CN101551341B - Meat online non-destructive testing method and apparatus based on integration of image and spectrum information - Google Patents
Meat online non-destructive testing method and apparatus based on integration of image and spectrum information Download PDFInfo
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Abstract
The invention discloses a meat online non-destructive testing method and apparatus based on fusion of image and spectrum information, including a conveyor belt, a spectrum collection room, an image collection room, a camera mounted beam, an imaging source, a camera, a Y type optical fiber, a spectrograph, a data processing PC, two photosensors, a motor and a conveyor belt bracket. Through online collection of meat image and spectrum information, collecting feature information of characteristic meat quality, establishing a fused quantification prediction model based on image characteristics, spectrum characteristics and characteristics layer data of image and spectrum, using the obtained quantification prediction model to combine with quality evaluation system to establish a decision layer data fusion model based on image and spectrum for testing meat online. The invention uses complementarity and redundancy of the image information and the spectrum information to implement classification of materials and quality test during meat producing process according to optical feature of meat, which improving production efficiency.
Description
Technical field
The present invention relates to a kind of online test method and device, refer in particular to online lossless detection method of meat quality and device based on image and spectral information fusion at agricultural and animal products.
Background technology
Meat and meat products are one of human main food sources.Along with the raising of the level of consumption, the quality of meat products has caused that the consumer extensively payes attention to; Meat packing enterprise obtains stronger competitive power in order to guarantee the quality of product in intense market competition, raw meat and processing semi-manufacture are carried out quality monitoring and control, and product is carried out by the qualitative classification price, with the economic worth of maximization product.
It is to adopt artificial sensory evaluation method and chemical analysis method that traditional meat quality detects.Artificial sensory evaluation need be through the evaluation personnel of professional training, and the evaluation result subjectivity is strong, and is repeatable poor, and it is big to carry out large batch of online detection labour intensity; Chemical analysis method is to carry out destructiveness through chemical method to detect, complex steps, and testing result relies on technical level of operators and skill level, is not suitable for the online detection in the actual production process.
Machine vision technique is realized information acquisition by various imaging systems, utilize image processing techniques to extract and explain the feature of acquisition target by computing machine, in conjunction with various algorithm for pattern recognitions, can carry out quantitatively object, describe qualitatively and classification, in the agricultural and animal products Quality Detection, obtain using widely.Utilize machine vision technique to detect indexs such as the color of meat, texture distribution, shape size, bones, further analyzing and processing can also detect indexs such as the pH value of meat, elasticity, tender degree.Spectral analysis technique is a kind of effective ways to the Non-Destructive Testing of agricultural and animal products quality, and it utilizes agricultural and animal products that the characteristics such as absorption, scattering, reflection and transmission of light are determined the agricultural and animal products quality; Utilize the spectrum detection technique can be to the chemical composition of meat products, the pH value, and index such as tender degree detects.
This class is fast, accurate based on the Dynamic Non-Destruction Measurement speed of agricultural and animal products optical characteristics, be not subjected to subjective man's activity, the researcher has launched a large amount of research both at home and abroad, but mainly be to utilize image information or meat product is carried out classification with single index, can not inside and outside a plurality of index of quality of meat products be detected with spectral information.Meat products quality complexity, and its quality is relevant with its purposes, should be by its inside and outside many index Comprehensive Assessment.Therefore utilize the image of sample and the information of spectrum two aspects, utilization has the width of the information expansion Quality Detection of complementary character, utilization has the precision of the information raising quality evaluation of redundant character, inside and outside index to meat products detects, utilize decision-making level's information fusion, in conjunction with the quality requirements system in the actual production, meat quality is carried out accurate comprehensively evaluation carry out classify and grading, for optimizing the meat products production technology, improve meat products production economic benefit, ensureing that consumption of resident rights and interests and food quality have very important practical sense.
Summary of the invention
The object of the present invention is to provide a kind of method and device of the online Non-Destructive Testing of meat quality of merging based on image and spectral information.Image information and spectral information by the online acquisition meat, utilize image processing techniques and spectral analysis technique to carry out feature extraction to the information that obtains, obtain to characterize the characteristic information of meat index, set up each testing index based on characteristics of image, based on quantitative forecast model spectral signature and that merge based on image and spectrum characteristics layer data, utilize the quantitative forecast result to carry out decision-making level's data fusion, meat is carried out online detection evaluation.
The technical solution used in the present invention is as follows:
One, a kind of method of the online Non-Destructive Testing of meat quality of merging based on image and spectral information:
Gather in real time meat image information and spectral information, carry out information fusion and handle, the integrated quality of meat is detected, its concrete steps are as follows:
1) set up online detection model:
According to the requirement of meat quality index, determine to detect the weight of index and each index, set up the grade estimation system; The image of online acquisition meat and spectral information utilize image processing techniques and spectral analysis technique that the information that obtains is carried out data processing, extract the characteristic information that characterizes index to be detected; Off-line carries out the physical and chemical testing of each index to meat; The spectrum that utilize to extract and each index actual value of image feature information and test, foundation based on image, based on quality quantitative forecast model spectrum or image and the fusion of spectral signature layer; In conjunction with the grade estimation system of setting up, carry out decision-making level's fusion treatment, set up the online detection model of meat quality based on image and spectral information fusion;
2) carry out online detection:
During online detection, meat image information to be measured and spectral information are gathered the back in real time and by the meat products Quality Detection model of setting up the image and the spectral information of input are handled, extract feature, predict by single meat quality quantitative forecast model, meat quality is carried out online quality grading evaluation by decision-making level's data fusion model.
The image information of described online acquisition meat, be image in ultraviolet, visible light, near infrared or the infrared wavelength range, Image Information Processing comprises that the compensation of moving image and correction, background segment, target area extract, the characteristics of image that extracts comprises that color, the correlated characteristic that the texture distribution is described, Fat Distribution reaches the index that requires with meat pH value, elasticity and tender degree actual production extract, and foundation is based on the quality prediction model of image information.
After described spectral information is gathered,, correction level and smooth and differential preprocess method in conjunction with spectrum, extract the characteristic information that characterizes meat chemical composition, pH value, color, elasticity and tender degree index, comprise that characteristic wavelength, spectrum get main gene through decomposing gained, set up the quality prediction model based on spectral information.
The image of described extraction and spectrum characteristics value utilize artificial neural network, support vector machine method to carry out the characteristic layer information fusion; Adopt D-S evidence theory, Bayesian network method to carry out decision-making level's information fusion.
Described meat quality forecast model comprises the attribute classification system in each stage of fresh meat, raw meat or meat products meat products and production.
Two, a kind of device of the online Non-Destructive Testing of meat quality of merging based on image and spectral information:
Comprise that travelling belt, spectra collection chamber, image acquisition chamber, video camera articulate crossbeam, imaging source, video camera, y-type optical fiber, spectrometer, spectroscopic light source, data processing PC, two photoelectric sensors, motor, travelling belt support.The video camera that video camera is fixed on middle, image acquisition chamber articulates on the crossbeam, imaging source is installed around the video camera, first photoelectric sensor is fixed on the image acquisition chamber sidewall of video camera below, the travelling belt of placing meat is positioned at the video camera below and passes the image acquisition chamber, the motor-driven travelling belt rotates, the spectra collection chamber is installed in the travelling belt top, second photoelectric sensor is fixed on spectra collection chamber sidewall, meat enters the spectra collection chamber, second photoelectric sensor detects sample, send a signal to spectrometer, the spectrometer collection sends to data processing PC through the spectral information of y-type optical fiber transmission, meat transmits continuously and enters the image acquisition chamber, and the detected signal of first photoelectric sensor is given video camera, and the image information of gathering meat is connected to data processing PC.
The beneficial effect that the present invention has is:
1, the present invention is according to the optical characteristics of meat, organically combine image processing techniques and spectral analysis technique, adopt the information fusion disposal route, utilize the complementarity and the redundancy of image information and spectral information, combine with the appraisement system of the actual production processing meat quality that requires, meat quality is evaluated.
2, the present invention's online raw material classification of being used for the meat products process of manufacture is selected, process quality control, meat products end product quality detect, and is auxiliary and replace professional testing staff, and the liberation labour gets rid of artificial subjective factor, enhances productivity.
The present invention utilizes the optical characteristics of meat, image information and spectral information are carried out Data Fusion, inside and outside a plurality of index of quality to meat are measured, classify according to the requirement to each quality in the actual production, be used for the online detection of meat products process of manufacture, intelligent classification processing, the raw meat in the meat products process of realizing cold fresh meat quality classified, the quality of monitoring raw meat changes, can optimize technology for processing meat food, strict control product quality, the economic worth of raising meat and meat products.
Description of drawings
Fig. 1 is a pick-up unit structural representation of the present invention.
Among the figure: 1. travelling belt, 2. spectra collection chamber, 3. image acquisition chamber, 4. video camera articulates crossbeam, 5. imaging source, 6. video camera, 7.Y type optical fiber, 8. spectra collection instrument, 9. spectroscopic light source, 10. data processing PC, 11. photoelectric sensor, 12. photoelectric sensors, 13. motors, 14. travelling belt supports.
Fig. 2 is the specific embodiment of the invention (fresh pork flavor evaluation) technology path synoptic diagram.
Embodiment
As shown in Figure 1, the present invention includes travelling belt 1, spectra collection chamber 2, image acquisition chamber 3, video camera and articulate crossbeam 4, imaging source 5, video camera 6, y-type optical fiber 7, spectrometer 8, spectroscopic light source 9, data processing PC10, two photoelectric sensors 11,12, motor 13, travelling belt support 14; The video camera that video camera 6 is fixed on 3 middles, image acquisition chamber articulates on the crossbeam 4, imaging source 5 is installed around the video camera 6, first photoelectric sensor 11 is fixed on image acquisition chamber 3 sidewalls of video camera 6 belows, the travelling belt 1 of placing meat is positioned at video camera 6 belows and passes image acquisition chamber 3, motor 13 drives travelling belt 1 and rotates, spectra collection chamber 2 is installed in travelling belt 1 top, second photoelectric sensor 12 is fixed on spectra collection chamber 2 sidewalls, meat enters spectra collection chamber 2, second photoelectric sensor 12 detects sample, send a signal to spectrometer 8, the spectral information that spectrometer 8 is gathered through y-type optical fiber 7 transmission sends to data processing PC10, meat transmits continuously and enters image acquisition chamber 3, the first photoelectric sensors, 11 detected signals to video camera 6, and the image information of gathering meat is connected to data processing PC10.
Be example with hierarchical detection in the present embodiment to edible fresh meat, longissimus dorsi muscle with the pork trunk is an object, detect PSE (pale, soft, exudative) meat in the fresh meat and DFD (dry, hard, look dark) meat, and intramuscular fat content is estimated as an edible quality index.
As shown in Figure 2, the implementation process of present embodiment is as follows: according to the characteristics of PSE meat and DFD meat, determining to detect index is yellowish pink (adopting CIE L*a*b* colour system), elasticity, tender degree, seepage of water, pH value, fat content (2%～4% for best), sets up the fresh pork appraisement system; Gather PSE meat, DFD meat, when the image information of normal fresh meat sample and spectral information, sample levels is placed on the travelling belt 1 that is driven by motor 13, enter spectra collection chamber 2, be detected during through second photoelectric sensor 12, second photoelectric sensor 12 sends a signal to spectrometer 8, the sample spectral signals that spectrometer 8 is gathered by y-type optical fiber 2 transmission, pass to data processing PC 10, sample transmits continuously and enters image acquisition chamber 3, be detected during through first photoelectric sensor 11, the first photoelectric sensor device 11 sends a signal to video camera 6, and the image information of video camera 6 collected specimens passes to data processing PC 10; Off-line carries out code test to each index physical and chemical indexs such as sample CIE L*a*b* color, elasticity, tender degree, seepage of water, pH value, fat contents and measures; The image information that obtains is carried out pre-service, comprise image is carried out motion compensation and correction, extract the longissimus dorsi muscle zone; Calculate the target area average RGB value of extracting and marble grain distribution situation, and analyze the correlativity of itself and other each index, searching can characterize the characteristics of image of pH value, elasticity, tender degree, seepage of water, fat content; To the spectrum that obtains proofread and correct, smoothly, multiple preprocess method such as differential, adopt progressively linear regression, principal component analysis (PCA), partial least square method, successive projection is sought definite features that can characterize each index such as track algorithm, genetic algorithm, comprise major component, the offset minimum binary main gene, characteristic wavelength etc., the forecast model of a foundation index; Utilize characteristics of image, spectral signature and spectrum and characteristics of image layer information fusion to handle, set up the forecast model of each index; The bond quality overall evaluation system carrying out decision-making level's information fusion processing, is judged its quality to each index prediction result, sets up the meat products quality on-line detection system; During online detection, detected sample spectrum is with the spectra collection process of above-mentioned modeling sample, after spectrum and the image acquisition, import data processing PC (10) into, data processing PC carries out pre-service, feature extraction according to the quality on-line detection system of setting up to raw data, the fusion of characteristic layer and data Layer, judge that revise product are PSE (pale, soft, exudative) meat or DFD (dry, hard, look dark) meat, still are normal meat, and provide its fat content.
Claims (5)
1. meat online non-destructive testing method that merges based on image and spectral information is characterized in that the step of this method is as follows:
1) set up online detection model:
According to the requirement of meat quality index, determine to detect the weight of index and each index, set up the grade estimation system; By the device of online detection, the image of online acquisition meat and spectral information utilize image processing techniques and spectral analysis technique that the information that obtains is carried out data processing, extract the characteristic information that characterizes index to be detected; Off-line carries out the physical and chemical testing of each index to meat; The spectrum that utilize to extract and each index actual value of image feature information and test, foundation based on image, based on quality quantitative forecast model spectrum or image and the fusion of spectral signature layer; In conjunction with the grade estimation system of setting up, carry out decision-making level's fusion treatment, set up the online detection model of meat quality based on image and spectral information fusion;
2) carry out online detection:
During online detection, meat image information to be measured and spectral information are gathered the back in real time and by the meat products Quality Detection model of setting up the image and the spectral information of input are handled, extract feature, predict by single meat quality quantitative forecast model, meat quality is carried out online quality grading evaluation by decision-making level's data fusion model;
The device of described online detection: comprise that travelling belt (1), spectra collection chamber (2), image acquisition chamber (3), video camera articulate crossbeam (4), imaging source (5), video camera (6), y-type optical fiber (7), spectrometer (8), spectroscopic light source (9), data processing PC (10), two photoelectric sensors (11,12), motor (13), travelling belt support (14); The video camera that video camera (6) is fixed on middle, image acquisition chamber (3) articulates on the crossbeam (4), imaging source (5) is installed around the video camera (6), first photoelectric sensor (11) is fixed on image acquisition chamber (3) sidewall of video camera (6) below, the travelling belt (1) of placing meat is positioned at video camera (6) below and passes image acquisition chamber (3), motor (13) drives travelling belt (1) and rotates, spectra collection chamber (2) is installed in travelling belt (1) top, second photoelectric sensor (12) is fixed on spectra collection chamber (2) sidewall, meat enters spectra collection chamber (2), second photoelectric sensor (12) detects sample, send a signal to spectrometer (8), the spectral information that spectrometer (8) is gathered through y-type optical fiber (7) transmission sends to data processing PC (10), meat transmits continuously and enters image acquisition chamber (3), the detected signal of first photoelectric sensor (11) is given video camera (6), and the image information of gathering meat is connected to data processing PC (10).
2. a kind of meat online non-destructive testing method according to claim 1 based on image and spectral information fusion, it is characterized in that: the image information of described online acquisition meat, be ultraviolet, visible light, image near infrared or the infrared wavelength range, Image Information Processing comprises the compensation and the correction of moving image, background segment, extract the target area, the characteristics of image that extracts comprises color, texture distributes and describes, Fat Distribution reaches and meat pH value, the correlated characteristic of the index that elasticity and tender degree actual production require extracts, and sets up the quality prediction model based on image information.
3. a kind of meat online non-destructive testing method according to claim 1 based on image and spectral information fusion, it is characterized in that: after described spectral information is gathered,, correction level and smooth and differential preprocess method in conjunction with spectrum, extract the characteristic information that characterizes meat chemical composition, pH value, color, elasticity and tender degree index, comprise that characteristic wavelength, spectrum get main gene through decomposing gained, set up the quality prediction model based on spectral information.
4. a kind of meat online non-destructive testing method according to claim 1 based on image and spectral information fusion, it is characterized in that: the image of described extraction and spectrum characteristics value utilize artificial neural network, support vector machine method to carry out the characteristic layer information fusion; Adopt D-S evidence theory, Bayesian network method to carry out decision-making level's information fusion.
5. a kind of meat online non-destructive testing method based on image and spectral information fusion according to claim 1, it is characterized in that: described meat quality forecast model comprises the attribute classification system in each stage of fresh meat, raw meat or meat products meat products and production.
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