CN110487808A - It is a kind of for automating the hygienic state detection method and system of frying pan pot gallbladder - Google Patents
It is a kind of for automating the hygienic state detection method and system of frying pan pot gallbladder Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8806—Specially adapted optical and illumination features
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/90—Investigating the presence of flaws or contamination in a container or its contents
- G01N21/9018—Dirt detection in containers
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/90—Investigating the presence of flaws or contamination in a container or its contents
- G01N21/9072—Investigating the presence of flaws or contamination in a container or its contents with illumination or detection from inside the container
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Abstract
The present invention provides a kind of for automating the hygienic state detection method of frying pan pot gallbladder, comprising: obtains the present image of pot gallbladder；The image comparison of present image and normal pot gallbladder is subjected to abnormal conditions detection；If detecting any abnormal conditions, being judged as in insanitariness and alarming；Wherein, abnormal conditions detection includes abnormal color detection, abnormal skin texture detection and/or abnormal area detection.Hygienic state detection method for automating frying pan pot gallbladder of the invention, which can be improved, checks on the quality.
Description
Technical field
The present embodiments relate to detection technique fields more particularly to a kind of for automating the hygienic state of frying pan pot gallbladder
Detection method and system.
Background technique
Pot gallbladder in automation frying pan is the main executing agency for completing vegetable production.On the one hand pot gallbladder is by external heat
Amount is conducted to the raw material and seasoning of vegetable in pot, and the function of stirring and frying is on the other hand completed by rotating and turn over,
Therefore, the working condition of pot gallbladder directly affects the quality of vegetable production.Existing is to automate journey by manual periodic inspection
Spend it is lower, easily missing inspection or detection do not find the problem and cause safety and sanitation accident.
Summary of the invention
The purpose of the embodiment of the present invention be to propose a kind of hygienic state detection method for automating frying pan pot gallbladder and
System can be improved and check on the quality.
For this purpose, the embodiment of the present invention uses following technical scheme:
In a first aspect, the embodiment of the present invention provides a kind of for automating the hygienic state detection method of frying pan pot gallbladder, packet
It includes:
Obtain the present image of pot gallbladder；
The image comparison of the present image and normal pot gallbladder is subjected to abnormal conditions detection；
If detecting any abnormal conditions, being judged as in insanitariness and alarming；
Wherein, abnormal conditions detection includes abnormal color detection, abnormal skin texture detection and/or abnormal area detection.
Further, the image comparison of the present image and normal pot gallbladder is carried out abnormal conditions detection includes:
Obtain RGB preset value, textural characteristics preset value and/or the predeterminable area label of the image of normal pot gallbladder；
The rgb value and the comparison of RGB preset value for obtaining the present image carry out abnormal color detection；
The texture eigenvalue and the comparison of textural characteristics preset value for obtaining the present image carry out abnormal skin texture detection；
The zone marker and predeterminable area label comparison for obtaining the present image carry out abnormal area detection.
Further, the rgb value and RGB preset value for obtaining the present image compare progress abnormal color detection
RGB preset value is divided into tri- preset values of R, G, B；
The present image of the pot gallbladder is divided into tri- Color Channel components of R, G, B；
Three Color Channel components compare with corresponding preset value respectively and combine judgement；
It is corresponding, detect that any abnormal conditions include:
If joint judging result and the image of the normal pot gallbladder are inconsistent, it is judged as abnormal color；
Conversely, being then judged as normal color.
Further, the texture eigenvalue and the comparison of textural characteristics preset value for obtaining the present image carry out abnormal texture
Detection includes:
The present image of the pot gallbladder is subjected to gridding processing；
The texture eigenvalue of image in grid and the textural characteristics preset value of the normal pot gallbladder are compared；
It is corresponding, detect that any abnormal conditions include:
If the textural characteristics preset value difference of texture characteristic amount and the normal pot gallbladder in grid is greater than default difference value,
Then it is judged as abnormal texture；
Conversely, being then judged as normal texture.
Further, the zone marker and predeterminable area label comparison for obtaining the present image carry out abnormal area detection
Include:
The present image is subjected to binary conversion treatment and marks off target area to be compared；
The zone marker of target area and the zone marker of the normal pot gallbladder are compared；
It is corresponding, detect that any abnormal conditions include:
If the zone marker of target area and the zone marker of normal pot gallbladder are inconsistent, it is judged as abnormal area；
Conversely, being then judged as normal region.
Further, marking off target area to be compared includes:
The area threshold of the target area is determined according to preset detection sensitivity；
Target area to be compared is marked off according to the area threshold.
Further, the image comparison of the present image and normal pot gallbladder also wrap before abnormal conditions detection
It includes:
The present image of the pot gallbladder is subjected to white balance processing.
Second aspect, the embodiment of the present invention provide a kind of for automating the hygienic state detection system of frying pan pot gallbladder, packet
It includes:
Image collection module, for obtaining the present image of pot gallbladder；
Image judgment module, for the image comparison of the present image and normal pot gallbladder to be carried out abnormal conditions detection；
If detecting any abnormal conditions, being judged as in insanitariness and alarming；
Wherein, abnormal conditions detection includes abnormal color detection, abnormal skin texture detection and/or abnormal area detection.
Further, the system also includes features to obtain module,
The feature obtains module, the RGB preset value of the image for obtaining normal pot gallbladder, textural characteristics preset value and/
Or predeterminable area label.
Further, which further includes lighting module；
The lighting module is used for light filling.
The embodiment of the present invention has the beneficial effect that
The embodiment of the present invention carries out abnormal conditions detection by the image comparison of present image and normal pot gallbladder and defends to obtain
Raw situation improves the degree of automation, and without manual inspection, reduces missing inspection and detection does not find the problem and causes to defend safely
It makes trouble former, to reduce operations risks.
Detailed description of the invention
Fig. 1 is that the process for the hygienic state detection method for automating frying pan pot gallbladder that the embodiment of the present invention one provides is shown
It is intended to.
Specific embodiment
To keep the technical problems solved, the adopted technical scheme and the technical effect achieved by the invention clearer, below
It will the technical scheme of the embodiment of the invention will be described in further detail in conjunction with attached drawing, it is clear that described embodiment is only
It is a part of the embodiment of the present invention, instead of all the embodiments.
Embodiment one
The present embodiment provides a kind of for automating the hygienic state detection method of frying pan pot gallbladder, can obtain a pot gallbladder automatically
Image detect sanitary conditions, improve the degree of automation, and without manual inspection, reduce missing inspection and detection is not found the problem
And cause safety and sanitation accident.
Fig. 1 is that the process for the hygienic state detection method for automating frying pan pot gallbladder that the embodiment of the present invention one provides is shown
It is intended to.As described in Figure 1, which specifically comprises the following steps:
S11 obtains the present image of pot gallbladder.
S12 carries out white balance processing to the present image of the pot gallbladder.
The colour temperature of adjust automatically present image provides reliable initial data with accurate reproduction color for abnormality detection.
The image comparison of the present image and normal pot gallbladder is carried out abnormal conditions detection by S13.
Wherein, abnormal conditions detection includes abnormal color detection, abnormal skin texture detection and/or abnormal area detection.
Specifically, obtaining the RGB preset value of the image of normal pot gallbladder, textural characteristics preset value and/or predeterminable area label.
The rgb value and the comparison of RGB preset value for obtaining the present image carry out abnormal color detection.Abnormal color detection is used
In the abnormal nigrescence of detection pot gallbladder inner surface and/or jaundice.
The texture eigenvalue and the comparison of textural characteristics preset value for obtaining the present image carry out abnormal skin texture detection.It is abnormal
Skin texture detection be used for detect regional area be burned and/or coating sintering.
The zone marker and predeterminable area label comparison for obtaining the present image carry out abnormal area detection.Abnormal area
Detect the coating stripping and vegetable residue for detecting large area.
S14, if detecting any abnormal conditions, being judged as in insanitariness and alarming.
The present embodiment carries out abnormal conditions detection by the image comparison of present image and normal pot gallbladder to obtain hygienic feelings
Condition improves the degree of automation, and without manual inspection, reduces missing inspection and detection does not find the problem and causes safety and sanitation thing
Therefore to it reduce operations risks.
Embodiment two
The present embodiment on the basis of the above embodiments, has refined each method for detecting abnormality.The detection method specifically includes
Following steps:
S21 obtains the present image of pot gallbladder.
The present image of the pot gallbladder is carried out white balance processing by S22.
The colour temperature of adjust automatically present image provides reliable initial data with accurate reproduction color for abnormality detection.
The image comparison of the present image and normal pot gallbladder is carried out abnormal conditions detection by S23.
Wherein, abnormal conditions detection includes abnormal color detection, abnormal skin texture detection and/or abnormal area detection.
Firstly, obtaining the RGB preset value of the image of normal pot gallbladder, textural characteristics preset value and/or predeterminable area label.
In a first aspect, obtaining rgb value and the comparison progress abnormal color detection of RGB preset value of the present image.
Specifically, RGB preset value is divided into tri- preset values of R, G, B, the present image of the pot gallbladder is divided into R, G, B tri-
A Color Channel component, three Color Channel components compare with corresponding preset value respectively and combine judgement.
In the present embodiment, tri- preset values of R, G, B are set according to actual use situation, generally according to applying in pot gallbladder
Layer color setting, by setting different threshold values to three Color Channel components, and combine sentencing to the component in three channels
Certainly, the region in image with the presence or absence of abnormal nigrescence or jaundice can be detected.
Second aspect, the texture eigenvalue and the comparison of textural characteristics preset value for obtaining the present image carry out abnormal texture
Detection.
It specifically includes: the present image of the pot gallbladder is subjected to gridding processing；By the textural characteristics of the image in grid
Value and the textural characteristics preset value of the normal pot gallbladder compare.
Handled by gridding and in present image take the rectangle calculation window of suitable size, then from left to right, on to
Lower progress spacescan simultaneously calculates the texture eigenvalue in this window ranges, is matched with the template of normal the bottom of a pan surface texture
Detection, can in detection image with the presence or absence of regional area be burned and/or coating sintering.
The third aspect, the zone marker and predeterminable area label comparison for obtaining the present image carry out abnormal area inspection
It surveys.
Specifically, the present image is carried out binary conversion treatment and marks off target area to be compared, by target area
Morphologic corrosion treatment is done in domain, and the region of the zone marker of the target area after corrosion treatment and the normal pot gallbladder is marked
Note compares.
In the present embodiment, corresponding zone marker is made according to the case where normal pot gallbladder.Based on to normal the bottom of a pan surface
Priori knowledge, first to present image carry out binary conversion treatment, mark off multiple target areas to be compared；Then to two-value
Image after change does morphologic corrosion treatment, to eliminate small and meaningless boundary point and noise；Finally to marking off
Whether each target area is marked and compares with the zone marker of the normal pot gallbladder, can deposit in detection image
In the coating stripping and vegetable residue of large area.
Further, marking off target area to be compared includes:
The area threshold that the target area is determined according to preset detection sensitivity is marked off according to the area threshold
Target area to be compared.
S24, if detecting any abnormal conditions, being judged as in insanitariness and alarming.
For abnormal color detect, if three channels of the present image of pot gallbladder component joint judging result and it is described just
The image of normal pot gallbladder is inconsistent, then is judged as abnormal color.Conversely, being then judged as normal color.
For abnormal skin texture detection, if the textural characteristics of texture characteristic amount and the normal pot gallbladder in grid preset value difference
It is different to be greater than default difference value, then it is judged as abnormal texture.Conversely, being then judged as normal texture.
In the present embodiment, default difference value can be set according to specific actual use situation.
Abnormal area is detected, if the zone marker of target area and the zone marker of normal pot gallbladder are inconsistent, is sentenced
Break as abnormal area.Conversely, being then judged as normal region.
The present embodiment is detected by carrying out abnormal color detection, abnormal skin texture detection and/or abnormal area to present image,
Easily automatic detection is provided, the safety and health of dining room vegetable service has been ensured, has substantially reduced since safety and sanitation missing inspection is drawn
The operations risks of hair accident and dispute.
Embodiment three
The present embodiment provides a kind of for automating the hygienic state detection system of frying pan pot gallbladder, for executing above-mentioned implementation
For automating the hygienic state detection method of frying pan pot gallbladder described in example, has corresponding functional module, solve identical skill
Art problem reaches identical technical effect.The detection system includes:
Image collection module can be selected industry camera etc. and be suitable for frying pan work for obtaining the present image of pot gallbladder
The equipment of environment, aside, the stretching when needing to carry out hygienic state detection to frying pan reaches on pot gallbladder for storage when frying pan works
Shooting obtains the present image of pot gallbladder behind side.
Image judgment module receives the present image of the pot gallbladder of image collection module shooting, is used for the present image
Abnormal conditions detection is carried out with the image comparison of normal pot gallbladder；If detecting any abnormal conditions, it is judged as in unhygienic
State is simultaneously alarmed.Wherein, abnormal conditions detection includes abnormal color detection, abnormal skin texture detection and/or abnormal area detection.
In the present embodiment, which further includes that feature obtains module.The feature obtains module for obtaining normal pot
RGB preset value, textural characteristics preset value and/or the predeterminable area label of the image of gallbladder, are also used for obtaining the present image of pot gallbladder
Rgb value, textural characteristics preset value and/or predeterminable area label.
The device further includes lighting module.The lighting module is used for light filling, can accelerate the shutter speed of shooting, reduce
Shooting image noise avoids shooting image color cast.
The present embodiment carries out abnormal conditions detection by the image comparison of present image and normal pot gallbladder to obtain hygienic feelings
Condition improves the degree of automation, and without manual inspection, reduces missing inspection and detection does not find the problem and causes safety and sanitation thing
Therefore to it reduce operations risks.It can be used for intelligent robot dining room, the central kitchen of industrialized production pantry, large enterprise
Practicability is improved in employee dining room.
The technical principle of the invention is described above in combination with a specific embodiment.These descriptions are intended merely to explain of the invention
Principle, and shall not be construed in any way as a limitation of the scope of protection of the invention.Based on the explanation herein, the technology of this field
Personnel can associate with other specific embodiments of the invention without creative labor, these modes are fallen within
Within protection scope of the present invention.
Claims (10)
1. a kind of for automating the hygienic state detection method of frying pan pot gallbladder characterized by comprising
Obtain the present image of pot gallbladder；
The image comparison of the present image and normal pot gallbladder is subjected to abnormal conditions detection；
If detecting any abnormal conditions, being judged as in insanitariness and alarming；
Wherein, abnormal conditions detection includes abnormal color detection, abnormal skin texture detection and/or abnormal area detection.
2. according to claim 1 for automating the hygienic state detection method of frying pan pot gallbladder, which is characterized in that will be described
The image comparison of present image and normal pot gallbladder carries out abnormal conditions detection
Obtain RGB preset value, textural characteristics preset value and/or the predeterminable area label of the image of normal pot gallbladder；
The rgb value and the comparison of RGB preset value for obtaining the present image carry out abnormal color detection；
The texture eigenvalue and the comparison of textural characteristics preset value for obtaining the present image carry out abnormal skin texture detection；
The zone marker and predeterminable area label comparison for obtaining the present image carry out abnormal area detection.
3. according to claim 2 for automating the hygienic state detection method of frying pan pot gallbladder, which is characterized in that obtain institute
The rgb value and RGB preset value for stating present image compare progress abnormal color detection
RGB preset value is divided into tri- preset values of R, G, B；
The present image of the pot gallbladder is divided into tri- Color Channel components of R, G, B；
Three Color Channel components compare with corresponding preset value respectively and combine judgement；
It is corresponding, detect that any abnormal conditions include:
If joint judging result and the image of the normal pot gallbladder are inconsistent, it is judged as abnormal color；
Conversely, being then judged as normal color.
4. according to claim 2 for automating the hygienic state detection method of frying pan pot gallbladder, which is characterized in that obtain institute
The texture eigenvalue and textural characteristics preset value for stating present image compare the abnormal skin texture detection of progress
The present image of the pot gallbladder is subjected to gridding processing；
The texture eigenvalue of image in grid and the textural characteristics preset value of the normal pot gallbladder are compared；
It is corresponding, detect that any abnormal conditions include:
If the textural characteristics preset value difference of texture characteristic amount and the normal pot gallbladder in grid is greater than default difference value, sentence
Break as abnormal texture；
Conversely, being then judged as normal texture.
5. according to claim 2 for automating the hygienic state detection method of frying pan pot gallbladder, which is characterized in that obtain institute
The zone marker and predeterminable area for stating present image mark comparison progress abnormal area to detect
The present image is subjected to binary conversion treatment and marks off target area to be compared；
The zone marker of target area and the zone marker of the normal pot gallbladder are compared；
It is corresponding, detect that any abnormal conditions include:
If the zone marker of target area and the zone marker of normal pot gallbladder are inconsistent, it is judged as abnormal area；
Conversely, being then judged as normal region.
6. according to claim 5 for automating the hygienic state detection method of frying pan pot gallbladder, which is characterized in that mark off
Target area to be compared includes:
The area threshold of the target area is determined according to preset detection sensitivity；
Target area to be compared is marked off according to the area threshold.
7. according to claim 1 for automating the hygienic state detection method of frying pan pot gallbladder, which is characterized in that will be described
The image comparison of present image and normal pot gallbladder carries out before abnormal conditions detection further include:
White balance processing is carried out to the present image of the pot gallbladder.
8. a kind of for automating the hygienic state detection system of frying pan pot gallbladder characterized by comprising
Image collection module, for obtaining the present image of pot gallbladder；
Image judgment module, for the image comparison of the present image and normal pot gallbladder to be carried out abnormal conditions detection；
If detecting any abnormal conditions, being judged as in insanitariness and alarming；
Wherein, abnormal conditions detection includes abnormal color detection, abnormal skin texture detection and/or abnormal area detection.
9. according to any one of claims 8 for automating the hygienic state detection system of frying pan pot gallbladder, it is characterised in that: further include spy
Sign obtains module,
The feature obtains module, the RGB preset value of the image for obtaining normal pot gallbladder, textural characteristics preset value and/or pre-
If zone marker.
10. according to any one of claims 8 for automating the hygienic state detection system of frying pan pot gallbladder, which is characterized in that further include
Lighting module；
The lighting module is used for light filling.
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