and the main components of bamboo material are cellulose, hemicellulose and lignin, and contain proteins, fats, various saccharides and a small amount of ash elements.
Carbonization, also known as dry distillation, carbonization, and coking, refers to a process of heating and decomposing a solid or organic substance in the absence of air or heating a solid substance to produce a liquid or gas, which is usually converted into a solid product. The carbonization process does not necessarily involve cracking or pyrolysis, and the product is collected after condensation. The carbonization process requires higher temperatures than usual distillation, with which liquid fuels can be extracted from charcoal or wood. Carbonization can also decompose mineral salts by pyrolysis, for example, dry distillation of sulfate can produce sulfur dioxide and sulfur trioxide, which can be dissolved in water to produce sulfuric acid; carbonizing coal to obtain coke, coal tar, coarse ammonia water and coal gas; carbonizing the bamboo chips to obtain the carbonized bamboo chips.
The principle of carbonizing the bamboo chips is that sugar in the bamboo chips is burnt off at high temperature, so that the processed bamboo chips are not easy to be bitten by insects, and the color, the natural color and the dark color are not different but are colored. The carbonized bamboo chips are not cracked after carbonization and dehydration, while the natural bamboo chips, namely the original bamboo, are cracked.
Before the processing of the bamboo products on the next step, the colors of the carbonized bamboo chips must be subjected to color separation, otherwise, the color consistency of the bamboo products cannot be ensured.
The existing scheme for separating colors of the carbonized bamboo chips mainly depends on a mode of manual visual identification to separate the colors of the carbonized bamboo chips, has high labor intensity and low color separation and screening efficiency, particularly, the human eyes carry out monotonous saccadic examination for a long time, so that visual fatigue is easily generated, and the increase of misjudgment and omission inspection is easier. The color consistency of the carbonized bamboo chips after manual color separation screening is difficult to be ensured, and the color quality of bamboo products cannot be ensured.
However, the inventors found that at least the following problems exist in the prior art:
the scheme of current carbonization bamboo chip colour separation mainly relies on artifical naked eye discernment's mode to carry out the colour separation screening to the carbonization bamboo chip, and intensity of labour is big, and colour separation screening efficiency is low, and easy erroneous judgement and hourglass are examined, and the colour uniformity of the carbonization bamboo chip after artifical colour separation screening is difficult to obtain the guarantee, can't ensure the colour quality of bamboo product.
Disclosure of Invention
In view of this, the present invention provides a method and a system for separating colors of carbonized bamboo chips, which can automatically separate colors of the carbonized bamboo chips without manual work, thereby improving color separation efficiency and color separation accuracy, ensuring color consistency of the carbonized bamboo chips after automatic color separation, and ensuring color quality of bamboo products.
According to an aspect of the present invention, there is provided a carbonized bamboo chip color separation method, including:
collecting color image data samples of historical carbonized bamboo chips; the color image data sample of the historical carbonized bamboo chip comprises image information of various colors of the carbonized bamboo chip and corresponding color type labels;
establishing a color separation model based on the color image data of the carbonized bamboo chips according to the collected color image data samples of the historical carbonized bamboo chips;
according to the established color separation model based on the color image data of the carbonized bamboo chips, performing color separation on the current carbonized bamboo chips;
and screening out the carbonized bamboo chips with inconsistent colors in the current carbonized bamboo chips according to the color separation result of color separation of the current carbonized bamboo chips.
Wherein, according to the color image data sample of the historical carbonized bamboo chips, establishing a color separation model based on the color image data of the carbonized bamboo chips, comprising:
acquiring image information of various colors of the carbonized bamboo chips in the color image data sample of the historical carbonized bamboo chips and corresponding color type labels according to the acquired color image data sample of the historical carbonized bamboo chips;
dividing the image information of various colors of the carbonized bamboo chips in the obtained color image data sample of the historical carbonized bamboo chips and the corresponding color type labels into N sections; wherein N is a natural number greater than 1;
extracting the image information of the various colors of the carbonized bamboo chips divided into the N sections and the time weighting characteristics of the corresponding color type labels through a convolutional neural network;
obtaining image information of various colors of the carbonized bamboo chips divided into N sections and multi-scale characteristics of corresponding color type labels according to the extracted time weighting characteristics;
fusing image information of various colors of the carbonized bamboo chips in the obtained color image data samples of the N sections of historical carbonized bamboo chips and the multi-scale characteristics of the corresponding color type labels, and calculating a prediction score;
obtaining the final classification of the color image data samples related to the collected historical carbonized bamboo chips according to the calculated prediction scores;
obtaining training characteristics of the color image data samples related to the collected historical carbonized bamboo chips according to the obtained classification of the color image data samples related to the collected historical carbonized bamboo chips;
and performing model training according to the obtained training characteristics associated with the collected historical carbonized bamboo chip color image data samples, and establishing a color separation model based on the carbonized bamboo chip color image data.
Wherein, according to the color separation model of the color image data based on the carbonized bamboo chips, color separation is carried out on the current carbonized bamboo chips, and the color separation comprises the following steps:
matching training characteristics of current carbonized bamboo chip image information from the established color separation model of the color image data based on the carbonized bamboo chips according to the established color separation model of the color image data based on the carbonized bamboo chips, and performing color separation on the current carbonized bamboo chip image information by adopting a mode of training the current carbonized bamboo chip image information by the matched training characteristics to perform color separation on the current carbonized bamboo chip image information and perform color separation on the current carbonized bamboo chip.
Wherein, according to the colour separation result of colour separation is carried out to current carbonization bamboo chip, screen out the carbonization bamboo chip that the colour is inconsistent in the current carbonization bamboo chip, include:
and prompting the color separation result in a labeling mode according to the color separation result of color separation of the current carbonized bamboo chips, and screening the carbonized bamboo chips with inconsistent colors in the current carbonized bamboo chips according to the prompted color separation result.
Wherein, before the acquiring the color image data sample of the historical carbonized bamboo chips, the method further comprises the following steps:
and generating a color type label corresponding to the obtained color image information of the carbonized bamboo chips according to the obtained color image information of the carbonized bamboo chips.
According to another aspect of the present invention, there is provided a carbonized bamboo chip color separation system comprising:
the device comprises a collecting unit, an establishing unit, a color separation unit and a screening unit;
the acquisition unit is used for acquiring color image data samples of historical carbonized bamboo chips; the color image data sample of the historical carbonized bamboo chip comprises image information of various colors of the carbonized bamboo chip and corresponding color type labels;
the establishing unit is used for establishing a color separation model based on the color image data of the carbonized bamboo chips according to the collected color image data samples of the historical carbonized bamboo chips;
the color separation unit is used for carrying out color separation on the current carbonized bamboo chips according to the established color separation model based on the color image data of the carbonized bamboo chips;
and the screening unit is used for screening the carbonized bamboo chips with inconsistent colors in the current carbonized bamboo chips according to the color separation result of color separation of the current carbonized bamboo chips.
Wherein, the establishing unit is specifically configured to:
acquiring image information of various colors of the carbonized bamboo chips in the color image data sample of the historical carbonized bamboo chips and corresponding color type labels according to the acquired color image data sample of the historical carbonized bamboo chips;
dividing the image information of various colors of the carbonized bamboo chips in the obtained color image data sample of the historical carbonized bamboo chips and the corresponding color type labels into N sections; wherein N is a natural number greater than N;
extracting the image information of the various colors of the carbonized bamboo chips divided into the N sections and the time weighting characteristics of the corresponding color type labels through a convolutional neural network;
obtaining image information of various colors of the carbonized bamboo chips divided into N sections and multi-scale characteristics of corresponding color type labels according to the extracted time weighting characteristics;
fusing image information of various colors of the carbonized bamboo chips in the obtained color image data samples of the N sections of historical carbonized bamboo chips and the multi-scale characteristics of the corresponding color type labels, and calculating a prediction score;
obtaining the final classification of the color image data samples related to the collected historical carbonized bamboo chips according to the calculated prediction scores;
obtaining training characteristics of the color image data samples related to the collected historical carbonized bamboo chips according to the obtained classification of the color image data samples related to the collected historical carbonized bamboo chips;
and performing model training according to the obtained training characteristics associated with the collected historical carbonized bamboo chip color image data samples, and establishing a color separation model based on the carbonized bamboo chip color image data.
The color separation unit is specifically configured to:
matching training characteristics of current carbonized bamboo chip image information from the established color separation model of the color image data based on the carbonized bamboo chips according to the established color separation model of the color image data based on the carbonized bamboo chips, and performing color separation on the current carbonized bamboo chip image information by adopting a mode of training the current carbonized bamboo chip image information by the matched training characteristics to perform color separation on the current carbonized bamboo chip image information and perform color separation on the current carbonized bamboo chip.
Wherein, the screening unit is specifically configured to:
and prompting the color separation result in a labeling mode according to the color separation result of color separation of the current carbonized bamboo chips, and screening the carbonized bamboo chips with inconsistent colors in the current carbonized bamboo chips according to the prompted color separation result.
Wherein, carbonization bamboo chip colour separation system still includes:
the generating unit is used for acquiring the color image information of the carbonized bamboo chips after the color separation process of the carbonized bamboo chips is finished, and generating the color type labels corresponding to the color image information of the acquired carbonized bamboo chips according to the acquired color image information of the carbonized bamboo chips.
It can be found that, by the above scheme, a color image data sample of a historical carbonized bamboo strip can be collected, wherein the color image data sample of the historical carbonized bamboo strip comprises image information of multiple colors of the carbonized bamboo strip and corresponding color type labels, a color separation model based on the color image data of the carbonized bamboo strip is established according to the collected color image data sample of the historical carbonized bamboo strip, a color separation model based on the color image data of the carbonized bamboo strip is established according to the established color separation model based on the color image data of the carbonized bamboo strip, the current carbonized bamboo strip is subjected to color separation, and a carbonized bamboo strip with inconsistent color in the current carbonized bamboo strip is screened according to a color separation result of the color separation of the current carbonized bamboo strip, so that the color separation of the carbonized bamboo strip without manual work can be realized, the color separation efficiency and the color separation accuracy are improved, and the color consistency of the carbonized bamboo strip subjected to automatic color separation can be ensured, can ensure the color quality of bamboo products.
Further, the above scheme may obtain image information of multiple colors of carbonized bamboo chips in the color image data sample of the historical carbonized bamboo chips and corresponding color type labels according to the collected color image data sample of the historical carbonized bamboo chips, divide the image information of multiple colors of carbonized bamboo chips and corresponding color type labels in the color image data sample of the historical carbonized bamboo chips into N segments, where N is a natural number greater than 1, extract time weighting features of the image information of multiple colors of the carbonized bamboo chips and corresponding color type labels after being divided into N segments through a convolutional neural network, and obtain multi-scale features of the image information of multiple colors of the carbonized bamboo chips and corresponding color type labels after being divided into N segments according to the extracted time weighting features, and fusing image information of multiple colors of the obtained carbonized bamboo chips in the color image data samples of the N sections of historical carbonized bamboo chips and the multi-scale characteristics of the corresponding color type labels to calculate a prediction score, and obtaining a final classification of color image data samples related to the collected historical carbonized bamboo chips according to the calculated prediction score, and obtaining training characteristics of the color image data samples related to the collected historical carbonized bamboo chips according to the obtained classification of the color image data samples related to the collected historical carbonized bamboo chips, and performing model training according to the obtained training characteristics associated with the collected historical color image data samples of the carbonized bamboo chips, and establishing a color separation model based on the color image data of the carbonized bamboo chips, so that the modeling effect and accuracy of establishing the color separation model based on the color image data of the carbonized bamboo chips can be improved.
Furthermore, according to the scheme, the training characteristics of the current carbonized bamboo chip image information can be matched from the established color separation model of the color image data based on the carbonized bamboo chips, the training characteristics of the current carbonized bamboo chip image information are trained by adopting the matched training characteristics, the color separation is carried out on the current carbonized bamboo chip image information, the color separation is carried out on the current carbonized bamboo chip, and the color separation efficiency and the accuracy of the color separation result of the current carbonized bamboo chip image information can be effectively improved.
Further, above scheme can adopt the mark mode to indicate this colour separation result according to this colour separation result of colour separation to current carbonization bamboo chip, according to the colour separation result of this suggestion, screens off the inconsistent carbonization bamboo chip of colour in the current carbonization bamboo chip, can realize improving automatic hourglass rate of examining the colour separation to the carbonization bamboo chip through the mark mode, improves the color quality guarantee of the carbonization bamboo chip after the colour separation to improve the color quality of bamboo product.
Furthermore, according to the scheme, after the color separation process of the carbonized bamboo chips is completed, the color image information of the carbonized bamboo chips can be obtained, and the color type labels corresponding to the obtained color image information of the carbonized bamboo chips are generated according to the obtained color image information of the carbonized bamboo chips, so that the construction efficiency of establishing the color separation model based on the color image data of the carbonized bamboo chips can be effectively improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of an embodiment of a method for color separation of carbonized bamboo chips according to the present invention;
FIG. 2 is a schematic flow chart of another embodiment of the method for color separation of carbonized bamboo chips according to the present invention;
FIG. 3 is a schematic structural view of an embodiment of the carbonized bamboo chip color separation system of the present invention;
FIG. 4 is a schematic structural view of another embodiment of a carbonized bamboo sheet color separation system of the present invention;
fig. 5 is a schematic structural view of another embodiment of the carbonized bamboo sheet color separation system of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be noted that the following examples are only illustrative of the present invention, and do not limit the scope of the present invention. Similarly, the following examples are only some but not all examples of the present invention, and all other examples obtained by those skilled in the art without any inventive work are within the scope of the present invention.
The invention provides a color separation method for carbonized bamboo chips, which can automatically separate the colors of the carbonized bamboo chips without manual work, improves the color separation efficiency and the color separation accuracy, ensures the color consistency of the carbonized bamboo chips subjected to automatic color separation, and can ensure the color quality of bamboo products.
Referring to fig. 1, fig. 1 is a schematic flow chart of a color separation method for carbonized bamboo chips according to an embodiment of the present invention. It should be noted that the method of the present invention is not limited to the flow sequence shown in fig. 1 if the results are substantially the same. As shown in fig. 1, the method comprises the steps of:
s101: collecting color image data samples of historical carbonized bamboo chips; the color image data sample of the historical carbonized bamboo chips comprises image information of various colors of the carbonized bamboo chips and corresponding color type labels.
Before the acquiring of the color image data sample of the historical carbonized bamboo chips, the method may further include:
and generating a color type label corresponding to the obtained color image information of the carbonized bamboo chips according to the obtained color image information of the carbonized bamboo chips.
In this embodiment, an electronic device, such as a server, on which the carbonized bamboo piece color separation method operates may collect color image data samples of historical carbonized bamboo pieces from a terminal device with which a tester logs in by a wired connection manner or a wireless connection manner.
In the present embodiment, the terminal device may be various electronic terminals including but not limited to a smart phone, a tablet computer, a laptop portable computer, a desktop computer, and the like, which have a camera and various sensors including but not limited to light-sensitive, distance, gravity, acceleration, magnetic induction, and the like.
In this embodiment, the electronic device may be a server providing various services, for example, a backend login server providing support for a color image data login interface of the carbonized bamboo chips displayed on the terminal device, and the backend login server may analyze and perform processing on data such as color image data of the historical carbonized bamboo chips and color image data of the current carbonized bamboo chips, and feed back a processing result, for example, suggestion information recommended to a color separator for reference, to the terminal device.
In this embodiment, the color separator may use the terminal device to interact with an electronic device, such as a server, over a network to receive or send messages or the like. The terminal device can be installed with various client applications needing to verify color separator information, such as a carbonized bamboo chip application, an instant messaging tool, a mailbox client, carbonized bamboo chip platform software, a color image application and the like.
S102: and establishing a color separation model based on the color image data of the carbonized bamboo chips according to the collected color image data samples of the historical carbonized bamboo chips.
Wherein, should establish the colour separation model based on the colour image data of carbonization bamboo chip according to the colour image data sample of this historical carbonization bamboo chip of gathering, can include:
acquiring image information of various colors of the carbonized bamboo chips in the color image data sample of the historical carbonized bamboo chips and corresponding color type labels according to the acquired color image data sample of the historical carbonized bamboo chips;
dividing the image information of various colors of the carbonized bamboo chips in the obtained color image data sample of the historical carbonized bamboo chips and the corresponding color type labels into N sections; wherein N is a natural number greater than 1;
extracting the image information of the various colors of the carbonized bamboo chips divided into the N sections and the time weighting characteristics of the corresponding color type labels through a convolutional neural network;
obtaining image information of various colors of the carbonized bamboo chips divided into N sections and multi-scale characteristics of corresponding color type labels according to the extracted time weighting characteristics;
fusing the image information of various colors of the carbonized bamboo chips in the obtained color image data samples of the N sections of historical carbonized bamboo chips and the multi-scale characteristics of the corresponding color type labels, and calculating a prediction score;
obtaining a final classification of color image data samples related to the collected historical carbonized bamboo chips according to the calculated prediction score;
obtaining training characteristics of the color image data samples related to the collected historical carbonized bamboo chips according to the obtained classification of the color image data samples related to the collected historical carbonized bamboo chips;
and performing model training according to the obtained training characteristics of the color image data sample associated with the collected historical carbonized bamboo chips, and establishing a color separation model based on the color image data of the carbonized bamboo chips.
In the present embodiment, the convolutional neural network is a kind of feedforward neural network that includes convolutional calculation and has a deep structure, and is one of the representative algorithms of deep learning.
In this embodiment, the convolutional neural network may include: at least one three-dimensional convolutional layer, at least one three-dimensional pooling layer, at least one fully-connected layer, and the like.
S103: and carrying out color separation on the current carbonized bamboo chips according to the established color separation model based on the color image data of the carbonized bamboo chips.
Wherein, this colour separation model according to this color separation based on carbonization bamboo chip's colour image data of establishing carries out the colour separation to current carbonization bamboo chip, can include:
matching training characteristics of current carbonized bamboo chip image information from the established color separation model based on the color image data of the carbonized bamboo chips according to the established color separation model based on the color image data of the carbonized bamboo chips, and carrying out color separation on the current carbonized bamboo chip image information by adopting a mode of training the current carbonized bamboo chip image information by adopting the matched training characteristics, thereby carrying out color separation on the current carbonized bamboo chip image information.
In this embodiment, the current carbonized bamboo chip image information may be image information of a current target carbonized bamboo chip, and the present invention is not limited thereto.
S104: and screening out the carbonized bamboo chips with inconsistent colors in the current carbonized bamboo chips according to the color separation result of color separation of the current carbonized bamboo chips.
Wherein, should carry out the colour separation result of colour separation according to this present carbonization bamboo chip, screen out the carbonization bamboo chip that the colour is inconsistent in the present carbonization bamboo chip, can include:
and prompting the color separation result in a labeling mode according to the color separation result of color separation of the current carbonized bamboo chips, and screening the carbonized bamboo chips with inconsistent colors in the current carbonized bamboo chips according to the prompted color separation result.
It can be found that, in this embodiment, a color image data sample of a historical carbonized bamboo strip may be collected, where the color image data sample of the historical carbonized bamboo strip includes image information of multiple colors of the carbonized bamboo strip and a corresponding color type label, a color separation model based on the color image data of the carbonized bamboo strip is established according to the collected color image data sample of the historical carbonized bamboo strip, a color separation model based on the color image data of the carbonized bamboo strip is established according to the established color separation model based on the color image data of the carbonized bamboo strip, a color separation is performed on a current carbonized bamboo strip, and a color separation result of the color separation performed on the current carbonized bamboo strip is used to screen out a carbonized bamboo strip with inconsistent color in the current carbonized bamboo strip, so that the color separation of the carbonized bamboo strip without manual work can be automatically performed, the color separation efficiency and the color separation accuracy are improved, and the color consistency of the carbonized bamboo strip after automatic color separation is ensured, can ensure the color quality of bamboo products.
Further, in this embodiment, the image information of multiple colors of the carbonized bamboo chips in the color image data sample of the historical carbonized bamboo chips and the corresponding color type labels may be obtained according to the collected color image data sample of the historical carbonized bamboo chips, the image information of multiple colors of the carbonized bamboo chips and the corresponding color type labels in the color image data sample of the historical carbonized bamboo chips are divided into N segments, where N is a natural number greater than 1, the time weighting characteristics of the image information of multiple colors of the carbonized bamboo chips and the corresponding color type labels after being divided into N segments are extracted through a convolutional neural network, and the multi-scale characteristics of the image information of multiple colors of the carbonized bamboo chips and the corresponding color type labels after being divided into N segments are obtained according to the extracted time weighting characteristics, and fusing image information of multiple colors of the obtained carbonized bamboo chips in the color image data samples of the N sections of historical carbonized bamboo chips and the multi-scale characteristics of the corresponding color type labels to calculate a prediction score, and obtaining a final classification of color image data samples related to the collected historical carbonized bamboo chips according to the calculated prediction score, and obtaining training characteristics of the color image data samples related to the collected historical carbonized bamboo chips according to the obtained classification of the color image data samples related to the collected historical carbonized bamboo chips, and performing model training according to the obtained training characteristics associated with the collected historical color image data samples of the carbonized bamboo chips, and establishing a color separation model based on the color image data of the carbonized bamboo chips, so that the modeling effect and accuracy of establishing the color separation model based on the color image data of the carbonized bamboo chips can be improved.
Further, in this embodiment, training features of the current carbonized bamboo chip image information may be matched from the color separation model of the color image data based on the carbonized bamboo chips according to the color separation model of the color image data based on the carbonized bamboo chips, and the color separation of the current carbonized bamboo chip image information may be performed by training the current carbonized bamboo chip image information using the matched training features, so as to effectively improve the color separation efficiency and accuracy of the color separation result of the current carbonized bamboo chip image information.
Further, in this embodiment, can adopt the mark mode to indicate this colour separation result according to this colour separation result of colour separation to current carbonization bamboo chip, according to the colour separation result of this suggestion, screen off the inconsistent carbonization bamboo chip of colour in the current carbonization bamboo chip, can realize improving automatic hourglass inspection rate of carrying out the colour separation to the carbonization bamboo chip through the mark mode, improve the color quality guarantee of the carbonization bamboo chip after the colour separation to improve the color quality of bamboo product.
Referring to fig. 2, fig. 2 is a schematic flow chart of another embodiment of a method for separating colors of carbonized bamboo chips according to the present invention. In this embodiment, the method includes the steps of:
s201: and generating a color type label corresponding to the obtained color image information of the carbonized bamboo chips according to the obtained color image information of the carbonized bamboo chips.
S202: collecting color image data samples of historical carbonized bamboo chips; the color image data sample of the historical carbonized bamboo chips comprises image information of various colors of the carbonized bamboo chips and corresponding color type labels.
As described above in S101, further description is omitted here.
S203: and establishing a color separation model based on the color image data of the carbonized bamboo chips according to the collected color image data samples of the historical carbonized bamboo chips.
As described above in S102, further description is omitted here.
S204: and carrying out color separation on the current carbonized bamboo chips according to the established color separation model based on the color image data of the carbonized bamboo chips.
As described above in S103, which is not described herein.
S205: and screening out the carbonized bamboo chips with inconsistent colors in the current carbonized bamboo chips according to the color separation result of color separation of the current carbonized bamboo chips.
As described above in S104, and will not be described herein.
It can be found that, in this embodiment, after the color separation process of the carbonized bamboo chips is completed, the color image information of the carbonized bamboo chips may be obtained, and the color type labels corresponding to the obtained color image information of the carbonized bamboo chips may be generated according to the obtained color image information of the carbonized bamboo chips, so that the efficiency of constructing the color separation model based on the color image data of the carbonized bamboo chips may be effectively improved.
The invention also provides a color separation system for the carbonized bamboo chips, which can automatically separate the colors of the carbonized bamboo chips without manpower, improve the color separation efficiency and the color separation accuracy, ensure the color consistency of the carbonized bamboo chips subjected to automatic color separation and ensure the color quality of bamboo products.
Referring to fig. 3, fig. 3 is a schematic structural view of an embodiment of a carbonized bamboo chip color separation system according to the present invention. In this embodiment, the carbonized bamboo strip color separation system 30 includes a collecting unit 31, a creating unit 32, a color separation unit 33, and a screening unit 34.
The acquisition unit 31 is used for acquiring color image data samples of historical carbonized bamboo chips; the color image data sample of the historical carbonized bamboo chips comprises image information of various colors of the carbonized bamboo chips and corresponding color type labels.
The establishing unit 32 is configured to establish a color separation model based on the color image data of the carbonized bamboo chips according to the collected color image data samples of the historical carbonized bamboo chips.
The color separation unit 33 is configured to perform color separation on the current carbonized bamboo strip according to the established color separation model based on the color image data of the carbonized bamboo strip.
The screening unit 34 is configured to screen out the carbonized bamboo strips with inconsistent colors from the current carbonized bamboo strips according to the color separation result obtained by color separation of the current carbonized bamboo strips.
Optionally, the establishing unit 32 may be specifically configured to:
acquiring image information of various colors of the carbonized bamboo chips in the color image data sample of the historical carbonized bamboo chips and corresponding color type labels according to the acquired color image data sample of the historical carbonized bamboo chips;
dividing the image information of various colors of the carbonized bamboo chips in the obtained color image data sample of the historical carbonized bamboo chips and the corresponding color type labels into N sections; wherein N is a natural number greater than 1;
extracting the image information of the various colors of the carbonized bamboo chips divided into the N sections and the time weighting characteristics of the corresponding color type labels through a convolutional neural network;
obtaining image information of various colors of the carbonized bamboo chips divided into N sections and multi-scale characteristics of corresponding color type labels according to the extracted time weighting characteristics;
fusing the image information of various colors of the carbonized bamboo chips in the obtained color image data samples of the N sections of historical carbonized bamboo chips and the multi-scale characteristics of the corresponding color type labels, and calculating a prediction score;
obtaining a final classification of color image data samples related to the collected historical carbonized bamboo chips according to the calculated prediction score;
obtaining training characteristics of the color image data samples related to the collected historical carbonized bamboo chips according to the obtained classification of the color image data samples related to the collected historical carbonized bamboo chips;
and performing model training according to the obtained training characteristics of the color image data sample associated with the collected historical carbonized bamboo chips, and establishing a color separation model based on the color image data of the carbonized bamboo chips.
Alternatively, the color separation unit 33 may be specifically configured to:
matching training characteristics of current carbonized bamboo chip image information from the established color separation model based on the color image data of the carbonized bamboo chips according to the established color separation model based on the color image data of the carbonized bamboo chips, and carrying out color separation on the current carbonized bamboo chip image information by adopting a mode of training the current carbonized bamboo chip image information by adopting the matched training characteristics, thereby carrying out color separation on the current carbonized bamboo chip image information.
Optionally, the screening unit 34 may be specifically configured to:
and prompting the color separation result in a labeling mode according to the color separation result of color separation of the current carbonized bamboo chips, and screening the carbonized bamboo chips with inconsistent colors in the current carbonized bamboo chips according to the prompted color separation result.
Referring to fig. 4, fig. 4 is a schematic structural view of another embodiment of a carbonized bamboo sheet color separation system according to the present invention. Different from the previous embodiment, the color separation system 40 of the carbonized bamboo chips in this embodiment further includes: the unit 41 is generated.
The generating unit 41 is configured to obtain color image information of the carbonized bamboo chips after color separation of the carbonized bamboo chips is completed, and generate a color type label corresponding to the obtained color image information of the carbonized bamboo chips according to the obtained color image information of the carbonized bamboo chips.
Referring to fig. 5, fig. 5 is a schematic structural view of another embodiment of a carbonized bamboo sheet color separation system according to the present invention. The unit modules of the carbonized bamboo chip color separation system can respectively execute the corresponding steps in the method embodiments. For a detailed description of the above method, please refer to the above method, which is not repeated herein.
In this embodiment, the carbonized bamboo chip color separation system includes: a processor 51, a memory 52 coupled to the processor 51, a color separator 53, and a filter 54.
The processor 51 is configured to, after a color separation process of the carbonized bamboo chips is completed, obtain color image information of the carbonized bamboo chips, generate a color type label corresponding to the obtained color image information of the carbonized bamboo chips according to the obtained color image information of the carbonized bamboo chips, collect a color image data sample of historical carbonized bamboo chips, where the color image data sample of the historical carbonized bamboo chips includes image information of multiple colors of the carbonized bamboo chips and corresponding color type labels, and establish a color separation model based on the color image data of the carbonized bamboo chips according to the collected color image data sample of the historical carbonized bamboo chips.
The memory 52 is used for storing an operating system, instructions executed by the processor 51, and the like.
The color separator 53 is configured to perform color separation on the current carbonized bamboo chips according to the established color separation model based on the color image data of the carbonized bamboo chips.
The screening device 54 is configured to screen out the carbonized bamboo strips with inconsistent colors from the current carbonized bamboo strips according to the color separation result obtained by color separation of the current carbonized bamboo strips.
Optionally, the processor 51 may be specifically configured to:
acquiring image information of various colors of the carbonized bamboo chips in the color image data sample of the historical carbonized bamboo chips and corresponding color type labels according to the acquired color image data sample of the historical carbonized bamboo chips;
dividing the image information of various colors of the carbonized bamboo chips in the obtained color image data sample of the historical carbonized bamboo chips and the corresponding color type labels into N sections; wherein N is a natural number greater than 1;
extracting the image information of the various colors of the carbonized bamboo chips divided into the N sections and the time weighting characteristics of the corresponding color type labels through a convolutional neural network;
obtaining image information of various colors of the carbonized bamboo chips divided into N sections and multi-scale characteristics of corresponding color type labels according to the extracted time weighting characteristics;
fusing the image information of various colors of the carbonized bamboo chips in the obtained color image data samples of the N sections of historical carbonized bamboo chips and the multi-scale characteristics of the corresponding color type labels, and calculating a prediction score;
obtaining a final classification of color image data samples related to the collected historical carbonized bamboo chips according to the calculated prediction score;
obtaining training characteristics of the color image data samples related to the collected historical carbonized bamboo chips according to the obtained classification of the color image data samples related to the collected historical carbonized bamboo chips;
and performing model training according to the obtained training characteristics of the color image data sample associated with the collected historical carbonized bamboo chips, and establishing a color separation model based on the color image data of the carbonized bamboo chips.
Optionally, the color separator 53 may be specifically configured to:
matching training characteristics of current carbonized bamboo chip image information from the established color separation model based on the color image data of the carbonized bamboo chips according to the established color separation model based on the color image data of the carbonized bamboo chips, and carrying out color separation on the current carbonized bamboo chip image information by adopting a mode of training the current carbonized bamboo chip image information by adopting the matched training characteristics, thereby carrying out color separation on the current carbonized bamboo chip image information.
Optionally, the filter 54 may be specifically configured to:
and prompting the color separation result in a labeling mode according to the color separation result of color separation of the current carbonized bamboo chips, and screening the carbonized bamboo chips with inconsistent colors in the current carbonized bamboo chips according to the prompted color separation result.
It can be found that, by the above scheme, a color image data sample of a historical carbonized bamboo strip can be collected, wherein the color image data sample of the historical carbonized bamboo strip comprises image information of multiple colors of the carbonized bamboo strip and corresponding color type labels, a color separation model based on the color image data of the carbonized bamboo strip is established according to the collected color image data sample of the historical carbonized bamboo strip, a color separation model based on the color image data of the carbonized bamboo strip is established according to the established color separation model based on the color image data of the carbonized bamboo strip, the current carbonized bamboo strip is subjected to color separation, and a carbonized bamboo strip with inconsistent color in the current carbonized bamboo strip is screened according to a color separation result of the color separation of the current carbonized bamboo strip, so that the color separation of the carbonized bamboo strip without manual work can be realized, the color separation efficiency and the color separation accuracy are improved, and the color consistency of the carbonized bamboo strip subjected to automatic color separation can be ensured, can ensure the color quality of bamboo products.
Further, the above scheme may obtain image information of multiple colors of carbonized bamboo chips in the color image data sample of the historical carbonized bamboo chips and corresponding color type labels according to the collected color image data sample of the historical carbonized bamboo chips, divide the image information of multiple colors of carbonized bamboo chips and corresponding color type labels in the color image data sample of the historical carbonized bamboo chips into N segments, where N is a natural number greater than 1, extract time weighting features of the image information of multiple colors of the carbonized bamboo chips and corresponding color type labels after being divided into N segments through a convolutional neural network, and obtain multi-scale features of the image information of multiple colors of the carbonized bamboo chips and corresponding color type labels after being divided into N segments according to the extracted time weighting features, and fusing image information of multiple colors of the obtained carbonized bamboo chips in the color image data samples of the N sections of historical carbonized bamboo chips and the multi-scale characteristics of the corresponding color type labels to calculate a prediction score, and obtaining a final classification of color image data samples related to the collected historical carbonized bamboo chips according to the calculated prediction score, and obtaining training characteristics of the color image data samples related to the collected historical carbonized bamboo chips according to the obtained classification of the color image data samples related to the collected historical carbonized bamboo chips, and performing model training according to the obtained training characteristics associated with the collected historical color image data samples of the carbonized bamboo chips, and establishing a color separation model based on the color image data of the carbonized bamboo chips, so that the modeling effect and accuracy of establishing the color separation model based on the color image data of the carbonized bamboo chips can be improved.
Furthermore, according to the scheme, the training characteristics of the current carbonized bamboo chip image information can be matched from the established color separation model of the color image data based on the carbonized bamboo chips, the training characteristics of the current carbonized bamboo chip image information are trained by adopting the matched training characteristics, the color separation is carried out on the current carbonized bamboo chip image information, the color separation is carried out on the current carbonized bamboo chip, and the color separation efficiency and the accuracy of the color separation result of the current carbonized bamboo chip image information can be effectively improved.
Further, above scheme can adopt the mark mode to indicate this colour separation result according to this colour separation result of colour separation to current carbonization bamboo chip, according to the colour separation result of this suggestion, screens off the inconsistent carbonization bamboo chip of colour in the current carbonization bamboo chip, can realize improving automatic hourglass rate of examining the colour separation to the carbonization bamboo chip through the mark mode, improves the color quality guarantee of the carbonization bamboo chip after the colour separation to improve the color quality of bamboo product.
Furthermore, according to the scheme, after the color separation process of the carbonized bamboo chips is completed, the color image information of the carbonized bamboo chips can be obtained, and the color type labels corresponding to the obtained color image information of the carbonized bamboo chips are generated according to the obtained color image information of the carbonized bamboo chips, so that the construction efficiency of establishing the color separation model based on the color image data of the carbonized bamboo chips can be effectively improved.
In the several embodiments provided in the present invention, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a module or a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be substantially or partially implemented in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, a network device, or the like) or a processor (processor) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only a part of the embodiments of the present invention, and not intended to limit the scope of the present invention, and all equivalent devices or equivalent processes performed by the present invention through the contents of the specification and the drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (9)
1. A color separation method for carbonized bamboo chips is characterized by comprising the following steps:
collecting color image data samples of historical carbonized bamboo chips; the color image data sample of the historical carbonized bamboo chip comprises image information of various colors of the carbonized bamboo chip and corresponding color type labels;
establishing a color separation model based on the color image data of the carbonized bamboo chips according to the collected color image data samples of the historical carbonized bamboo chips;
according to the established color separation model based on the color image data of the carbonized bamboo chips, performing color separation on the current carbonized bamboo chips;
screening out the carbonized bamboo chips with inconsistent colors in the current carbonized bamboo chips according to the color separation result of color separation of the current carbonized bamboo chips;
the color separation model based on the color image data of the carbonized bamboo chips is established according to the collected color image data samples of the historical carbonized bamboo chips, and comprises the following steps:
acquiring image information of various colors of the carbonized bamboo chips in the color image data sample of the historical carbonized bamboo chips and corresponding color type labels according to the acquired color image data sample of the historical carbonized bamboo chips;
dividing the image information of various colors of the carbonized bamboo chips in the obtained color image data sample of the historical carbonized bamboo chips and the corresponding color type labels into N sections; wherein N is a natural number greater than 1;
extracting the image information of the various colors of the carbonized bamboo chips divided into the N sections and the time weighting characteristics of the corresponding color type labels through a convolutional neural network;
according to the extracted time weighting characteristics, obtaining image information of multiple colors of the carbonized bamboo chips divided into N sections and multi-scale characteristics of corresponding color type labels;
fusing image information of multiple colors of the obtained carbonized bamboo chips in the color image data samples of the N sections of historical carbonized bamboo chips and the multi-scale characteristics of the corresponding color type labels, and calculating a prediction score;
obtaining the final classification of the color image data samples related to the collected historical carbonized bamboo chips according to the calculated prediction scores;
obtaining training characteristics of the color image data samples related to the collected historical carbonized bamboo chips according to the obtained classification of the color image data samples related to the collected historical carbonized bamboo chips;
and performing model training according to the obtained training characteristics associated with the collected historical carbonized bamboo chip color image data samples, and establishing a color separation model based on the carbonized bamboo chip color image data.
2. The carbonized bamboo chip color separation method according to claim 1, wherein the color separation of the current carbonized bamboo chip according to the established color separation model based on the color image data of the carbonized bamboo chip comprises:
and matching training characteristics of the current carbonized bamboo chip image information from the established color separation model based on the color image data of the carbonized bamboo chips according to the established color separation model based on the color image data of the carbonized bamboo chips, and performing color separation on the current carbonized bamboo chip image information by adopting a mode of training the current carbonized bamboo chip image information by adopting the matched training characteristics.
3. The method for separating colors of carbonized bamboo chips as claimed in claim 1, wherein said screening out the carbonized bamboo chips with inconsistent colors from the current carbonized bamboo chips according to the color separation result of color separation of the current carbonized bamboo chips comprises:
and prompting the color separation result in a labeling mode according to the color separation result of color separation of the current carbonized bamboo chips, and screening the carbonized bamboo chips with inconsistent colors in the current carbonized bamboo chips according to the prompted color separation result.
4. The carbonized bamboo sheet color separation method according to claim 1, further comprising, before the acquiring color image data samples of historical carbonized bamboo sheets:
and generating a color type label corresponding to the obtained color image information of the carbonized bamboo chips according to the obtained color image information of the carbonized bamboo chips.
5. A carbonized bamboo sheet color separation system comprising:
the device comprises a collecting unit, an establishing unit, a color separation unit and a screening unit;
the acquisition unit is used for acquiring color image data samples of historical carbonized bamboo chips; the color image data sample of the historical carbonized bamboo chip comprises image information of various colors of the carbonized bamboo chip and corresponding color type labels;
the establishing unit is used for establishing a color separation model based on the color image data of the carbonized bamboo chips according to the collected color image data samples of the historical carbonized bamboo chips;
the color separation unit is used for carrying out color separation on the current carbonized bamboo chips according to the established color separation model based on the color image data of the carbonized bamboo chips;
and the screening unit is used for screening the carbonized bamboo chips with inconsistent colors in the current carbonized bamboo chips according to the color separation result of color separation of the current carbonized bamboo chips.
6. The carbonized bamboo sheet color separation system of claim 5, wherein the establishing unit is specifically configured to:
acquiring image information of various colors of the carbonized bamboo chips in the color image data sample of the historical carbonized bamboo chips and corresponding color type labels according to the acquired color image data sample of the historical carbonized bamboo chips;
dividing the image information of various colors of the carbonized bamboo chips in the obtained color image data sample of the historical carbonized bamboo chips and the corresponding color type labels into N sections; wherein N is a natural number greater than 1;
extracting the image information of the various colors of the carbonized bamboo chips divided into the N sections and the time weighting characteristics of the corresponding color type labels through a convolutional neural network;
obtaining image information of various colors of the carbonized bamboo chips divided into N sections and multi-scale characteristics of corresponding color type labels according to the extracted time weighting characteristics;
fusing image information of various colors of the carbonized bamboo chips in the obtained color image data samples of the N sections of historical carbonized bamboo chips and the multi-scale characteristics of the corresponding color type labels, and calculating a prediction score;
obtaining the final classification of the color image data samples related to the collected historical carbonized bamboo chips according to the calculated prediction scores;
obtaining training characteristics of the color image data samples related to the collected historical carbonized bamboo chips according to the obtained classification of the color image data samples related to the collected historical carbonized bamboo chips;
and performing model training according to the obtained training characteristics associated with the collected historical carbonized bamboo chip color image data samples, and establishing a color separation model based on the carbonized bamboo chip color image data.
7. The carbonized bamboo sheet color separation system of claim 5, wherein the color separation unit is specifically configured to:
and matching training characteristics of the current carbonized bamboo chip image information from the established color separation model based on the color image data of the carbonized bamboo chips according to the established color separation model based on the color image data of the carbonized bamboo chips, and performing color separation on the current carbonized bamboo chip image information by adopting a mode of training the current carbonized bamboo chip image information by adopting the matched training characteristics.
8. The carbonized bamboo sheet color separation system of claim 5, wherein the screening unit is specifically configured to:
and prompting the color separation result in a labeling mode according to the color separation result of color separation of the current carbonized bamboo chips, and screening the carbonized bamboo chips with inconsistent colors in the current carbonized bamboo chips according to the prompted color separation result.
9. The carbonized bamboo chip color separation system of claim 5, further comprising:
and the generating unit is used for acquiring the color image information of the carbonized bamboo chips after the color separation process of the carbonized bamboo chips is finished, and generating the color type labels corresponding to the color image information of the acquired carbonized bamboo chips according to the acquired color image information of the carbonized bamboo chips.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910079753.9A CN109871455B (en) | 2019-01-28 | 2019-01-28 | Color separation method and system for carbonized bamboo chips |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910079753.9A CN109871455B (en) | 2019-01-28 | 2019-01-28 | Color separation method and system for carbonized bamboo chips |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109871455A CN109871455A (en) | 2019-06-11 |
| CN109871455B true CN109871455B (en) | 2020-11-10 |
Family
ID=66918208
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910079753.9A Active CN109871455B (en) | 2019-01-28 | 2019-01-28 | Color separation method and system for carbonized bamboo chips |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109871455B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109886934B (en) * | 2019-01-28 | 2020-12-18 | 厦门理工学院 | Carbonized bamboo chip defect detection method and system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2001041064A2 (en) * | 1999-12-01 | 2001-06-07 | Koninklijke Philips Electronics N.V. | Program classification using object tracking |
| CN101436302A (en) * | 2008-12-10 | 2009-05-20 | 南京大学 | Method for sorting colors of colorful three-dimensional model based on neural network |
| CN103971134A (en) * | 2014-04-25 | 2014-08-06 | 华为技术有限公司 | Image classifying, retrieving and correcting method and corresponding device |
| CN108446705A (en) * | 2017-02-16 | 2018-08-24 | 华为技术有限公司 | The method and apparatus of image procossing |
| CN109033308A (en) * | 2018-07-16 | 2018-12-18 | 安徽江淮汽车集团股份有限公司 | A kind of image search method and device |
-
2019
- 2019-01-28 CN CN201910079753.9A patent/CN109871455B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2001041064A2 (en) * | 1999-12-01 | 2001-06-07 | Koninklijke Philips Electronics N.V. | Program classification using object tracking |
| CN101436302A (en) * | 2008-12-10 | 2009-05-20 | 南京大学 | Method for sorting colors of colorful three-dimensional model based on neural network |
| CN103971134A (en) * | 2014-04-25 | 2014-08-06 | 华为技术有限公司 | Image classifying, retrieving and correcting method and corresponding device |
| CN108446705A (en) * | 2017-02-16 | 2018-08-24 | 华为技术有限公司 | The method and apparatus of image procossing |
| CN109033308A (en) * | 2018-07-16 | 2018-12-18 | 安徽江淮汽车集团股份有限公司 | A kind of image search method and device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109871455A (en) | 2019-06-11 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Grosjean et al. | Enumeration, measurement, and identification of net zooplankton samples using the ZOOSCAN digital imaging system | |
| Zhao et al. | Tracing the geographic origin of beef in China on the basis of the combination of stable isotopes and multielement analysis | |
| Basile et al. | What do tree-related microhabitats tell us about the abundance of forest-dwelling bats, birds, and insects? | |
| Hadley et al. | Tropical forest fragmentation limits pollination of a keystone understory herb | |
| Wang et al. | Multilocus phylogeny and revised classification for mountain dragons of the genus Japalura sl.(Reptilia: Agamidae: Draconinae) from Asia | |
| Spirin et al. | Antrodia hyalina, a new polypore from Russia, and A. leucaena, new to Europe | |
| Spirin et al. | What is Antrodia sensu stricto? | |
| Mitra et al. | The Mixoplankton Database (MDB): Diversity of photo‐phago‐trophic plankton in form, function, and distribution across the global ocean | |
| CN109254959B (en) | Data evaluation method and device, terminal equipment and readable storage medium | |
| CN111157698A (en) | Inversion method for obtaining total potassium content of black soil by using emissivity data | |
| Nolan et al. | Automated detection and segmentation of vine rows using high resolution UAS imagery in a commercial vineyard | |
| CN102998350B (en) | Method for distinguishing edible oil from swill-cooked dirty oil by electrochemical fingerprints | |
| CN109871455B (en) | Color separation method and system for carbonized bamboo chips | |
| Morrison et al. | Hummingbird–plant interactions are more specialized in forest compared to coffee plantations | |
| CN108038499A (en) | A kind of seeds sorting technique and system based on deep learning | |
| Pastor et al. | Unveiling new sequestrate Cortinarius species from northern Patagonian Nothofagaceae forests based on molecular and morphological data | |
| Masetti et al. | NMR tracing of food geographical origin: The impact of seasonality, cultivar and production year on data analysis | |
| Vidaković et al. | Phenotypic diversity of almond-leaved pear (Pyrus spinosa Forssk.) along Eastern Adriatic Coast | |
| CN105223140A (en) | The method for quickly identifying of homology material | |
| CN103605670B (en) | A kind of method and apparatus for determining the crawl frequency of network resource point | |
| Kaya et al. | An automatic identification method for the comparison of plant and honey pollen based on GLCM texture features and artificial neural network | |
| Vidaković et al. | Phenotypic variation in European wild pear (Pyrus pyraster (L.) Burgsd.) populations in the North-Western Part of the Balkan Peninsula | |
| Orliac | The petrosal bone of extinct Suoidea (Mammalia, Artiodactyla) | |
| CN109886934B (en) | Carbonized bamboo chip defect detection method and system | |
| Wikantika et al. | Integrated Studies of Banana on Remote Sensing, Biogeography, and Biodiversity: An Indonesian Perspective |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |