CN113808115A - Big data storage type factory inspection platform - Google Patents
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- CN113808115A CN113808115A CN202111119657.6A CN202111119657A CN113808115A CN 113808115 A CN113808115 A CN 113808115A CN 202111119657 A CN202111119657 A CN 202111119657A CN 113808115 A CN113808115 A CN 113808115A
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- 238000007689 inspection Methods 0.000 title claims abstract description 46
- 238000013500 data storage Methods 0.000 title claims abstract description 37
- 239000000463 material Substances 0.000 claims abstract description 24
- 235000015203 fruit juice Nutrition 0.000 claims abstract description 23
- 230000007246 mechanism Effects 0.000 claims abstract description 21
- 230000009466 transformation Effects 0.000 claims description 40
- 238000006243 chemical reaction Methods 0.000 claims description 24
- 238000001514 detection method Methods 0.000 claims description 11
- 238000004458 analytical method Methods 0.000 claims description 8
- 238000001914 filtration Methods 0.000 claims description 3
- 238000005211 surface analysis Methods 0.000 claims description 3
- 235000011389 fruit/vegetable juice Nutrition 0.000 abstract description 13
- 238000005516 engineering process Methods 0.000 description 7
- 238000000034 method Methods 0.000 description 4
- 235000013399 edible fruits Nutrition 0.000 description 3
- CURLTUGMZLYLDI-UHFFFAOYSA-N Carbon dioxide Chemical compound O=C=O CURLTUGMZLYLDI-UHFFFAOYSA-N 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000021332 multicellular organism growth Effects 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 2
- 206010003210 Arteriosclerosis Diseases 0.000 description 1
- 208000024172 Cardiovascular disease Diseases 0.000 description 1
- 208000002699 Digestive System Neoplasms Diseases 0.000 description 1
- 208000031226 Hyperlipidaemia Diseases 0.000 description 1
- 230000032683 aging Effects 0.000 description 1
- 208000011775 arteriosclerosis disease Diseases 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
- 229910002092 carbon dioxide Inorganic materials 0.000 description 1
- 239000001569 carbon dioxide Substances 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000001816 cooling Methods 0.000 description 1
- 208000029078 coronary artery disease Diseases 0.000 description 1
- 238000007418 data mining Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 230000035622 drinking Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000002708 enhancing effect Effects 0.000 description 1
- 238000001704 evaporation Methods 0.000 description 1
- 230000008020 evaporation Effects 0.000 description 1
- 235000021022 fresh fruits Nutrition 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 230000036039 immunity Effects 0.000 description 1
- 210000000936 intestine Anatomy 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 235000015097 nutrients Nutrition 0.000 description 1
- 235000016709 nutrition Nutrition 0.000 description 1
- 230000035764 nutrition Effects 0.000 description 1
- 239000000047 product Substances 0.000 description 1
- 210000002345 respiratory system Anatomy 0.000 description 1
- 210000002784 stomach Anatomy 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 239000013589 supplement Substances 0.000 description 1
- 230000002485 urinary effect Effects 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Images
Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
- G06T7/0006—Industrial image inspection using a design-rule based approach
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
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- G06T5/80—
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/90—Determination of colour characteristics
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
- G06T2207/30128—Food products
Abstract
The invention relates to a big data storage type factory inspection platform, which comprises: the delivery inspection mechanism is used for executing image signal acquisition operation on the transparent bottle body to be delivered; the color storage mechanism is used for storing a color numerical value interval of the injected juice material of the transparent bottle body to be delivered from the factory; and the deviation distinguishing device is used for accumulating the total number of the color positive pixel points in the target identification area to be used as the color positive identification total number, and sending a color deviation signal when the proportion of the color positive identification total number occupying the total number of all the pixel points in the target identification area does not exceed a set proportion threshold value. The big data storage type delivery inspection platform provided by the invention is intelligent in operation and stable in operation, and can complete color distortion identification of the fruit juice material injected into the transparent bottle body to be delivered on the basis of introducing a big data storage mechanism for storing the color numerical value interval of the fruit juice material injected into the transparent bottle body to be delivered.
Description
Technical Field
The invention relates to the field of big data application, in particular to a big data storage type factory inspection platform.
Background
Big data can not be processed by cloud, and the cloud processing provides elastically expandable basic equipment for the big data, and is one of platforms for generating the big data. Since 2013, big data technology is closely combined with cloud computing technology, and the relation between the big data technology and the cloud computing technology is expected to be closer in the future. In addition, emerging computing forms such as the Internet of things and the mobile internet can also help big data revolution together, so that big data marketing can exert greater influence.
With the rapid development of big data, just like computers and the internet, big data is likely to be a new revolution of technology. The related technologies such as data mining, machine learning, artificial intelligence and the like which are developed along with the method can change a plurality of algorithms and basic theories in the data world, and realize breakthrough in science and technology. In the prior art, in the operation process of injecting juice into the transparent bottle body, the overall color of the juice material in different transparent bottle bodies is different due to different juice producing areas, differences in individual fruit body growth and differences in processing links, and the deviation between the overall color of the juice material in various transparent bottle bodies and the set color of the juice is allowable in a certain range.
Disclosure of Invention
In order to solve the technical problems in the prior art, the invention provides a big data storage type factory inspection platform which can visually identify the whole color of the fruit juice material in different transparent bottle bodies on the basis of introducing a color storage mechanism for storing the color numerical value interval of the fruit juice material injected into the transparent bottle body to be factory, so that the effectiveness of fruit juice material identification is improved.
For this reason, the present invention needs to have at least the following important points:
(1) the intelligent color determination method comprises the following steps of adopting a first conversion part, a second conversion part, a third conversion part, a side analysis device, a region processing device and a color detection device, and analyzing the number of color distortion pixel points in an identified bottle body imaging region, so as to finish the intelligent determination of the whole color of the fruit juice material injected into the transparent bottle body to be delivered from a factory;
(2) the introduced color storage mechanism is used for storing a color numerical value interval of the fruit juice material injected into the transparent bottle body to be delivered from the factory, and the color numerical value interval consists of a red brightness numerical value interval, a green brightness numerical value interval and a blue brightness numerical value interval and is used for providing a judgment basis for the color distortion of the fruit juice material injected into the transparent bottle body to be delivered from the factory.
According to an aspect of the present invention, there is provided a big data storage factory inspection platform, comprising:
and the first transformation component is used for executing point image restoration processing on the received factory collected picture so as to obtain a corresponding first transformation picture.
More specifically, in the big data storage factory inspection platform, the platform further comprises:
and the second transformation component is connected with the first transformation component and is used for executing high-speed white noise filtering processing on the received first transformation picture so as to obtain a corresponding second transformation picture.
More specifically, in the big data storage factory inspection platform, the platform further comprises:
third transformation means, connected to the second transformation means, for performing distortion calibration processing on the received second transformed picture to obtain a corresponding distortion calibration picture;
the side surface analysis equipment is connected with the third transformation part and used for searching each image area with the similarity exceeding the geometric shape of the side surface of the transparent bottle body to be delivered from the factory in the third transformation part to serve as each area to be referred to for output;
the area processing equipment is connected with the side analysis equipment and is used for outputting the area to be referenced with the shallowest depth-of-field data in each area to be referenced as a target identification area;
the color detection device is connected with the region processing device and is used for acquiring a red brightness value, a green brightness value and a blue brightness value of each pixel point in the target identification region in an RGB color space;
the content judgment device is respectively connected with the color detection equipment and the color storage mechanism and is used for taking pixel points of which the red brightness value is in a red brightness value interval, the green brightness value is in a green brightness value interval and the blue brightness value is in a blue brightness value interval in the target identification area as color positive pixel points;
the deviation distinguishing device is connected with the content judging device and used for accumulating the total number of the color positive pixel points in the target identification area to be used as the color positive identification total number and sending a color deviation signal when the proportion of the color positive identification total number occupying the total number of all the pixel points in the target identification area does not exceed a set proportion threshold;
the delivery inspection mechanism is arranged on the side surface of the transparent bottle body to be delivered, is connected with the first conversion component, and is used for executing image signal acquisition operation on the transparent bottle body to be delivered so as to obtain a corresponding delivery acquisition picture;
the color storage mechanism is arranged at the far end of the factory inspection mechanism and is used for storing a color numerical value interval of the injected fruit juice material of the transparent bottle body to be factory;
wherein, the colour numerical value interval of the fruit juice material that the transparent bottle that the storage was about to leave the factory was injected includes: the color numerical value interval consists of a red brightness numerical value interval, a green brightness numerical value interval and a blue brightness numerical value interval;
the deviation distinguishing equipment is also used for sending a color reliable signal when the proportion of the total number of all pixel points of the target identification area occupied by the total number of the color positive identification exceeds the set proportion threshold;
wherein, the color value interval comprises a red brightness value interval, a green brightness value interval and a blue brightness value interval: the red brightness corresponds to an R channel value under an RGB color space, the green brightness corresponds to a G channel value under the RGB color space, and the blue brightness corresponds to a B channel value under the RGB color space, and meanwhile, the values of a red brightness value interval, a green brightness value interval and a blue brightness value interval are all between 0 and 255;
wherein, in the factory inspection mechanism, a set volume of fruit juice material is injected into the transparent bottle to be factory.
The big data storage type factory inspection platform is intelligent in operation and stable in operation. Because can be used for saving the whole colour of the fruit juice material of being poured into of the transparent bottle that waits to leave the factory on the basis of introducing the colour numerical value interval of colour storage mechanism, carry out visual identification to the whole colour of fruit juice material of different transparent bottles to avoid the excessive fruit juice product of colour difference to flow into market.
Drawings
Embodiments of the invention will now be described with reference to the accompanying drawings, in which:
fig. 1 is a diagram illustrating an example of a transparent bottle applied to a big data storage factory inspection platform according to an embodiment of the present invention.
Detailed Description
Embodiments of the big data storage factory inspection platform according to the present invention will be described in detail with reference to the accompanying drawings.
The fruit juice contains much water and sugar, and can rapidly supplement water and energy consumed by human body due to exercise after drinking. A small amount of carbon dioxide in the fruit juice can take away part of heat in the body through evaporation after entering intestines and stomach, and plays a role in relieving summer heat and cooling.
The fruit juice contains many natural nutrients, and has effects of enhancing immunity, reducing illness, delaying aging, etc. Especially fresh fruit juice has most of the nutrition and corresponding efficacy of the fruit. If the fresh juice is drunk frequently, the risk of cancer of the digestive system, the urinary system and the respiratory tract can be greatly reduced, and cardiovascular diseases such as arteriosclerosis, hyperlipidemia, coronary heart disease and the like can be effectively prevented. In the prior art, in the operation process of injecting juice into the transparent bottle body, the overall color of the juice material in different transparent bottle bodies is different due to different juice producing areas, differences in individual fruit body growth and differences in processing links, and the deviation between the overall color of the juice material in various transparent bottle bodies and the set color of the juice is allowable in a certain range.
In order to overcome the defects, the invention builds a big data storage type factory inspection platform, and can effectively solve the corresponding technical problems.
Fig. 1 is a diagram illustrating an example of a transparent bottle applied to a big data storage factory inspection platform according to an embodiment of the present invention.
The big data storage type factory inspection platform shown according to the embodiment of the invention comprises:
and the first transformation component is used for executing point image restoration processing on the received factory collected picture so as to obtain a corresponding first transformation picture.
Next, the detailed structure of the big data storage factory inspection platform according to the present invention will be described further.
The big data storage type factory inspection platform further comprises:
and the second transformation component is connected with the first transformation component and is used for executing high-speed white noise filtering processing on the received first transformation picture so as to obtain a corresponding second transformation picture.
The big data storage type factory inspection platform further comprises:
third transformation means, connected to the second transformation means, for performing distortion calibration processing on the received second transformed picture to obtain a corresponding distortion calibration picture;
the side surface analysis equipment is connected with the third transformation part and used for searching each image area with the similarity exceeding the geometric shape of the side surface of the transparent bottle body to be delivered from the factory in the third transformation part to serve as each area to be referred to for output;
the area processing equipment is connected with the side analysis equipment and is used for outputting the area to be referenced with the shallowest depth-of-field data in each area to be referenced as a target identification area;
the color detection device is connected with the region processing device and is used for acquiring a red brightness value, a green brightness value and a blue brightness value of each pixel point in the target identification region in an RGB color space;
the content judgment device is respectively connected with the color detection equipment and the color storage mechanism and is used for taking pixel points of which the red brightness value is in a red brightness value interval, the green brightness value is in a green brightness value interval and the blue brightness value is in a blue brightness value interval in the target identification area as color positive pixel points;
the deviation distinguishing device is connected with the content judging device and used for accumulating the total number of the color positive pixel points in the target identification area to be used as the color positive identification total number and sending a color deviation signal when the proportion of the color positive identification total number occupying the total number of all the pixel points in the target identification area does not exceed a set proportion threshold;
the delivery inspection mechanism is arranged on the side surface of the transparent bottle body to be delivered, is connected with the first conversion component, and is used for executing image signal acquisition operation on the transparent bottle body to be delivered so as to obtain a corresponding delivery acquisition picture;
the color storage mechanism is arranged at the far end of the factory inspection mechanism and is used for storing a color numerical value interval of the injected fruit juice material of the transparent bottle body to be factory;
wherein, the colour numerical value interval of the fruit juice material that the transparent bottle that the storage was about to leave the factory was injected includes: the color numerical value interval consists of a red brightness numerical value interval, a green brightness numerical value interval and a blue brightness numerical value interval;
the deviation distinguishing equipment is also used for sending a color reliable signal when the proportion of the total number of all pixel points of the target identification area occupied by the total number of the color positive identification exceeds the set proportion threshold;
wherein, the color value interval comprises a red brightness value interval, a green brightness value interval and a blue brightness value interval: the red brightness corresponds to an R channel value under an RGB color space, the green brightness corresponds to a G channel value under the RGB color space, and the blue brightness corresponds to a B channel value under the RGB color space, and meanwhile, the values of a red brightness value interval, a green brightness value interval and a blue brightness value interval are all between 0 and 255;
wherein, in the factory inspection mechanism, a set volume of fruit juice material is injected into the transparent bottle to be factory.
The big data storage type factory inspection platform further comprises:
the parallel configuration interface is respectively connected with the first conversion component, the second conversion component, the third conversion component, the side analysis equipment, the area processing equipment and the color detection equipment;
the parallel configuration interface is used for providing configuration parameters required by respective work for the first transformation component, the second transformation component, the third transformation component, the side analysis device, the area processing device and the color detection device.
In the big data storage type factory inspection platform:
the first conversion member has a built-in storage unit for storing input data and output data of the first conversion member.
In the big data storage type factory inspection platform:
the second conversion component is connected with the IIC control bus and used for receiving various control instructions sent by the IIC control bus.
In the big data storage type factory inspection platform:
the first conversion component is further connected with a clock generator for receiving a timing signal customized by the clock generator for the device a.
In the big data storage type factory inspection platform:
the second transformation component is implemented using an ASIC chip that includes an online programming interface.
In the big data storage type factory inspection platform:
the first conversion part and the second conversion part are located on the same printed circuit board and share the same circuit supply device.
In the big data storage type factory inspection platform:
the second transformation component is further connected to a parallel data bus for receiving data from the parallel data bus and sending data to the parallel data bus.
In addition, in the big data storage type factory inspection platform, the content judgment device is further configured to use a pixel point, in which a red brightness value in the target identification area is outside a red brightness value range, as a color cast pixel point; the content judgment device is also used for taking pixel points with green brightness values outside the green brightness value interval in the target identification area as color cast pixel points; and the content judgment device is also used for taking the pixel points of which the blue brightness values in the target identification area are outside the blue brightness value range as color cast pixel points.
Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art will appreciate that various modifications and substitutions can be made thereto without departing from the spirit and scope of the present invention as set forth in the appended claims.
Claims (10)
1. A big data storage factory inspection platform, the platform comprising:
and the first transformation component is used for executing point image restoration processing on the received factory collected picture so as to obtain a corresponding first transformation picture.
2. The big data storage factory inspection platform of claim 1, wherein the platform further comprises:
and the second transformation component is connected with the first transformation component and is used for executing high-speed white noise filtering processing on the received first transformation picture so as to obtain a corresponding second transformation picture.
3. The big data storage factory inspection platform of claim 2, wherein said platform further comprises:
third transformation means, connected to the second transformation means, for performing distortion calibration processing on the received second transformed picture to obtain a corresponding distortion calibration picture;
the side surface analysis equipment is connected with the third transformation part and used for searching each image area with the similarity exceeding the geometric shape of the side surface of the transparent bottle body to be delivered from the factory in the third transformation part to serve as each area to be referred to for output;
the area processing equipment is connected with the side analysis equipment and is used for outputting the area to be referenced with the shallowest depth-of-field data in each area to be referenced as a target identification area;
the color detection device is connected with the region processing device and is used for acquiring a red brightness value, a green brightness value and a blue brightness value of each pixel point in the target identification region in an RGB color space;
the content judgment device is respectively connected with the color detection equipment and the color storage mechanism and is used for taking pixel points of which the red brightness value is in a red brightness value interval, the green brightness value is in a green brightness value interval and the blue brightness value is in a blue brightness value interval in the target identification area as color positive pixel points;
the deviation distinguishing device is connected with the content judging device and used for accumulating the total number of the color positive pixel points in the target identification area to be used as the color positive identification total number and sending a color deviation signal when the proportion of the color positive identification total number occupying the total number of all the pixel points in the target identification area does not exceed a set proportion threshold;
the delivery inspection mechanism is arranged on the side surface of the transparent bottle body to be delivered, is connected with the first conversion component, and is used for executing image signal acquisition operation on the transparent bottle body to be delivered so as to obtain a corresponding delivery acquisition picture;
the color storage mechanism is arranged at the far end of the factory inspection mechanism and is used for storing a color numerical value interval of the injected fruit juice material of the transparent bottle body to be factory;
wherein, the colour numerical value interval of the fruit juice material that the transparent bottle that the storage was about to leave the factory was injected includes: the color numerical value interval consists of a red brightness numerical value interval, a green brightness numerical value interval and a blue brightness numerical value interval;
the deviation distinguishing equipment is also used for sending a color reliable signal when the proportion of the total number of all pixel points of the target identification area occupied by the total number of the color positive identification exceeds the set proportion threshold;
wherein, the color value interval comprises a red brightness value interval, a green brightness value interval and a blue brightness value interval: the red brightness corresponds to an R channel value under an RGB color space, the green brightness corresponds to a G channel value under the RGB color space, and the blue brightness corresponds to a B channel value under the RGB color space, and meanwhile, the values of a red brightness value interval, a green brightness value interval and a blue brightness value interval are all between 0 and 255;
wherein, in the factory inspection mechanism, a set volume of fruit juice material is injected into the transparent bottle to be factory.
4. The big data storage factory inspection platform of claim 3, wherein said platform further comprises:
the parallel configuration interface is respectively connected with the first conversion component, the second conversion component, the third conversion component, the side analysis equipment, the area processing equipment and the color detection equipment;
the parallel configuration interface is used for providing configuration parameters required by respective work for the first transformation component, the second transformation component, the third transformation component, the side analysis device, the area processing device and the color detection device.
5. The big data storage factory inspection platform of claim 3, wherein:
the first conversion member has a built-in storage unit for storing input data and output data of the first conversion member.
6. The big data storage factory inspection platform of claim 3, wherein:
the second conversion component is connected with the IIC control bus and used for receiving various control instructions sent by the IIC control bus.
7. The big data storage factory inspection platform of claim 3, wherein:
the first conversion component is further connected with a clock generator for receiving a timing signal customized by the clock generator for the device a.
8. The big data storage factory inspection platform of claim 3, wherein:
the second transformation component is implemented using an ASIC chip that includes an online programming interface.
9. The big data storage factory inspection platform of claim 3, wherein:
the first conversion part and the second conversion part are located on the same printed circuit board and share the same circuit supply device.
10. The big data storage factory inspection platform of claim 3, wherein:
the second transformation component is further connected to a parallel data bus for receiving data from the parallel data bus and sending data to the parallel data bus.
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Application publication date: 20211217 |