CN112132237A - Pure pixel spectrum library establishing method and device - Google Patents
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Abstract
The invention belongs to the technical field of image data processing, and particularly relates to a method and a device for establishing a clean pixel spectral library, wherein the method comprises the steps of acquiring initial spectral data of an object to be put in a library; selecting a ROI region based on the initial spectral data; filtering interference pixels in the ROI area and acquiring pure pixels in the ROI area; and establishing a spectrum library based on the pure pixels. When the spectral library is established, the standard property and the reliability of data in the spectral library established according to the spectral data of an object to be put in the library are improved by filtering the interference pixel in the ROI area, the error rate when the spectral library is used for data comparison is reduced, the data comparison precision is improved, the classification efficiency and the classification accuracy are also improved, the production efficiency is greatly improved, and the method has high practicability.
Description
Technical Field
The invention belongs to the technical field of image data processing, and particularly relates to a method and a device for establishing a pure pixel spectral library.
Background
At present, in a classification algorithm applying hyperspectrum in industry, a spectrum library of an object to be measured is generally required to be established. And the data in the spectral library determines the accuracy of the results obtained by the classification algorithm. The spectrum library roughly comprises two types, wherein one type is a standard spectrum library, and the other type is a self-defined spectrum library established according to an object to be detected.
When a custom spectrum library is established, the conventional method is to record the spectrum data of all objects to be detected into the spectrum library. However, the spectral data of the object to be detected has interference pixels, so that the spectral data in the spectral library has the interference pixels, which causes the problems of poor data standard and low reliability in the spectral library, and further causes the problem of influencing the subsequent classification precision. Therefore, it is necessary to design a method and an apparatus for establishing a pure pixel spectrum library.
Disclosure of Invention
The invention aims to provide a method and a device for establishing a pure pixel spectrum library, and aims to solve the technical problems that when a spectrum library is established in the prior art, interference pixels exist in spectrum data in the spectrum library, so that the standard property and the reliability of the data in the spectrum library are poor, and further the subsequent classification precision is influenced.
In order to achieve the above object, an embodiment of the present invention provides a method for establishing a pure pixel spectral library, where the method includes the following steps:
acquiring initial spectral data of an object to be put in storage;
selecting a ROI region based on the initial spectral data;
filtering interference pixels in the ROI area and acquiring pure pixels in the ROI area;
and establishing a spectrum library based on the pure pixels.
Optionally, the filtering out the interference pixel in the ROI region and obtaining the pure pixel in the ROI region includes:
selecting target pixels from the ROI area optionally;
calculating the actual similarity between the spectrums of all the pixels in the ROI area and the spectrum of the target pixel;
judging whether the actual similarity meets a preset similarity threshold or not;
if the ROI meets the similarity threshold, defining the pixel meeting the similarity threshold in the ROI as the pure pixel.
Optionally, before the determining that the actual similarity meets a preset similarity threshold, the method further includes:
setting a similarity measurement standard;
setting the similarity threshold according to the similarity measurement standard; wherein different similarity metrics correspond to different similarity thresholds.
Optionally, the similarity metric comprises a minimum distance, a spectral angle, a spectral information divergence, or a spectral correlation.
Optionally, the establishing a spectrum library based on the pure pixels comprises:
counting the number of pixels meeting the similarity threshold in the ROI area in real time;
calculating the percentage of the number of the pixels meeting the similarity threshold value in the ROI area in real time, and recording the percentage as the percentage of pure pixels;
and establishing a spectrum library based on the percentage of the pure pixels.
Optionally, the establishing a spectrum library based on the percentage of pure pixels includes:
judging whether the percentage of the pure pixels meets a preset percentage threshold value;
if the pixel spectrum is judged to be yes, a spectrum library is established according to the spectrum of all current pixels meeting the preset similarity threshold.
Optionally, the determining whether the percentage of pure pixels meets a preset percentage threshold includes:
presetting a percentage threshold;
and judging whether the percentage of the pure pixels meets the percentage threshold value.
Optionally, the establishing a spectrum library based on the percentage of pure pixels includes:
counting the percentage of each pure pixel;
obtaining the maximum value of the percentage of each pure pixel;
and establishing a spectrum library according to the spectrums of all the corresponding pixels meeting the preset similarity threshold when the percentage of the pure pixels is the maximum value.
The invention also provides a pure pixel spectrum library establishing device, which comprises:
the initial spectrum data acquisition module is used for acquiring initial spectrum data of an object to be put in storage;
a ROI area selection module for selecting a ROI area based on the initial spectral data;
the pure pixel acquisition module is used for filtering the interference pixels in the ROI area and acquiring the pure pixels in the ROI area;
and the spectrum library establishing module is used for establishing a spectrum library based on the pure pixels.
The invention also provides computer equipment which comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the steps in the pure pixel spectrum library establishing method when executing the computer program.
The present invention also provides a computer-readable storage medium on which a computer program is stored, which, when executed by a processor, implements the steps in the above pure pel spectral library establishment method.
The technical scheme or the technical schemes in the method and the device for establishing the pure pixel spectrum library provided by the embodiment of the invention at least have one of the following technical effects:
when a spectrum library is established, firstly, initial spectrum data of an object to be warehoused is obtained, then an ROI (region of interest) area is selected based on the initial spectrum data, interference pixels in the ROI area are filtered, pure pixels in the ROI area are obtained, and finally the spectrum library is established based on the pure pixels; through the filtering of the interference pixel in the ROI area, the standard property and the reliability of data in a spectrum library established according to the spectrum data of the object to be put in a warehouse are improved, the error rate when the spectrum library is used for data comparison is reduced, the data comparison precision is improved, the classification efficiency and the classification accuracy are also improved, the production efficiency is greatly improved, and the method has high practicability.
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In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
FIG. 1 is a flowchart of steps S100-S400 in a method for establishing a clean pixel spectral library according to an embodiment of the present invention;
FIG. 2 is a flowchart of steps S310-S330 in a method for establishing a pure pixel spectrum library according to an embodiment of the present invention;
FIG. 3 is a flowchart of steps S331-S332 in the method for establishing a pure pixel spectrum library according to the embodiment of the present invention;
FIG. 4 is a flowchart of steps S410-S430 in a method for establishing a pure pixel spectrum library according to an embodiment of the present invention;
FIG. 5 is a flowchart of steps S431-S432 in the method for establishing a pure pixel spectrum library according to the embodiment of the present invention;
FIG. 6 is a flowchart of steps S4311-S4312 in the method for establishing a pure pixel spectrum library according to the embodiment of the present invention;
FIG. 7 is a flowchart of steps S434-S436 in the method for establishing a pure pixel spectrum library according to the embodiment of the present invention;
FIG. 8 is a block diagram of a device for establishing a pure pixel spectrum library according to an embodiment of the present invention;
fig. 9 is a block diagram of a computer device according to an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It should also be understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to" determining "or" in response to detecting ". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".
Furthermore, in the description of the present application and the appended claims, the terms "first," "second," "third," and the like are used for distinguishing between descriptions and not necessarily for describing or implying relative importance.
Reference throughout this specification to "one embodiment" or "some embodiments," or the like, means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the present application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," or the like, in various places throughout this specification are not necessarily all referring to the same embodiment, but rather "one or more but not all embodiments" unless specifically stated otherwise. The terms "comprising," "including," "having," and variations thereof mean "including, but not limited to," unless expressly specified otherwise.
In one embodiment of the present invention, as shown in fig. 1, there is provided a method for establishing a clean pixel spectral library, the method comprising the following steps:
step S100: acquiring initial spectral data of an object to be put in storage;
in this step, the object to be put in storage is a source of spectral data to be established in the spectral library. In this embodiment, the initial spectral data of the objects to be put in storage is acquired one by a hyperspectral camera.
Step S200: selecting a ROI region based on the initial spectral data;
specifically, by selecting the ROI region, the processing time is reduced, and the image data processing accuracy is increased.
Step S300: filtering interference pixels in the ROI area and acquiring pure pixels in the ROI area;
specifically, the acquired initial spectral data inevitably has interference pixels, such as dust, impurities, interference and other impurity factors on the surface of the object to be put in storage. Therefore, in the step, a pure pixel in the ROI area, namely an impurity-free pixel, is obtained by filtering the interference pixel in the ROI area. Therefore, the accuracy and precision of the data in the subsequently established spectrum library are ensured.
Step S400: and establishing a spectrum library based on the pure pixels.
In the step, the interference pixels are filtered out from the spectral data in the spectral library established based on the pure pixels, so that the accuracy of the subsequent data comparison by using the spectral library is improved, and the data processing effect and the image processing precision are improved.
Therefore, when the spectrum library is established, the initial spectrum data of an object to be warehoused is obtained, the ROI area is selected based on the initial spectrum data, the interference pixel in the ROI area is filtered, the pure pixel in the ROI area is obtained, and finally the spectrum library is established based on the pure pixel; through the filtering of the interference pixel in the ROI area, the standard property and the reliability of data in a spectrum library established according to the spectrum data of the object to be put in a warehouse are improved, the error rate when the spectrum library is used for data comparison is reduced, the data comparison precision is improved, the classification efficiency and the classification accuracy are also improved, the production efficiency is greatly improved, and the method has high practicability.
In another embodiment of the present invention, as shown in fig. 2, the filtering out the interference pixels in the ROI region and obtaining the clean pixels in the ROI region includes:
step S310: selecting target pixels from the ROI area optionally;
in this step, the ROI area includes a plurality of pixels, and when the interference pixels are filtered, each pixel needs to be determined to determine whether the pixel is an interference pixel. Initially, a pixel is selected optionally, and the selected pixel is the target pixel in this step.
Step S320: calculating the actual similarity between the spectrums of all the pixels in the ROI area and the spectrum of the target pixel;
in the step, the difference of the spectrum data between the interference pixel and the pure pixel is utilized, so that whether the image is the pure pixel or not is distinguished by calculating the actual similarity of the spectrums of all the pixels in the ROI area and the spectrum of the target pixel.
Step S330: judging whether the actual similarity meets a preset similarity threshold or not;
in this step, a preset similarity threshold is used to measure the similarity between the spectrum of the target pixel and the spectra of all pixels in the ROI region.
Step S340: if the ROI meets the similarity threshold, defining the pixel meeting the similarity threshold in the ROI as the pure pixel.
In this step, if yes, it is determined that the actual similarity satisfies a preset similarity threshold, and at this time, the pixel satisfying the preset similarity threshold is the pure pixel.
In another embodiment of the present invention, as shown in fig. 3, before the determining that the actual similarity satisfies the preset similarity threshold, the method further includes:
step S331: setting a similarity measurement standard;
in order to improve the judgment high precision, different measurement standards can be set according to actual requirements so as to realize multi-standard judgment.
Step S332: setting the similarity threshold according to the similarity measurement standard; wherein different similarity metrics correspond to different similarity thresholds.
In another embodiment of the invention, the similarity metric comprises a minimum distance, a spectral angle, a spectral information divergence or a spectral correlation.
In one embodiment of the invention, the similarity metric is a minimum distance. That is, in the step S331, the similarity metric is set to the minimum distance. In step S332, the similarity threshold is a specific numerical value. In judgment, the greater the minimum distance of the spectrum, the greater the similarity.
In one embodiment of the invention, the similarity measure is a spectral angle. That is, in the step S331, the similarity measure is set to a spectrum angle. In step S332, the similarity threshold is a specific spectrum angle cosine value. When in judgment, the larger the cosine value of the spectrum angle is, the larger the similarity is
In one embodiment of the invention, the similarity measure is a divergence of spectral information. That is, in the step S331, the similarity measure is set as the divergence of spectral information. In step S332, the similarity threshold is a specific spectral information variance value. When in judgment, the closer the spectral information divergence value is to 0, the greater the similarity is
In one embodiment of the invention, the similarity measure is a spectral correlation. That is, in the step S331, the similarity measure is set to be a spectral correlation. In step S332, the similarity threshold is a specific spectral correlation coefficient. In judgment, the greater the minimum distance of the spectrum, the greater the similarity.
In another embodiment of the present invention, as shown in fig. 4, the creating a spectrum library based on the clean pels comprises:
step S410: counting the number of pixels meeting the similarity threshold in the ROI area in real time;
step S420: calculating the percentage of the number of the pixels meeting the similarity threshold value in the ROI area in real time, and recording the percentage as the percentage of pure pixels;
in this step, the percentage of the pure pixels is the ratio of all the pixels of the pure pixels in the ROI area.
Step S430: and establishing a spectrum library based on the percentage of the pure pixels.
In this step, the percentage of pure pixels is used for subsequently determining the number of pure pixels for establishing the spectrum library.
In another embodiment of the present invention, as shown in fig. 5, the creating a spectrum library based on the percentage of pure pixels includes:
step S431: judging whether the percentage of the pure pixels meets a preset percentage threshold value;
step S432: if the pixel spectrum is judged to be yes, a spectrum library is established according to the spectrum of all current pixels meeting the preset similarity threshold.
In this step, if yes, the percentage of the pure pixels is determined to meet a preset percentage threshold. At this point, the number of clear picture elements has reached the predetermined number requirement. Therefore, the acquisition of the pure pixels can be finished at this time, and a spectrum library is established by using the spectrums of all the current pixels meeting the preset similarity threshold.
Specifically, when the percentage threshold is set to be 90%, and when the percentage of pure pixels reaches 90%, the number of pure pixels in the established spectrum library accounts for 90% of the total amount of all pixels in the ROI area.
In another embodiment of the present invention, as shown in fig. 6, the determining whether the percentage of pure pixels meets a preset percentage threshold includes:
step S4311: presetting a percentage threshold;
in this step, the percentage threshold is preset, so that the percentage threshold can be timely adjusted, and the flexibility is improved.
Step S4312: and judging whether the percentage of the pure pixels meets the percentage threshold value.
In another embodiment of the present invention, as shown in fig. 7, the creating a spectrum library based on the percentage of pure pixels includes:
step S434: counting the percentage of each pure pixel;
step S435: obtaining the maximum value of the percentage of each pure pixel;
step S436: and establishing a spectrum library according to the spectrums of all the corresponding pixels meeting the preset similarity threshold when the percentage of the pure pixels is the maximum value.
Specifically, assume a total of 1000 pixels in the ROI region. When the 600 th pixel is judged to be a pure pixel, the percentage of the pure pixel is X%. And then, continuously judging, wherein when the 700 th pixel is judged to be a pure pixel, the percentage of the pure pixel is Y percent. Wherein Y% must not be less than X%. When the 1000 th pixel is judged, the pure pixel percentage Z% can be obtained. Thus, as described in step S434, the percentage of each pure pixel has been counted.
And then, obtaining the pure pixel percentage with the maximum numerical value according to the counted pure pixel percentages. Taking the above example, Z% is the maximum percentage of pure pixels, so that the corresponding pixels meeting the preset similarity threshold when the percentage of pure pixels is the maximum value are all the pure pixels in the ROI region.
Therefore, a spectrum library is established according to the spectrum of all pixels meeting the preset similarity threshold value when the percentage of the pure pixels is the maximum value, the spectrum library established based on all the pure pixels in the ROI area is obtained, the comprehensiveness of data in the spectrum library is guaranteed, and the data processing precision is improved.
In another embodiment of the present invention, as shown in fig. 8, there is further provided a pure pixel spectrum library creating apparatus, including: the system comprises an initial spectrum data acquisition module, an ROI area selection module, a pure pixel acquisition module and a spectrum library establishment module.
The system comprises an initial spectrum data acquisition module, a storage module and a storage module, wherein the initial spectrum data acquisition module is used for acquiring initial spectrum data of an object to be stored in a storage;
the ROI area selection module is used for selecting an ROI area based on the initial spectral data;
the pure pixel acquisition module is used for filtering the interference pixels in the ROI area and acquiring the pure pixels in the ROI area;
and the spectrum library establishing module is used for establishing a spectrum library based on the pure pixels.
In another embodiment of the present invention, the pure pel acquisition module is further to optionally select a target pel from the ROI area; calculating the actual similarity between the spectrums of all the pixels in the ROI area and the spectrum of the target pixel; judging whether the actual similarity meets a preset similarity threshold or not; if the ROI meets the similarity threshold, defining the pixel meeting the similarity threshold in the ROI as the pure pixel.
In another embodiment of the present invention, the spectrum library establishing module is further configured to count, in real time, the number of pixels in the ROI area that satisfy the similarity threshold; calculating the percentage of the number of the pixels meeting the similarity threshold value in the ROI area in real time, and recording the percentage as the percentage of pure pixels; and establishing a spectrum library based on the percentage of the pure pixels.
In another embodiment of the present invention, as shown in fig. 9, there is further provided a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above pure pel spectral library establishment method when executing the computer program.
In another embodiment of the present invention, a computer-readable storage medium is further provided, on which a computer program is stored, which when executed by a processor implements the steps in the pure pel spectral library establishment method described above.
For specific limitations of the pure pixel spectrum library establishing device, reference may be made to the above limitations on the pure pixel spectrum library establishing method, which is not described herein again. All modules in the pure pixel spectrum library establishing device can be completely or partially realized through software, hardware and a combination of the software and the hardware. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as shown in fig. 9. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to realize a clean pixel spectral library establishing method. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
Those skilled in the art will appreciate that the architecture shown in fig. 9 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (10)
1. A pure pixel spectral library establishing method is characterized by comprising the following steps:
acquiring initial spectral data of an object to be put in storage;
selecting a ROI region based on the initial spectral data;
filtering interference pixels in the ROI area and acquiring pure pixels in the ROI area;
and establishing a spectrum library based on the pure pixels.
2. The method for establishing the clean pixel spectral library of claim 1, wherein the filtering out the interference pixels in the ROI area and obtaining the clean pixels in the ROI area comprises:
selecting target pixels from the ROI area optionally;
calculating the actual similarity between the spectrums of all the pixels in the ROI area and the spectrum of the target pixel;
judging whether the actual similarity meets a preset similarity threshold or not;
if the ROI meets the similarity threshold, defining the pixel meeting the similarity threshold in the ROI as the pure pixel.
3. The method for establishing the pure pixel spectral library according to claim 2, wherein before the step of judging that the actual similarity meets a preset similarity threshold, the method further comprises the following steps:
setting a similarity measurement standard;
setting the similarity threshold according to the similarity measurement standard; wherein different similarity metrics correspond to different similarity thresholds.
4. The method of claim 3, wherein the similarity metric comprises a minimum distance, a spectral angle, a spectral information divergence, or a spectral correlation.
5. The method for creating a clean pel spectra library of any one of claims 2 to 4, wherein creating a spectra library based on the clean pels comprises:
counting the number of pixels meeting the similarity threshold in the ROI area in real time;
calculating the percentage of the number of the pixels meeting the similarity threshold value in the ROI area in real time, and recording the percentage as the percentage of pure pixels;
and establishing a spectrum library based on the percentage of the pure pixels.
6. The method of claim 5, wherein the creating a spectrum library based on the percentage of pure pixels comprises:
judging whether the percentage of the pure pixels meets a preset percentage threshold value;
if the pixel spectrum is judged to be yes, a spectrum library is established according to the spectrum of all current pixels meeting the preset similarity threshold.
7. The method for establishing the pure pixel spectral library of claim 5, wherein the determining whether the pure pixel percentage meets a preset percentage threshold comprises:
presetting a percentage threshold;
and judging whether the percentage of the pure pixels meets the percentage threshold value.
8. The method of claim 5, wherein the creating a spectrum library based on the percentage of pure pixels comprises:
counting the percentage of each pure pixel;
obtaining the maximum value of the percentage of each pure pixel;
and establishing a spectrum library according to the spectrums of all the corresponding pixels meeting the preset similarity threshold when the percentage of the pure pixels is the maximum value.
9. A pure pixel spectral library creation apparatus, comprising:
the initial spectrum data acquisition module is used for acquiring initial spectrum data of an object to be put in storage;
a ROI area selection module for selecting a ROI area based on the initial spectral data;
the pure pixel acquisition module is used for filtering the interference pixels in the ROI area and acquiring the pure pixels in the ROI area;
and the spectrum library establishing module is used for establishing a spectrum library based on the pure pixels.
10. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method of any one of claims 1 to 7 when executing the computer program.
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| CN113390799A (en) * | 2021-06-24 | 2021-09-14 | 中国烟草总公司郑州烟草研究院 | Method for identifying and detecting stems in tobacco leaves |
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