CN110244009A - A kind of quick identification detection system and method for honey quality - Google Patents

A kind of quick identification detection system and method for honey quality Download PDF

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CN110244009A
CN110244009A CN201910525409.8A CN201910525409A CN110244009A CN 110244009 A CN110244009 A CN 110244009A CN 201910525409 A CN201910525409 A CN 201910525409A CN 110244009 A CN110244009 A CN 110244009A
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万凌燕
黄春
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Liupanshui Food And Drug Inspection And Testing Institute
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    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
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    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
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    • G06V10/40—Extraction of image or video features
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
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Abstract

The invention belongs to honey authentication technique fields, disclose the quick identification detection system and method for a kind of honey quality, comprising: honey image capture module, smell acquisition module, honey quality detection module, main control module, characteristic extracting module, image comparison module, determination module, display module.The present invention is very short to the acquisition time of honey laser image to be measured by honey quality detection module, directly uses laser illumination honey to be measured, and the representation of laser facula for then receiving its formation can be analyzed；, can be different by attenuation degree of the light to different component when being detected using laser diffusion spectrum picture technology to complex material, to distinguish the different chemical compositions containing same functional group.Near-infrared spectrum technique is used compared to rising, avoids its deficiency to complex system analysis dynamics, and be easy to implement on-line checking；Meanwhile the accuracy to honey image characteristics extraction can be improved by characteristic extracting module.

Description

A kind of quick identification detection system and method for honey quality
Technical field
The invention belongs to honey authentication technique field more particularly to a kind of quick identification detection method systems of honey quality And method.
Background technique
Honeybee takes the nectar or secretion that water content is about 75% from the spending of plant, and is stored in oneself second stomach, In vivo under the action of a variety of conversions, various vitamins, minerals and amino acid were fermented repeatedly by 15 days or so and is enriched to one When fixed numerical value, at the same the polysaccharide transformation adult body in nectar can directly be absorbed simple sugar glucose, fructose, moisture content is few It is stored into nest hole in 23%, is sealed with beeswax.Honey is the supersaturated solution of sugar, and when low temperature can generate crystallization, generates and crystallizes Be glucose, the part for not generating crystallization is mainly fructose.However, the quick identification detection process of existing honey quality is to bee The detection method of sweet quality have it is time-consuming, laborious, and the disadvantages of testing cost is higher；Meanwhile not to honey image characteristics extraction Accurately, it influences accurately to identify honey.
In conclusion problem of the existing technology is: the quick identification detection process of existing honey quality is to honey product The detection method of matter have it is time-consuming, laborious, and the disadvantages of testing cost is higher；Meanwhile it is inaccurate to honey image characteristics extraction, Influence accurately identifies honey.
Summary of the invention
In view of the problems of the existing technology, the present invention provides a kind of quick identification detection system of honey quality and sides Method.
The invention is realized in this way a kind of quick identification detection method of honey quality, the honey quality it is quick Detection method includes the following steps for identification:
Step 1 acquires honey image data using image pick-up device by honey image capture module；Mould is acquired by smell Block acquires honey odor data using smell sensor；Honey quality is detected using laser equipment by honey quality detection module Data；
Step 2, main control module dispatch feature extraction module extract the characteristic of the honey image of acquisition using extraction procedure According to；
Step 3 will acquire honey image and real honey image using comparison program by image comparison module and carry out pair Than；Denoising honey image is obtained to Solving Partial Differential Equations using the method for iteration；
Noise image is specifically included based on the fully differential restructing algorithm of non-local mean regular terms:
1) basic model of the fully differential restructing algorithm based on non-local mean regular terms indicates are as follows:
Wherein α is the weight of non-local mean regular terms, and Du is the gradient of honey image, by introducing auxiliary variable Du= W, u=x, and can be obtained using Augmented Lagrange method:
Wherein α, β and θ respectively indicate the coefficient of corresponding penalty term, and v, γ and λ indicate corresponding Lagrange multiplier, By being divided into w, u, tri- subproblems of x are iterated solution；
2) by the solution to u subproblem, to obtain the new iterative reconstruction value of honey image u, concrete model can be indicated Are as follows:
uk+1=uk-ηd；
Wherein η=abs (dTd/dTGd optimal step size, G=(β D) are indicatedTD+θΙ+μATA), Ι is unit matrix, d=DT(β Du-v)-γ+θ(u-x)-βDTw+AT(μ (Au-y)-λ) is gradient direction, and k obtains current iteration knot for indexing the number of iterations Fruit uk+1Afterwards, subsequent processes are sent to, for judging whether iterated conditional meets and assume to handle more；
Step 4 determines the true of honey according to detection honey quality and comparing result using decision procedure by determination module It is false；
Step 5 utilizes honey image, the honey smell, honey quality, spy of display display acquisition by display module It levies data, comparing result, determine result.
Further, the honey quality detection detection method of the quick identification detection method of the honey quality is as follows:
1) honey sample to be measured is taken, heating water bath is carried out to honey to be measured, room temperature is cooled to, to obtain homogeneous fluid The honey to be measured of state；The near infrared spectrum of honey to be measured is acquired, and the near infrared spectrum is pre-processed, with heredity Algorithm analyzes near infrared spectrum after pretreatment, filters out the characteristic wavelength of the honey to be measured；
2) operation wavelength that laser is determined according to the characteristic wavelength, the honey to be measured described in the laser illumination, Corresponding light spot image is collected by camera；
3) light spot image is handled, and extracts the image features of the light spot image；
4) it is calculated using the relationship foundation between described image characteristic parameter and the quality parameter of the honey to be measured, To obtain the quality parameter of the honey to be measured.
Further, the feature extracting method of the quick identification detection method of the honey quality is as follows:
(1) adulterated at swarmming by parser analysis difference plant nectar source, different sources, different storage phases and difference The smell finger-print linearly or nonlinearly data structure property of honey, it is linear using Wilks criterion, independent component analysis ICA etc. Data Dimensionality Reduction extractive technique, while exploring the nonlinear datas dimensionality reductions such as core principle component analysis KPCA, Self-organizing Maps SOM and extracting skill Art；
(2) analysis represent honey differentiation, for attribute classification eigenvector information extract mechanism, find honey it is poor The feature vector of alienation information evaluates the otherness discriminating power of its feature vector, eliminates classify unknown display information and background letter Breath enhances ratio of the differentiation information in fingerprint matrix, reaches the target of differentiation characteristic information between extracting honey.
The honey for the quick identification detection method based on the honey quality that another object of the present invention is to provide a kind of The quick identification detection system of the quick identification detection system of quality, the honey quality includes:
Honey image capture module, connect with main control module, for acquiring honey image data by image pick-up device；
Smell acquisition module, connect with main control module, for acquiring honey odor data by smell sensor；
Honey quality detection module, connect with main control module, for detecting honey quality data by laser equipment；
Main control module, with honey image capture module, smell acquisition module, honey quality detection module, feature extraction mould Block, image comparison module, determination module, display module connection, for being worked normally by main controller controls modules；
Characteristic extracting module is connect with main control module, the feature of the honey image for extracting acquisition by extraction procedure Data；
Image comparison module, connect with main control module, for that will acquire honey image and real honey by comparison program Image compares；
Determination module is connect with main control module, for being sentenced by decision procedure according to detection honey quality and comparing result Determine the true and false of honey；
Display module is connect with main control module, for honey image, the honey smell, bee by display display acquisition Sweet quality, comparing result, determines result at characteristic.
Another object of the present invention is to provide a kind of honey of quick identification detection method using the honey quality Quality detecting system.
Advantages of the present invention and good effect are as follows: the present invention is cheap by honey quality detection module recognition detection expense； Honey quality is detected using laser diffusion spectrum picture technology, Instrument purchase expense is well below traditional near infrared spectrum Required instrument in technology, while after establishing model, the consumptive material expense for detecting honey quality can be ignored substantially；To honey to be measured The acquisition time of laser image is very short, directly uses laser illumination honey to be measured, then receives the laser light of its formation Spot image can be analyzed；After model foundation, it can be neglected substantially using the model calculating time of common desktop computer Slightly；It, can decaying by light to different component when being detected using laser diffusion spectrum picture technology to complex material Degree is different, to distinguish the different chemical compositions containing same functional group, has compared using near-infrared spectrum technique, has avoided it To the deficiency of complex system analysis dynamics, and it is easy to implement on-line checking；Meanwhile it can be improved pair by characteristic extracting module The accuracy of honey image characteristics extraction.
Detailed description of the invention
Fig. 1 is the quick identification detection method flow chart of honey quality provided in an embodiment of the present invention.
Fig. 2 is the quick identification detection system structure of honey quality provided in an embodiment of the present invention；
In figure: 1, honey image capture module；2, smell acquisition module；3, honey quality detection module；4, main control module； 5, characteristic extracting module；6, image comparison module；7, determination module；8, display module.
Specific embodiment
In order to further understand the content, features and effects of the present invention, the following examples are hereby given, and cooperate attached drawing Detailed description are as follows.
Structure of the invention is explained in detail with reference to the accompanying drawing.
As shown in Figure 1, detection method includes the following steps for the quick identification of honey quality provided by the invention:
S101: honey image data is acquired using image pick-up device by honey image capture module；Pass through smell acquisition module Honey odor data is acquired using smell sensor；Honey quality number is detected using laser equipment by honey quality detection module According to；
S102: main control module dispatch feature extraction module extracts the characteristic of the honey image of acquisition using extraction procedure According to；
S103: honey image and real honey image will be acquired using comparison program by image comparison module and carried out pair Than；Denoising honey image is obtained to Solving Partial Differential Equations using the method for iteration；
Noise image is specifically included based on the fully differential restructing algorithm of non-local mean regular terms:
1) basic model of the fully differential restructing algorithm based on non-local mean regular terms indicates are as follows:
Wherein α is the weight of non-local mean regular terms, and Du is the gradient of honey image, by introducing auxiliary variable Du= W, u=x, and can be obtained using Augmented Lagrange method:
Wherein α, β and θ respectively indicate the coefficient of corresponding penalty term, and v, γ and λ indicate corresponding Lagrange multiplier, By being divided into w, u, tri- subproblems of x are iterated solution；
2) by the solution to u subproblem, to obtain the new iterative reconstruction value of honey image u, concrete model can be indicated Are as follows:
uk+1=uk-ηd；
Wherein η=abs (dTd/dTGd optimal step size, G=(β D) are indicatedTD+θΙ+μATA), Ι is unit matrix, d=DT(β Du-v)-γ+θ(u-x)-βDTw+AT(μ (Au-y)-λ) is gradient direction, and k obtains current iteration knot for indexing the number of iterations Fruit uk+1Afterwards, subsequent processes are sent to, for judging whether iterated conditional meets and assume to handle more；
S104: the true of honey is determined according to detection honey quality and comparing result using decision procedure by determination module It is false；
S105: honey image, the honey smell, honey quality, feature of display display acquisition are utilized by display module Data, determine result at comparing result.
As shown in Fig. 2, the quick identification detection system of honey quality provided in an embodiment of the present invention includes: that honey image is adopted Collect module 1, smell acquisition module 2, honey quality detection module 3, main control module 4, characteristic extracting module 5, image comparison module 6, determination module 7, display module 8.
Honey image capture module 1 is connect with main control module 4, for acquiring honey image data by image pick-up device；
Smell acquisition module 2 is connect with main control module 4, for acquiring honey odor data by smell sensor；
Honey quality detection module 3 is connect with main control module 4, for detecting honey quality data by laser equipment；
Main control module 4 is mentioned with honey image capture module 1, smell acquisition module 2, honey quality detection module 3, feature Modulus block 5, image comparison module 6, determination module 7, display module 8 connect, for passing through main controller controls modules just Often work；
Characteristic extracting module 5 is connect with main control module 4, the spy of the honey image for extracting acquisition by extraction procedure Levy data；
Image comparison module 6 is connect with main control module 4, for that will acquire honey image and real bee by comparison program Sweet image compares；
Determination module 7 is connect with main control module 4, for passing through decision procedure according to detection honey quality and comparing result Determine the true and false of honey；
Display module 8 is connect with main control module 4, for by display display acquisition honey image, honey smell, Honey quality, comparing result, determines result at characteristic.
3 detection method of honey quality detection module provided by the invention is as follows:
1) honey sample to be measured is taken, heating water bath is carried out to honey to be measured, room temperature is cooled to, to obtain homogeneous fluid The honey to be measured of state；The near infrared spectrum of honey to be measured is acquired, and the near infrared spectrum is pre-processed, with heredity Algorithm analyzes near infrared spectrum after pretreatment, filters out the characteristic wavelength of the honey to be measured；
2) operation wavelength that laser is determined according to the characteristic wavelength, the honey to be measured described in the laser illumination, Corresponding light spot image is collected by camera；
3) light spot image is handled, and extracts the image features of the light spot image；
4) it is calculated using the relationship foundation between described image characteristic parameter and the quality parameter of the honey to be measured, To obtain the quality parameter of the honey to be measured.
5 extracting method of characteristic extracting module provided by the invention is as follows:
(1) adulterated at swarmming by parser analysis difference plant nectar source, different sources, different storage phases and difference The smell finger-print linearly or nonlinearly data structure property of honey, utilizes the lines such as Wilks criterion, independent component analysis (ICA) Property Data Dimensionality Reduction extractive technique, while exploring the nonlinear datas dimensionality reductions such as core principle component analysis (KPCA), Self-organizing Maps (SOM) Extractive technique；
(2) analysis represent honey differentiation, for attribute classification eigenvector information extract mechanism, find honey it is poor The feature vector of alienation information evaluates the otherness discriminating power of its feature vector, eliminates classify unknown display information and background letter Breath reaches the mesh of differentiation characteristic information between extracting honey to enhance ratio of the differentiation information in fingerprint matrix Mark.
The above is only the preferred embodiments of the present invention, and is not intended to limit the present invention in any form, Any simple modification made to the above embodiment according to the technical essence of the invention, equivalent variations and modification, belong to In the range of technical solution of the present invention.

Claims (5)

1. a kind of quick identification detection method of honey quality, which is characterized in that the quick identification detection side of the honey quality Method the following steps are included:
Step 1 acquires honey image data using image pick-up device by honey image capture module；Pass through smell acquisition module benefit Honey odor data is acquired with smell sensor；Honey quality number is detected using laser equipment by honey quality detection module According to；
Step 2, main control module dispatch feature extraction module extract the characteristic of the honey image of acquisition using extraction procedure；
Step 3 will acquire honey image using comparison program by image comparison module and compare with real honey image； Denoising honey image is obtained to Solving Partial Differential Equations using the method for iteration；
Noise image is specifically included based on the fully differential restructing algorithm of non-local mean regular terms:
1) basic model of the fully differential restructing algorithm based on non-local mean regular terms indicates are as follows:
Wherein α is the weight of non-local mean regular terms, and Du is the gradient of honey image, by introducing auxiliary variable Du=w, u =x, and can be obtained using Augmented Lagrange method:
Wherein α, β and θ respectively indicate the coefficient of corresponding penalty term, and v, γ and λ indicate corresponding Lagrange multiplier, pass through It is divided into w, u, tri- subproblems of x are iterated solution；
2) by the solution to u subproblem, to obtain the new iterative reconstruction value of honey image u, concrete model be may be expressed as:
uk+1=uk-ηd；
Wherein η=abs (dTd/dTGd optimal step size, G=(β D) are indicatedTD+θΙ+μATA), Ι is unit matrix, d=DT(βDu- v)-γ+θ(u-x)-βDTw+AT(μ (Au-y)-λ) is gradient direction, and k obtains current iteration result u for indexing the number of iterationsk +1Afterwards, subsequent processes are sent to, for judging whether iterated conditional meets and assume to handle more；
Step 4 determines the true and false of honey according to detection honey quality and comparing result using decision procedure by determination module；
Step 5 utilizes honey image, the honey smell, honey quality, characteristic of display display acquisition by display module According to, comparing result, determine result.
2. the quick identification detection method of honey quality as described in claim 1, which is characterized in that the honey quality it is fast The honey quality detection detection method that speed identifies detection method is as follows:
1) honey sample to be measured is taken, heating water bath is carried out to honey to be measured, room temperature is cooled to, to obtain homogeneous fluid state Honey to be measured；The near infrared spectrum of honey to be measured is acquired, and the near infrared spectrum is pre-processed, with genetic algorithm Near infrared spectrum after pretreatment is analyzed, the characteristic wavelength of the honey to be measured is filtered out；
2) operation wavelength of laser is determined according to the characteristic wavelength, honey to be measured, passes through described in the laser illumination Camera collects corresponding light spot image；
3) light spot image is handled, and extracts the image features of the light spot image；
4) it is calculated using the relationship foundation between described image characteristic parameter and the quality parameter of the honey to be measured, to obtain Obtain the quality parameter of the honey to be measured.
3. the quick identification detection method of honey quality as described in claim 1, which is characterized in that the honey quality it is fast The feature extracting method that speed identifies detection method is as follows:
(1) pass through parser analysis difference plant nectar source, different sources, different storage phases and different adulterated ingredient honey Smell finger-print linearly or nonlinearly data structure property, utilizes the linear datas such as Wilks criterion, independent component analysis ICA Dimensionality reduction extractive technique, while the nonlinear datas dimensionality reduction extractive technique such as explore core principle component analysis KPCA, Self-organizing Maps SOM；
(2) analysis represent honey differentiation, for attribute classification eigenvector information extract mechanism, find honey differentiation The feature vector of information evaluates the otherness discriminating power of its feature vector, eliminates classify unknown display information and background information, increases Strong ratio of the differentiation information in fingerprint matrix, reaches the target of differentiation characteristic information between extracting honey.
4. a kind of quick identification of honey quality of the quick identification detection method based on honey quality described in claim 1 detects System, which is characterized in that the quick identification detection system of the honey quality includes:
Honey image capture module, connect with main control module, for acquiring honey image data by image pick-up device；
Smell acquisition module, connect with main control module, for acquiring honey odor data by smell sensor；
Honey quality detection module, connect with main control module, for detecting honey quality data by laser equipment；
Main control module, with honey image capture module, smell acquisition module, honey quality detection module, characteristic extracting module, figure As contrast module, determination module, display module connection, for being worked normally by main controller controls modules；
Characteristic extracting module is connect with main control module, the characteristic of the honey image for extracting acquisition by extraction procedure；
Image comparison module, connect with main control module, for that will acquire honey image and real honey image by comparison program It compares；
Determination module is connect with main control module, for determining bee according to detection honey quality and comparing result by decision procedure Sweet is true and false；
Display module is connect with main control module, for honey image, the honey smell, honey product by display display acquisition Matter, comparing result, determines result at characteristic.
5. a kind of honey quality of quick identification detection method using honey quality described in claims 1 to 3 any one is examined Examining system.
CN201910525409.8A 2019-06-18 2019-06-18 A kind of quick identification detection system and method for honey quality Pending CN110244009A (en)

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CN102313715A (en) * 2011-08-08 2012-01-11 中国农业大学 Method for detecting honey quality base on laser technology
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