CN113933305B - Thin-skinned fruit sugar content nondestructive measurement method and system based on smart phone - Google Patents
Thin-skinned fruit sugar content nondestructive measurement method and system based on smart phone Download PDFInfo
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Abstract
The invention relates to a sugar degree nondestructive measurement method of a thin-skinned fruit based on a smart phone, which comprises the steps of selecting an interested area of the thin-skinned fruit, and emitting a visible light source and infrared light sources with different wave bands to enable the visible light source and the infrared light sources to reach the surface layer of the thin-skinned fruit and generate diffuse reflection; obtaining photos of the region of interest of the thin-skinned fruit, which is subjected to diffuse reflection under the irradiation of a visible light source and infrared light sources with different wave bands in a dark environment; the mobile phone extracts RGB values of the interested region of the thin-skinned fruit in each picture, an RGB-brix model is constructed based on the RGB values of the interested region of the thin-skinned fruit, and the brix value of the interested region of the thin-skinned fruit is obtained according to the RGB-brix model. The method directly utilizes the correlation between the RGB value of the mobile phone picture and the sugar content of the thin-skinned fruit, omits complex equipment such as a spectrometer and the like, simplifies a detection system, reduces the data processing amount, improves the detection efficiency, is quick and accurate, and has wide application market and prospect.
Description
Technical Field
The invention relates to the technical field of agricultural product detection, in particular to a sugar degree nondestructive measurement method and system for thin-skinned fruits based on a smart phone.
Background
China is one of the important fruit producing countries in the world, in recent years, with the improvement of living standard of people and the increase of the yield of various fruits, the consumption of the fruits is changed from 'quantity type' to 'quality type', the demand of people for the quality of the fruits is higher and higher, wherein the sugar degree of the fruits is taken as a main factor of the quality of the fruits and has an important position in the fruit detection technology. Most of the traditional fruit sugar degree detection methods are destructive detection, the measurement of the internal quality of fruits wastes time and labor, and only spot check can be performed. In order to solve the problem, the nondestructive testing of the fruit quality by using the hyperspectral imaging technology has been realized in recent two years, but the nondestructive testing method in the prior art still has the following problems: the nondestructive testing method has higher requirements on hardware, can realize fruit quality testing by usually needing a hyperspectral imaging system or a spectrometer to be matched with specific software, and has poor transportability; moreover, the nondestructive testing method usually needs to utilize a large amount of spectral data, increases the burden of data processing, and is inconvenient for rapid testing.
Therefore, in order to solve these limitations, it is necessary to optimize the hardware device design and perform the simplest processing on it, so as to enhance the portability of the hardware device; complicated equipment such as a spectrometer and the like is also needed to be removed, and a detection system is simplified, so that the detection process is convenient, quick and easy to operate while the accuracy is ensured.
Disclosure of Invention
Therefore, the technical problem to be solved by the invention is to overcome the technical defects in the prior art, and provide a thin-skinned fruit sugar content nondestructive measurement method and system based on a smart phone,
in order to solve the technical problem, the invention provides a non-destructive measurement method for sugar content of thin-skinned fruits based on a smart phone, which comprises the following steps:
s100: selecting an interested area of the thin-skinned fruit, and emitting a visible light source and infrared light sources with different wave bands to enable the visible light source and the infrared light sources to reach the surface layer of the thin-skinned fruit and generate diffuse reflection;
s200: acquiring photos of the region of interest of the thin-skinned fruit, which is subjected to diffuse reflection under the irradiation of a visible light source and infrared light sources with different wave bands in a dark environment;
s300: extracting the RGB value of the interested region of the thin-skinned fruit in each picture, constructing an RGB-brix model based on the RGB value of the interested region of the thin-skinned fruit, and obtaining the brix value of the interested region of the thin-skinned fruit according to the RGB-brix model.
In one embodiment of the present invention, in S1, the rated voltage of the visible light source is 10V or less, and the rated power thereof is 5W or less; the rated voltage of the infrared light sources with different wave bands is below 10V, and the rated power of the infrared light sources is below 10W.
In one embodiment of the invention, in S2, the method for obtaining the photo of the diffuse reflection of the interested area of the thin-skinned fruit under the irradiation of the visible light source and the infrared light sources with different wave bands in the dark environment comprises the following steps:
the method comprises the steps of shooting light of visible light after diffuse reflection occurs on the surface layer of the thin-skinned fruit by using a smart phone in a shooting mode, and shooting light of infrared light of different wave bands after diffuse reflection occurs on the surface layer of the thin-skinned fruit in a professional mode under fixed parameters.
In one embodiment of the present invention, in S3, the method for extracting RGB values of the region of interest of the thin-skinned fruit in each photo comprises:
dividing a square area with the size of M multiplied by N pixels by using the middle point of the pixel of the image shot by the mobile phone as a central coordinate by the mobile phone APP; and averaging the RGB values of all the pixel values in the area to obtain an average RGB value.
In one embodiment of the present invention, in S3, the method for constructing an RGB-brix model based on RGB values of the region of interest of the thin-skinned fruit comprises:
the sugar degree of the interested area of the thin-skin fruit is measured by a sugar degree meter, and the measured value is used as a real sugar degree value. Combining the corresponding average RGB values to construct an RGB-brix value database;
and fitting the average RGB value and the corresponding real sugar degree value by utilizing an RGB-sugar degree value database to obtain an RGB-sugar degree model.
In one embodiment of the present invention, in S3, the method for obtaining the brix value of the interested region of the thin-skinned fruit according to the RGB-brix model comprises:
the mobile phone shoots pictures of the interested region of the thin-skinned fruit to be detected under different light sources, the mobile phone APP loads the pictures, the RGB value is calculated and substituted into the RGB-brix model to calculate the output value of the model, and the output value is the brix value of the interested region of the thin-skinned fruit to be detected.
In addition, the invention also provides a thin-skinned fruit sugar degree nondestructive measurement system based on the smart phone, which comprises:
the light source module is used for emitting a visible light source and infrared light sources with different wave bands to reach the surface layer of the thin-skinned fruit and generate diffuse reflection;
the device comprises a photo acquisition module, a light source module and a control module, wherein the photo acquisition module is used for acquiring photos of the region of interest of the thin-skinned fruit which is subjected to diffuse reflection under the irradiation of a visible light source and infrared light sources with different wave bands in a dark environment;
the intelligent mobile phone processing module is used for extracting RGB values of the thin-skinned fruit interesting region in each picture, constructing an RGB-brix model based on the RGB values of the thin-skinned fruit interesting region, and obtaining the brix value of the thin-skinned fruit interesting region according to the RGB-brix model.
In one embodiment of the invention, in the light source module, the rated voltage of the visible light source is below 10V, and the rated power of the visible light source is below 5W; the rated voltage of the infrared light sources with different wave bands is below 10V, and the rated power of the infrared light sources is below 10W.
In an embodiment of the present invention, the photo acquisition module is further configured to:
the method comprises the steps of shooting light of visible light after diffuse reflection occurs on the surface layer of the thin-skinned fruit by using a smart phone in a shooting mode, and shooting light of infrared light of different wave bands after the diffuse reflection occurs on the surface layer of the thin-skinned fruit in a professional mode under fixed parameters.
In an embodiment of the present invention, the smartphone processing module is further configured to:
selecting an M multiplied by N pixel region in the center of the region of interest of the thin-skinned fruit in each picture, calculating an average RGB value of all pixel values in the region, measuring the sugar degree of the region of interest of the thin-skinned fruit by using a sugar degree meter, and taking the measured value as a real sugar degree value;
and fitting the average RGB value of the obtained pixel values with the corresponding real sugar degree value to obtain an RGB-sugar degree model.
In an embodiment of the present invention, the smartphone processing module is further configured to:
and taking the RGB value of the interested region of the thin-skinned fruit as an input value, and calculating by using an RGB-brix model to obtain an output value of the model, wherein the output value is the brix value of the interested region of the thin-skinned fruit.
Moreover, the invention also provides a smart phone APP for realizing the non-destructive measurement method for the sugar content of the thin-skinned fruit based on the smart phone.
Compared with the prior art, the technical scheme of the invention has the following advantages:
according to the method, firstly, the correlation between the RGB value of the mobile phone picture and the characteristic spectrum and the correlation between the characteristic spectrum and the sugar content of the thin-skinned fruit are utilized, the intermediate variable, namely the characteristic spectrum, is removed, the correlation between the RGB value of the mobile phone picture and the sugar content of the thin-skinned fruit is directly utilized, complex equipment such as a spectrometer and the like is omitted, a detection system is simplified, meanwhile, the data processing amount is reduced, the detection efficiency is improved, and the method is quick and accurate; secondly, based on smart mobile phone imaging system and cell-phone APP to thin skin fruit sugar degree carry out nondestructive test system with low costs, the device is small, and is small and exquisite light, and portability is strong, has extensive application market and prospect.
Drawings
In order that the present disclosure may be more readily and clearly understood, reference is now made to the following detailed description of the embodiments of the present disclosure taken in conjunction with the accompanying drawings, in which
Fig. 1 is a schematic flow chart of a smartphone-based nondestructive measurement method for sugar content of thin-skinned fruit according to an embodiment of the present invention.
Fig. 2 is a schematic structural diagram of an actual device for implementing a smartphone-based nondestructive measurement method for sugar content of thin-skinned fruits according to an embodiment of the present invention.
Fig. 3 is a schematic expanded structural diagram of an actual device for implementing a smartphone-based sugar content nondestructive measurement method for thin-skinned fruits according to an embodiment of the present invention.
Fig. 4 is a schematic diagram of a structure of a reflected light path according to an embodiment of the present invention.
Fig. 5 is a schematic structural diagram of a smartphone-based nondestructive measurement system for sugar content of thin-skinned fruit according to an embodiment of the present invention.
Fig. 6 is a schematic circuit diagram according to an embodiment of the present invention.
Fig. 7 is a schematic circuit diagram according to an embodiment of the present invention.
Description of reference numerals: 1. a light source module; 2. a photo acquisition module; 3. a smart phone processing module; 4. a warm white LED visible light source; 5. a near infrared light source with a waveband of 850nm to 855 nm; 6. a near infrared light source with a wave band of 940nm to 945 nm; 7. a warm white LED visible light source switch; 8. a near infrared light source switch with a waveband of 850nm to 855 nm; 9. a near-infrared light source switch with a wave band of 940nm to 945 nm; 10. detecting holes for the thin-skinned fruits; 11. a mobile phone photographing hole; 12. a table top; 13. an apple region of interest; 14. a 3.2V rechargeable lithium battery; 15. 3.7V rechargeable lithium cells.
Detailed Description
The present invention is further described below in conjunction with the following figures and specific examples so that those skilled in the art may better understand the present invention and practice it, but the examples are not intended to limit the present invention.
Example one
Referring to fig. 1, an embodiment of the present invention provides a method for nondestructive measurement of sugar content of a thin-skinned fruit based on a smart phone, including the following steps:
s100: selecting an interested area of the thin-skinned fruit, and emitting a visible light source and infrared light sources with different wave bands to enable the visible light source and the infrared light sources to reach the surface layer of the thin-skinned fruit and generate diffuse reflection;
s200: acquiring photos of the region of interest of the thin-skinned fruit, which is subjected to diffuse reflection under the irradiation of a visible light source and infrared light sources with different wave bands in a dark environment;
s300: extracting the RGB value of the interested region of the thin-skinned fruit in each picture, constructing an RGB-brix model based on the RGB value of the interested region of the thin-skinned fruit, and obtaining the brix value of the interested region of the thin-skinned fruit according to the RGB-brix model.
In the nondestructive measurement method for sugar content of thin-skinned fruit based on the smart phone, in S1, the rated voltage of a visible light source is below 10V, and the rated power of the visible light source is below 5W; the rated voltage of the infrared light sources with different wave bands is below 10V, and the rated power of the infrared light sources is below 10W.
In the nondestructive measurement method for sugar content of thin-skinned fruit based on the smart phone, as preferred, in this embodiment, 3 LED light sources can be selected, which are warm white LED visible light lamp beads with a wave band of 2800-3200K and LED near infrared light lamp beads with a wave band of 850-855nm and 940-945nm, respectively, and both carry a heat dissipation aluminum substrate. Wherein the rated voltage of the warm white LED visible light is 3.0-3.4V, and the rated power is 1W; the rated voltage of the near infrared light with the waveband of 850-855nm is 1.6-2.2V, and the rated power is 3W; the rated voltage of the 940-945nm band near infrared light is 1.3-1.8V, and the rated power is 3W.
In the thin-peel fruit sugar content nondestructive measurement method based on the smart phone, in order to ensure that the light source outputs stable power, the voltage stabilizer can be added to ensure that the light source outputs stable power, and the influence of the power consumption of the lithium battery on the power of the light source is reduced.
In the nondestructive measurement method for the sugar content of the thin-skinned fruit based on the smart phone, in S2, the method for obtaining the photos of the region of interest of the thin-skinned fruit under the irradiation of the visible light source and the infrared light sources with different wave bands in the dark environment and the diffuse reflection comprises the following steps:
the method comprises the steps of shooting light of visible light after diffuse reflection occurs on the surface layer of the thin-skinned fruit by using a smart phone in a shooting mode, and shooting light of infrared light of different wave bands after diffuse reflection occurs on the surface layer of the thin-skinned fruit in a professional mode under fixed parameters.
In the nondestructive measurement method for sugar content of thin-skinned fruits based on the smart phone, preferably, when the warm white LED visible light irradiates the apple, the mobile phone camera adopts a photographing mode to photograph; when the apple is irradiated by near infrared light of two wave bands of 850-855nm and 940-945nm, the mobile phone camera adopts a professional mode to take a picture, and the parameters are as follows: sensitivity (ISO) set to 1600; the integration time (S) is set to 1.
In the nondestructive measurement method for the sugar content of the thin-skinned fruit based on the smart phone, in S3, the method for extracting the RGB values of the region of interest of the thin-skinned fruit in each photo includes:
and calling a library function of MATLAB in the APP of the smart phone to extract the RGB value of the region of interest of the photo.
In the nondestructive measurement method for the sugar content of the thin-skinned fruit based on the smart phone, in S3, the method for constructing the RGB-sugar content model based on the RGB values of the region of interest of the thin-skinned fruit comprises:
s310: selecting an M multiplied by N pixel region in the center of the region of interest of the thin-skinned fruit in each picture, calculating an average RGB value of all pixel values in the region, measuring the sugar degree of the region of interest of the thin-skinned fruit by using a sugar degree meter, and taking the measured value as a real sugar degree value;
s320: and fitting the average RGB value of the obtained pixel values with the corresponding real sugar degree value to obtain an RGB-sugar degree model.
In the non-destructive measurement method for sugar content of thin-skinned fruit based on the smart phone, as preferable, the specific content of the RGB-sugar content model constructed in the embodiment is as follows: firstly, a picture shot under the irradiation of three light sources is marked as I 1 ，I 2 And I and 3 subscripts "1", "2", and "3" respectively represent images under infrared 1, infrared 2, and warm white LED light sources, each image being a color image having three color channels Red, green, and Blue, R respectively 1 ，G 1 ,B 1 ,R 2 ，G 2 ,B 2 And R 3 ,G 3 ,B 3 . Taking an apple as an example, selecting a 350 x 350 pixel area in the center of the apple interested area in each picture and calculating the average RGB values of all pixel values in the area, wherein r is 1 ，g 1 ,b 1 ,r 2 ，g 2 ,b 2 And r 3 ,g 3 ,b 3 (ii) a The X apples are respectively photographed, and the data obtained by calculation is (r) 1k ，g 1k ,b 1k ，r 2k ，g 2k ,b 2k ,r 3k ,g 3k ,b 3k K =1, \ 8230;, X); then, the sugar degree of the region of interest of X apples is measured by a sugar degree meter (high-precision sugar degree display meter) as a true sugar degree value T k (k =1, \8230;, X) in Brix; finally, according to the obtained pixel RGB value (r) 1k ，g 1k ,b 1k ,r 2k ，g 2k ,b 2k ，r 3k ,g 3k ,b 3k K =1, \ 8230;, X) and corresponding brix value T k (k =1, \8230;, X), using a multivariate linear regression model for modeling, the model obtained was: y =15.806-12.160 xr 1 -13.100×g 1 +13.992×b 1 -27.991×r 2 +70.833×g 2 -0.848×b 2 +5.656×r 3 -7.022×g 3 -3.495×b 3 +7.128×r 1 ×g 1 ×b 1 -2.870×r 2 ×g 2 ×b 2 -4.0790×r 3 ×g 3 ×b 3 。
In the nondestructive measurement method for the sugar content of the thin-skinned fruit based on the smart phone, in S3, the method for obtaining the sugar content value of the region of interest of the thin-skinned fruit according to the RGB-sugar content model includes:
and taking the RGB value of the interested region of the thin-skinned fruit as an input value, and calculating by using an RGB-brix model to obtain an output value of the model, wherein the output value is the brix value of the interested region of the thin-skinned fruit.
In the nondestructive measurement method for sugar content of thin-skinned fruit based on the smart phone, firstly, the correlation between the RGB value of the picture of the mobile phone and the characteristic spectrum and the correlation between the characteristic spectrum and the sugar content of the thin-skinned fruit are utilized, an intermediate variable, namely the characteristic spectrum is removed, the correlation between the RGB value of the picture of the mobile phone and the sugar content of the thin-skinned fruit is directly utilized, complex equipment such as a spectrometer and the like is omitted, a detection system is simplified, meanwhile, the data processing amount is reduced, the detection efficiency is improved, and the method is fast and accurate; secondly, based on smart mobile phone imaging system and cell-phone APP to thin skin fruit sugar degree carry out nondestructive test system with low costs, the device is small, and is small and exquisite light, and portability is strong, has extensive application market and prospect.
Example two
In the following, a nondestructive measurement system for sugar content of thin-skinned fruit based on a smart phone disclosed in the second embodiment of the present invention is introduced, and a nondestructive measurement system for sugar content of thin-skinned fruit based on a smart phone described in the following and a nondestructive measurement method for sugar content of thin-skinned fruit based on a smart phone described in the foregoing can be referred to correspondingly.
Referring to fig. 5, a second embodiment of the present invention provides a system for nondestructive measurement of sugar content of thin-skinned fruit based on a smart phone, including:
the light source module 1 is used for emitting a visible light source and infrared light sources with different wave bands to reach the surface layer of the thin-skinned fruit and generate diffuse reflection;
the photo acquisition module 2 is used for acquiring photos of the region of interest of the thin-skinned fruit, which is subjected to diffuse reflection under the irradiation of a visible light source and infrared light sources with different wave bands in a dark environment;
the intelligent mobile phone processing module 3 is used for extracting RGB values of the thin-skinned fruit interested area in each picture, building an RGB-sugar degree model based on the RGB values of the thin-skinned fruit interested area, and obtaining a sugar degree value of the thin-skinned fruit interested area according to the RGB-sugar degree model.
In the nondestructive measurement system for the sugar content of the thin-skinned fruit based on the smart phone, in the light source module 1, the rated voltage of a visible light source is below 10V, and the rated power of the visible light source is below 5W; the rated voltage of the infrared light sources in different wave bands is below 10V, and the rated power of the infrared light sources is below 10W.
In the non-destructive thin-skinned fruit brix measurement system based on the smart phone, the photo acquisition module 2 is further configured to capture light of visible light after diffuse reflection occurs on the surface layer of the thin-skinned fruit in a photographing mode by using the smart phone, and capture light of infrared light of different wave bands after diffuse reflection occurs on the surface layer of the thin-skinned fruit in a professional mode under fixed parameters.
In the thin-skinned fruit brix nondestructive measurement system based on the smart phone of the present disclosure, the smart phone processing module 3 is further configured to invoke the smart phone APP to extract the RGB values of the photo interest regions.
In the nondestructive measurement system for the sugar content of the thin-skinned fruit based on the smart phone, the smart phone processing module 3 is further configured to select an mxn pixel region in the center of the region of interest of the thin-skinned fruit in each picture, calculate an average RGB value of all pixel values in the region, measure the sugar content of the region of interest of the thin-skinned fruit by using a sugar content meter, and take a measurement value thereof as a real sugar content value; and fitting the obtained average RGB value of the pixel values with the corresponding real sugar degree value to obtain an RGB-sugar degree model.
In the nondestructive measurement system for the sugar content of the thin-skinned fruit based on the smart phone, the smart phone processing module 3 is further configured to use the obtained RGB values of the region of interest of the thin-skinned fruit as input values, and calculate an output value of the model by using an RGB-sugar content model, where the output value is the sugar content value of the region of interest of the thin-skinned fruit.
Fig. 2 and fig. 3 are schematic structural diagrams of an actual device for realizing smartphone-based sugar content nondestructive measurement of thin-skinned fruit according to an embodiment of the present invention. The device comprises the actual design of the light source module and the actual design of the photo taking module.
In the preferred embodiment of the present invention, in the practical design of the light source module 1, 6 light sources are uniformly arranged on the inclined table 12 as shown in fig. 3, wherein the angle between each two adjacent light sources and the line connecting the centers of the inclined table 12 is 60 degrees, and the inclination angle of the inclined table 12 is just enough to make the light of each light source irradiate the center of the thin-skinned fruit detection hole 10.
In the preferred embodiment of the present invention, in the practical design of the light source module 1, the circuit connection of the light sources takes into consideration the rated voltage of each light source, as shown in fig. 6, so that two warm white LED visible light sources 4 are connected in parallel and then connected in series with a switch 7 on both sides of a 3.2V rechargeable lithium battery 14, and two near infrared light sources 6 with the wavelength of 940nm to 945nm are connected in series and then connected in series with a switch 9 on both sides of the 3.2V rechargeable lithium battery 14; as shown in FIG. 7, two near infrared light sources 5 with a wavelength range of 850nm to 855nm are connected in series and then connected in series with a switch 8 to both sides of a 3.7V rechargeable lithium battery 15.
In a preferred embodiment of the present invention, in the actual design of the photo acquisition module 2, when taking a picture of an apple, the area of interest of the apple is aligned with the thin-skinned fruit inspection hole 10 as shown in fig. 2; the mobile phone is fixed at a designated position, so that the camera is aligned with the mobile phone photographing hole 11, and the structural schematic diagram of the reflection light path is shown in fig. 4 during photographing, so that light can be transmitted to the mobile phone photographing hole 11 after being reflected on the surface layer of the apple region of interest 13, and the mobile phone camera can receive light signals.
In the nondestructive measurement system for the sugar content of the thin-skinned fruit based on the smart phone, firstly, the correlation between the RGB value of the picture of the mobile phone and the characteristic spectrum and the correlation between the characteristic spectrum and the sugar content of the thin-skinned fruit are utilized, an intermediate variable, namely the characteristic spectrum is removed, the correlation between the RGB value of the picture of the mobile phone and the sugar content of the thin-skinned fruit is directly utilized, complex equipment such as a spectrometer is omitted, a detection system is simplified, meanwhile, the data processing amount is reduced, the detection efficiency is improved, and the method is fast and accurate; secondly, based on smart mobile phone imaging system and cell-phone APP to thin skin fruit sugar degree carry out nondestructive test system with low costs, the device is small, and is small and exquisite light, and portability is strong, has extensive application market and prospect.
The system for nondestructive measurement of sugar content of thin-skinned fruit based on a smart phone in this embodiment is used to implement the foregoing method for nondestructive measurement of sugar content of thin-skinned fruit based on a smart phone, so that the specific implementation of the system can be found in the foregoing section of the embodiment of the method for nondestructive measurement of sugar content of thin-skinned fruit based on a smart phone, and therefore, the specific implementation thereof can refer to the description of the corresponding section of the embodiment, and will not be further described herein.
In addition, since the system for nondestructive measurement of sugar content of thin-skinned fruit based on a smart phone of the present embodiment is used for implementing the method for nondestructive measurement of sugar content of thin-skinned fruit based on a smart phone, the effect corresponds to the effect of the method described above, and details are not described here.
EXAMPLE III
The embodiment of the invention also provides a smart phone APP for realizing the nondestructive measurement method of the sugar content of the thin-skinned fruit based on the smart phone, and the specific method and the system for realizing the nondestructive measurement of the sugar content of the thin-skinned fruit by the smart phone APP can be described with reference to the first embodiment and the second embodiment.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. This need not be, nor should it be exhaustive of all embodiments. And obvious variations or modifications of the invention may be made without departing from the scope of the invention.
Claims (7)
1. A non-destructive measurement method for sugar content of thin-skinned fruits based on a smart phone is characterized by comprising the following steps:
s100: selecting an interested area of the thin-skinned fruit, and emitting a visible light source and infrared light sources with different wave bands to reach the surface layer of the thin-skinned fruit and generate diffuse reflection, wherein the rated voltage of the visible light source is below 10V, and the rated power of the visible light source is below 5W; rated voltages of infrared light sources in different wave bands are all below 10V, and rated powers of the infrared light sources are all below 10W;
s200: acquiring photos of the region of interest of the thin-skinned fruit, which is subjected to diffuse reflection under the irradiation of a visible light source and infrared light sources with different wave bands in a dark environment; the photos comprise photos of the interested area of the thin-skinned fruit subjected to diffuse reflection under the irradiation of a visible light source and photos of the interested area of the thin-skinned fruit subjected to diffuse reflection under the irradiation of infrared light sources in each wave band;
s300: extracting the RGB value of the interested region of the thin-skinned fruit in each picture, constructing an RGB-brix model based on the RGB value of the interested region of the thin-skinned fruit, and obtaining the brix value of the interested region of the thin-skinned fruit according to the RGB-brix model; the RGB-brix model is a model which is obtained by fitting and represents the incidence relation between the brix value and the RGB value of each photo; the method for establishing the RGB-brix model comprises the following steps: selecting a 350 x 350 pixel region in the center of the region of interest of the thin-skinned fruit in each picture and calculating the average RGB value of all pixel values in the region, wherein r is 1 ，g 1 ，b 1 ，r 2 ，g 2 ，b 2 And r 3 ，g 3 ，b 3 1,2 and 3 respectively refer to an image under a first waveband infrared light source, an image under a second waveband infrared light source and an image under a visible light source; measuring the sugar degree of the interested region of the thin-skin fruit by using a sugar degree meter as a real sugar degree value T k (k =1,2,3); according to the obtained pixel RGB value and the corresponding sugar degree value T k Modeling by using a multiple linear regression model, wherein the obtained model is as follows:
Y＝15.806-12.160×r 1 -13.100×g 1 +13.992×b 1 -27.991×r 2 +70.833×g 2 -
0.848×b 2 +5.656×r 3 -7.022×g 3 -3.495×b 3 +7.128×r 1 ×g 1 ×b 1 -2.870×r 2 ×g 2 ×b 2 -4.0790×r 3 ×g 3 ×b 3 ；
in S300, the method for obtaining the brix value of the interested region of the thin-skinned fruit according to the RGB-brix model includes:
the mobile phone shoots pictures of the interested region of the thin-skinned fruit to be detected under different light sources, the mobile phone APP loads the pictures, the RGB value is calculated and substituted into the RGB-brix model to calculate the output value of the model, and the output value is the brix value of the interested region of the thin-skinned fruit to be detected.
2. The non-destructive measuring method for sugar content of thin-skinned fruit based on smart phone of claim 1, characterized in that: in S200, the method for obtaining the photo of the diffuse reflection of the interested area of the thin-skinned fruit under the irradiation of the visible light source and the infrared light sources with different wave bands in the dark environment includes:
the method comprises the steps of shooting light of visible light after diffuse reflection occurs on the surface layer of the thin-skinned fruit by using a smart phone in a shooting mode, and shooting light of infrared light of different wave bands after diffuse reflection occurs on the surface layer of the thin-skinned fruit in a professional mode under fixed parameters.
3. The smartphone-based nondestructive measurement method for sugar content of thin-skinned fruit according to claim 1, characterized in that: in S300, the method for extracting RGB values of the region of interest of the thin-skinned fruit in each photo includes:
dividing a square area with the size of M multiplied by N pixels by using the middle point of the pixel of the image shot by the mobile phone as a central coordinate by the mobile phone APP; and averaging the RGB values of all the pixel values in the area to obtain an average RGB value.
4. The smartphone-based nondestructive measurement method for sugar content of thin-skinned fruit according to claim 1, characterized in that: in S300, the method for constructing an RGB-brix model based on the RGB values of the region of interest of the thin-skinned fruit includes:
measuring the sugar degree of the interested region of the thin-skinned fruit by using a sugar degree meter, taking the measured value as a real sugar degree value, and constructing an RGB-sugar degree value database by combining a corresponding average RGB value;
and fitting the average RGB value and the corresponding real sugar degree value by utilizing an RGB-sugar degree value database to obtain an RGB-sugar degree model.
5. The utility model provides a thin skin fruit sugar content nondestructive measurement system based on smart mobile phone which characterized in that includes:
the light source module is used for emitting a visible light source and infrared light sources with different wave bands to reach the surface layer of the thin-skinned fruit and generate diffuse reflection, wherein the rated voltage of the visible light source is below 10V, and the rated power of the visible light source is below 5W; rated voltages of infrared light sources with different wave bands are all below 10V, and rated powers of the infrared light sources are all below 10W;
the device comprises a photo acquisition module, a photo processing module and a photo processing module, wherein the photo acquisition module is used for acquiring photos of the region of interest of the thin-skinned fruit under the irradiation of a visible light source and infrared light sources with different wave bands in a dark environment, wherein the diffuse reflection of the region of interest of the thin-skinned fruit is generated under the irradiation of the visible light source and the infrared light sources with different wave bands; the photos comprise photos of the interested area of the thin-skinned fruit subjected to diffuse reflection under the irradiation of a visible light source and photos of the interested area of the thin-skinned fruit subjected to diffuse reflection under the irradiation of infrared light sources in each wave band;
the intelligent mobile phone processing module is used for extracting the RGB value of the thin-skinned fruit interesting region in each picture, constructing an RGB-brix model based on the RGB value of the thin-skinned fruit interesting region, and obtaining the brix value of the thin-skinned fruit interesting region according to the RGB-brix model; the RGB-brix model is a model which is obtained by fitting and represents the incidence relation between the brix value and the RGB value of each photo; the method for establishing the RGB-brix model comprises the following steps: selecting a 350 x 350 pixel region in the center of the region of interest of the thin-skinned fruit in each picture and calculating the average RGB value of all pixel values in the region, wherein r is 1 ，g 1 ，b 1 ，r 2 ，g 2 ，b 2 And r 3 ，g 3 ，b 3 1,2 and 3 respectively refer to an image under a first waveband infrared light source, an image under a second waveband infrared light source and an image under a visible light source; measuring the sugar degree of the interested region of the thin-skin fruit by using a sugar degree meter as a real sugar degree value T k (k =1,2,3); according to the obtained pixel RGB value and the corresponding sugar degree value T k Modeling by using a multiple linear regression model, wherein the obtained model is as follows:
Y＝15.806-12.160×r 1 -13.100×g 1 +13.992×b 1 -27.991×r 2 +70.833×g 2 -
0.848×b 2 +5.656×r 3 -7.022×g 3 -3.495×b 3 +7.128×r 1 ×g 1 ×b 1 -2.870×r 2 ×g 2 ×b 2 -4.0790×r 3 ×g 3 ×b 3 ；
the method for obtaining the sugar degree value of the interested region of the thin-skinned fruit according to the RGB-sugar degree model comprises the following steps:
the mobile phone shoots pictures of the interested region of the thin-skinned fruit to be detected under different light sources, the mobile phone APP loads the pictures, the RGB value is calculated and substituted into the RGB-brix model to calculate the output value of the model, and the output value is the brix value of the interested region of the thin-skinned fruit to be detected.
6. The smartphone-based, non-destructive thin-skinned fruit brix measurement system of claim 5, wherein: the photo acquisition module is further configured to:
the method comprises the steps of shooting light of visible light after diffuse reflection occurs on the surface layer of the thin-skinned fruit by using a smart phone in a shooting mode, and shooting light of infrared light of different wave bands after the diffuse reflection occurs on the surface layer of the thin-skinned fruit in a professional mode under fixed parameters.
7. The smartphone-based, non-destructive thin-skinned fruit brix measurement system of claim 5, wherein: the smart phone processing module is further configured to:
selecting an MXN pixel area in the center of the thin-skin fruit interested area in each picture, calculating an average RGB value of all pixel values in the area, measuring the sugar degree of the thin-skin fruit interested area by using a sugar degree meter, and taking the measured value as a real sugar degree value;
and fitting the obtained average RGB value of the pixel values with the corresponding real sugar degree value to obtain an RGB-sugar degree model.
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