CN108663105A - A kind of weighing device and corresponding weighing method - Google Patents
A kind of weighing device and corresponding weighing method Download PDFInfo
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- CN108663105A CN108663105A CN201810392628.9A CN201810392628A CN108663105A CN 108663105 A CN108663105 A CN 108663105A CN 201810392628 A CN201810392628 A CN 201810392628A CN 108663105 A CN108663105 A CN 108663105A
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- 238000005303 weighing Methods 0.000 title claims abstract description 81
- 238000000034 method Methods 0.000 title claims abstract description 24
- 238000003909 pattern recognition Methods 0.000 claims abstract description 16
- 230000001960 triggered effect Effects 0.000 claims abstract description 3
- 238000012545 processing Methods 0.000 claims description 38
- NJPPVKZQTLUDBO-UHFFFAOYSA-N novaluron Chemical compound C1=C(Cl)C(OC(F)(F)C(OC(F)(F)F)F)=CC=C1NC(=O)NC(=O)C1=C(F)C=CC=C1F NJPPVKZQTLUDBO-UHFFFAOYSA-N 0.000 claims description 21
- 238000007781 pre-processing Methods 0.000 claims description 18
- 238000012549 training Methods 0.000 claims description 15
- 241001269238 Data Species 0.000 claims description 11
- 230000000694 effects Effects 0.000 abstract description 3
- 238000005516 engineering process Methods 0.000 abstract description 3
- 241000234295 Musa Species 0.000 description 5
- 235000018290 Musa x paradisiaca Nutrition 0.000 description 5
- 230000004438 eyesight Effects 0.000 description 5
- 235000013399 edible fruits Nutrition 0.000 description 4
- 238000004891 communication Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 238000007639 printing Methods 0.000 description 3
- 238000012937 correction Methods 0.000 description 2
- 235000013372 meat Nutrition 0.000 description 2
- 238000004806 packaging method and process Methods 0.000 description 2
- 241000196324 Embryophyta Species 0.000 description 1
- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 description 1
- 239000003242 anti bacterial agent Substances 0.000 description 1
- 229940088710 antibiotic agent Drugs 0.000 description 1
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- 235000013311 vegetables Nutrition 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01G—WEIGHING
- G01G19/00—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups
- G01G19/40—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups with provisions for indicating, recording, or computing price or other quantities dependent on the weight
- G01G19/413—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups with provisions for indicating, recording, or computing price or other quantities dependent on the weight using electromechanical or electronic computing means
- G01G19/414—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups with provisions for indicating, recording, or computing price or other quantities dependent on the weight using electromechanical or electronic computing means using electronic computing means only
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Abstract
The invention discloses a kind of weighing device and corresponding weighing method, this method is applied to a kind of weighing device, the method includes：Obtain the weight data of article on weighing device；Pattern recognition device action is triggered according to the weight data, obtains the image data of article on weighing device；It receives described image data and is handled to obtain recognition result；The recognition result is shown by display device；Its effect is：While weighing automatically of article is being realized, relevant staff is being not necessarily to, remembers the coding and input coding of all categories, corresponding article is identified by image recognition technology, to reduce the workload of staff, improves efficiency of weighing.
Description
Technical field
The invention belongs to electronic scale technical fields, and in particular to arrive a kind of weighing device and corresponding weighing method.
Background technology
Existing electronic price computing scale mostly uses greatly artificial value from the degree of automation and keeps formula, artificial balance structure on duty
Include mainly pressure sensor, small liquid crystal display and push type numeric keypad.Mode of operation is artificial (such as supermarket person
Work) commodity that customer takes are placed on weighing platform, commodity digital coding is pressed out on numeric keypad, waits for weight to stablize aobvious
Show, clicks printing commodity marked price.
It is long-term on duty by scale that the balance of artificial formula on duty needs to arrange for specific people, because he needs to remember all product
The coding and input coding of class, working efficiency is low, labor intensity is big, and supermarket employment and management cost it is all very high.
Invention content
To solve the above-mentioned problems, the object of the present invention is to provide a kind of weighing device and corresponding weighing method, have
Work efficiency is high, reduces the effect of relevant staff's labor intensity.
A kind of technical solution that the present invention takes is：A kind of weighing device, including pedestal, and the branch that is connect with pedestal
The top of frame, the holder is equipped with display device, and pattern recognition device is additionally provided on the holder, described image identification device
Working face towards the pedestal weighing table, the display device and pattern recognition device respectively with the control in the pedestal
Making sheet connects, and the control panel includes Weighing module and control module；
The Weighing module is used to obtain the weight data of article on weighing device；
Described image identification device is used to trigger pattern recognition device action according to the weight data, obtains weighing device
The image data of upper article；
The control module is for receiving described image data and being handled to obtain recognition result；
The display device is for showing the recognition result.
Preferably, the control module include preprocessing module, the first image processing module, the second image processing module,
Identification module and arrangement module；
The preprocessing module is used to described image data carrying out sectional drawing processing, to obtain preprocessing image data；
Described first image processing module is used to the preprocessing image data carrying out histogram equalization processing, with
To first object image data；
Second image processing module is used to the first object image data carrying out multi-angle rotary processing, with
To multiple second destination image datas；
The identification module is used to described image data and multiple second destination image datas being sent into preset trained mould
Type is handled, and to obtain multiple recognition results, each recognition result includes confidence of the article in each goods categories
Spend probability；By the confidence level probability by each article type carry out probability summation, obtain the article each article kind
The probability value of class；
The arrangement module is used to carry out descending arrangement to the type of goods identified according to the probability value, as described
Recognition result.
Preferably, a kind of weighing device, further includes secondary support, the secondary support include first connecting portion and with institute
The hinged second connecting portion of first connecting portion is stated, the first connecting portion is connect with the support vertical, the second connecting portion
Top be equipped with assisted image recognition device, and the working face of the auxiliary recognition device is towards the weighing table of the pedestal.
Preferably, the assisted image recognition device includes binocular camera and is arranged in the binocular camera one side
Flash lamp, the binocular camera and flash lamp are respectively connect with the control module.
The another technical solution that the present invention takes is：A kind of weighing method is applied to weighing device described above, institute
The method of stating includes：
Obtain the weight data of article on weighing device；
Pattern recognition device action is triggered according to the weight data, obtains the image data of article on weighing device；
It receives described image data and is handled to obtain recognition result；
The recognition result is shown by display device.
Preferably, the weighing method further includes：The input order of display device is obtained, and according to input order pair
The recognition result is directly chosen.
Preferably, described image data are received and are handled to obtain recognition result, following steps are specifically included：
Described image data are subjected to sectional drawing processing, to obtain preprocessing image data；
The preprocessing image data is subjected to histogram equalization processing, to obtain first object image data；
The first object image data is subjected to multi-angle rotary processing, to obtain multiple second destination image datas；
Described image data and multiple second destination image datas are sent into preset training pattern to handle, to obtain
Multiple recognition results, each recognition result include confidence level probability of the article in each goods categories；
By the confidence level probability by each article type carry out probability summation, obtain the article each article kind
The probability value of class；
Descending arrangement is carried out to the type of goods identified according to the probability value, as the recognition result.
Preferably, the multi-angle rotary includes 90 °, 180 ° and 270 ° rotations.
Preferably, the training pattern uses MobileNet vision identification processing models.
Using above-mentioned technical proposal, has the following advantages：A kind of weighing device proposed by the present invention and the accordingly side of weighing
Method is realizing while weighing automatically of article, is being not necessarily to relevant staff, remembers the coding of all categories, pass through image
Identification technology identifies corresponding article, to reduce the workload of staff, improves efficiency of weighing.
Description of the drawings
Fig. 1 is a kind of external structure schematic diagram of weighing device of the embodiment of the present invention；
Fig. 2 is a kind of schematic block circuit diagram of weighing device of the embodiment of the present invention；
Fig. 3 is a kind of method flow diagram of weighing method of the embodiment of the present invention.
Specific implementation mode
To keep the technical problem to be solved in the present invention, technical solution and advantage clearer, below in conjunction with attached drawing and tool
Body embodiment is described in detail, and description here does not mean that all themes corresponding to the specific example stated in embodiment
All refer in the claims.
With reference to shown in figure 1, Fig. 2, a kind of weighing device, including pedestal 1, and the holder 2 that is connect with pedestal 1, the branch
The top of frame 2 is equipped with display device 21, and pattern recognition device 22 is additionally provided on the holder 2, described image identification device 22
Working face towards the pedestal 1 weighing table, the display device 21 and pattern recognition device 22 respectively with the pedestal
Interior control panel 11 connects, and the control panel 11 includes Weighing module 112 and control module 114；
The Weighing module 112 is used to obtain the weight data of article on weighing device；
Described image identification device 22 is used to trigger pattern recognition device action according to the weight data, obtains dress of weighing
Set the image data of article；
The control module 114 is for receiving described image data and being handled to obtain recognition result；
The display device 21 is for showing the recognition result.
In the present embodiment, Weighing module 112 includes multiple pressure sensors, and is arranged in pedestal, and article refers to vegetable
Dish, fruit, meat, aquatic product or daily necessities etc., are not intended to limit herein, and the display device 21 is touched using coloured plate
Screen, described image identification device 22 use camera or camera；Power module 111, power module can be also set in pedestal
111 can be used rechargeable lithium battery, for being each module and power supply for electrical equipment, communication module 113, the use of communication module 113
Wireless communication module, for example, Zigbee module, WIFI blocks etc., by using the weighing device, under stable state of weighing, profit
The image of article is acquired with pattern recognition device, control module is sent to and is handled, to identify corresponding article
Type, finally show the information such as picture, title, weight, unit price and the total price of dependent merchandise on the display apparatus.
Compared with prior art, this scheme need not occupy personnel time, and client self-service can operate, and client is not
Need the click entrance for oneself taking time to search metering commodity, relevant staff that need not more remember the coding of corresponding commodity, pole
Shops's efficiency of operation is improved greatly, reduces the employment cost of StoreFront, improves customer experience.
Further, the control module 114 includes preprocessing module, the first image processing module, the second image procossing
Module, identification module and arrangement module；
The preprocessing module is used to described image data carrying out sectional drawing processing, to obtain preprocessing image data；
Geometry sectional drawing is done along the weighing platform side of pedestal specifically, doing the image sent, to reduce the image outside weighing platform
To normally identifying caused interference.
Described first image processing module is used to the preprocessing image data carrying out histogram equalization processing, with
To first object image data；
Specifically, by carrying out histogram equalization processing, by the gray level more than number of pixels in image into line broadening, and
The gray scale few to number of pixels in image is compressed, and to extend the dynamic range of pixel value, improves contrast and ash
The variation for spending tone, makes image be more clear, to avoid the reflective or overexposure in part from being interfered to normally identifying.
Second image processing module is used to the first object image data carrying out multi-angle rotary processing, with
To multiple second destination image datas；
It is carried out at rotation with 90 °, 180 ° and 270 ° specifically, rotating respectively the image in first object image data
Reason, can also increase more rotation angles, often rotate an angle and obtain an image, that is to say, that the second target image
Data include at least three different images.
The identification module is used to described image data and multiple second destination image datas being sent into preset trained mould
Type is handled, and to obtain multiple recognition results, each recognition result includes confidence of the article in each goods categories
Spend probability；By the confidence level probability by each article type carry out probability summation, obtain the article each article kind
The probability value of class；
Specifically, the image after artwork (unpretreated image) and previous step multi-angle rotary is respectively fed to preset
Training pattern, at least obtain four recognition results, each recognition result include training pattern can identify in property
Category not in confidence level probability.The training pattern uses MobileNet vision identification processing models, MobileNet visions
The foundation of identifying processing model is intended to acquire a large amount of training data of each type of goods, and training data is needed comprising article
Various forms (multi-angle), quantity and density add bag and are not added with the parameters such as bag packaging.By taking four recognition results as an example, according to every
One kind extracts its confidence value from above four recognition results and sums.For example, identifying A classes, knot is identified at four
Value in fruit is a1, a2, a3 respectively, and a4, the last probability of A classes is a1+a2+a3+a4, B classes is identified, in four recognition results
In value be b1, b2, b3 respectively, b4, the last probability of B classes is b1+b2+b3+b4, other classifications, herein no longer
It repeats.
The arrangement module is used to carry out descending arrangement to the type of goods identified according to the probability value, as described
Recognition result.
Specifically, after each goods categories are summed, it is ranked up according to the size of each probability value, by the knot of sequence
Fruit returns to front end (namely display device).
Further, in order to have artificial error correction, ensure that the reliability used, user can trigger the defeated of display device
Enter order, and the recognition result is directly chosen according to input order, that is to say, that if the user find that highest
Probability recognition result mistake, guiding user enter the selection page according to probability sorting, are chosen correct article kind again
Class, it is contemplated that identification only carries out major class identification, such as " banana ", " apple " herein, does not indicate derivative class, such as " big fragrant
Any of several broadleaf plants ", " small banana ", so needing to show that derivative Class Options, user click specific derivative class, meeting on the interface of display device
Pop-up confirms the window of printing bar code, prints bar code, and system, which returns, waits for placement status.
Further, there is unclear, incomplete situation, and the image recognition on holder 2 to reduce image
When the trip failure of device 22, the normal work of the device is not still influenced, can be carried out at the same time Image Acquisition yet, and also allows for adjusting
The acquisition angles of whole assisted image recognition device, improve corresponding accuracy and reliability, and a kind of weighing device also wraps
Secondary support 23 is included, the secondary support 23 includes first connecting portion 231 and the second connecting portion hinged with the first connecting portion 231
232, the first connecting portion 231 and 2 vertical connection of the holder, the top of the second connecting portion 232 are equipped with assistant images
Identification device, and the working face of the auxiliary recognition device is towards the weighing table of the pedestal, in specific application, the pair
The quantity of holder can be added according to actual conditions.
Further, the assisted image recognition device includes binocular camera 2321 and is arranged in the binocular camera
The flash lamp 2322 of one side, the binocular camera 2321 and flash lamp 2322 are respectively connect with the control module, this
Sample further improves the quality of acquisition image, will not be because external environment Software quality is as recognition effect.
Refering to what is shown in Fig. 3, a kind of weighing method, is applied to weighing device described above, the method includes：
S101 obtains the weight data of article on weighing device；
Specifically, the Weighing module on weighing device executes this operation, and Weighing module includes multiple pressure sensors, and is set
It sets in pedestal, article refers to veterinary antibiotics, meat, aquatic product or daily necessities etc., is not intended to limit herein, and the number that will weigh
It is handled according to control module is sent to.
S102 triggers pattern recognition device action according to the weight data, obtains the picture number of article on weighing device
According to；
Specifically, under stable state of weighing, the image of article is acquired using pattern recognition device, and is sent to
Control module is handled.
S103 receives described image data and is handled to obtain recognition result；
Specifically, control module executes this operation, is handled after receiving image data, to identify corresponding article
Type, and recognition result is sent to the display device of front end.
S104 shows the recognition result by display device.
Specifically, it after display device receives the recognition result that control module is sent, is shown by visual mode
Show, including the information such as picture, chart and word.
Further, the weighing method further includes：The input order of display device is obtained, and is ordered according to the input
The recognition result is directly chosen.
Specifically, if the user find that maximum probability recognition result mistake, guiding user enter the choosing according to probability sorting
The page is selected, is chosen correct type of goods again, what needs to be explained here is that, identification herein only carries out major class identification,
Such as " banana ", " apple ", derivative class, such as " big banana ", " small banana " are not indicated, so being needed on the interface of display device
Show that derivative Class Options, user click specific derivative class, can pop up the window for confirming printing bar code, print bar code, system
It returns and waits for placement status；Using this method, artificial error correction is made it have, ensure that the reliability used.
Further, described image data are received and are handled to obtain recognition result, following steps are specifically included：
Described image data are subjected to sectional drawing processing, to obtain preprocessing image data；
Geometry sectional drawing is done along the weighing platform side of pedestal specifically, doing the image sent, to reduce the image outside weighing platform
To normally identifying caused interference.
The preprocessing image data is subjected to histogram equalization processing, to obtain first object image data；
Specifically, by carrying out histogram equalization processing, by the gray level more than number of pixels in image into line broadening, and
The gray scale few to number of pixels in image is compressed, and to extend the dynamic range of pixel value, improves contrast and ash
The variation for spending tone, makes image be more clear, to avoid the reflective or overexposure in part from being interfered to normally identifying.
The first object image data is subjected to multi-angle rotary processing, to obtain multiple second destination image datas；
It is carried out at rotation with 90 °, 180 ° and 270 ° specifically, rotating respectively the image in first object image data
Reason, can also increase more rotation angles, often rotate an angle and obtain an image, that is to say, that the second target image
Data include at least three different images.
Described image data and multiple second destination image datas are sent into preset training pattern to handle, to obtain
Multiple recognition results, each recognition result include confidence level probability of the article in each goods categories；
Image after artwork (unpretreated image) and previous step multi-angle rotary is respectively fed to preset trained mould
Type, at least obtains four recognition results, each recognition result include training pattern can identify in all items classification
Confidence level probability.The training pattern uses MobileNet vision identification processing models, MobileNet vision identification processings
The foundation of model is intended to acquire a large amount of training data of each type of goods, and training data needs to include the various forms of article
(multi-angle), quantity and density add bag and are not added with the parameters such as bag packaging.
By the confidence level probability by each article type carry out probability summation, obtain the article each article kind
The probability value of class；
Specifically, by taking four recognition results as an example, its confidence level is extracted from above four recognition results according to every one kind
Numerical value is summed.For example, identify A classes, the value in four recognition results is a1, a2, a3 respectively, a4, last general of A classes
Rate is a1+a2+a3+a4, identifies B classes, and the value in four recognition results is b1, b2, b3, b4, the last probability of B classes respectively
For b1+b2+b3+b4, other classifications and so on, details are not described herein.
Descending arrangement is carried out to the type of goods identified according to the probability value, as the recognition result.
Specifically, after each goods categories are summed, it is ranked up according to the size of each probability value, by the knot of sequence
Fruit returns to front end (namely display device).
The article of pedestal weighed on face is carried out Image Acquisition by the present invention by pattern recognition device and pressure sensor
And Weight acquisition, and handled by control module, obtain title, weight, unit price and the total price of current item, and pass through
The display device that network is sent to weighing device is shown, is realized the automatic of article and is weighed, this scheme need not occupy work
Make personnel time, client self-service can operate, and client does not need the click entrance for oneself taking time to search metering commodity, related
Staff need not more remember the coding of corresponding commodity, reduce the workload of staff, improve efficiency of weighing, reduce
The employment cost of StoreFront, improves customer experience.
Finally, it should be noted that foregoing description is the preferred embodiment of the present invention, those skilled in the art exist
Under the enlightenment of the present invention, without prejudice to the purpose of the present invention and the claims, expression as multiple types can be made, this
The transformation of sample is each fallen within protection scope of the present invention.
Claims (9)
1. a kind of weighing device, which is characterized in that including pedestal, and the holder that is connect with pedestal, set at the top of the holder
There is display device, be additionally provided with pattern recognition device on the holder, the working face of described image identification device is towards the pedestal
Weighing table, the display device and pattern recognition device respectively connect with the control panel in the pedestal, the control
Plate includes Weighing module and control module；
The Weighing module is used to obtain the weight data of article on weighing device；
Described image identification device is used to trigger pattern recognition device action according to the weight data, obtains object on weighing device
The image data of product；
The control module is for receiving described image data and being handled to obtain recognition result；
The display device is for showing the recognition result.
2. a kind of weighing device according to claim 1, which is characterized in that the control module include preprocessing module,
First image processing module, the second image processing module, identification module and arrangement module；
The preprocessing module is used to described image data carrying out sectional drawing processing, to obtain preprocessing image data；
Described first image processing module is used to the preprocessing image data carrying out histogram equalization processing, to obtain the
One destination image data；
Second image processing module is used to the first object image data carrying out multi-angle rotary processing, more to obtain
A second destination image data；
The identification module be used for by described image data and multiple second destination image datas be sent into preset training pattern into
Row processing, to obtain multiple recognition results, each recognition result includes that confidence level of the article in each goods categories is general
Rate；The confidence level probability is subjected to probability summation by the type of each article, obtain the article each article type
Probability value；
The arrangement module is used to carry out descending arrangement to the type of goods identified according to the probability value, as the identification
As a result.
3. a kind of weighing device according to claim 2, which is characterized in that further include secondary support, the secondary support includes
First connecting portion and the second connecting portion hinged with the first connecting portion, the first connecting portion connect with the support vertical
It connects, the top of the second connecting portion is equipped with assisted image recognition device, and the working face of the auxiliary recognition device is towards institute
State the weighing table of pedestal.
4. a kind of weighing device according to claim 3, which is characterized in that the assisted image recognition device includes binocular
Camera and the flash lamp in the binocular camera one side is set, the binocular camera and flash lamp respectively with it is described
Control module connects.
5. a kind of weighing method, which is characterized in that it is applied to any a kind of weighing device in the claims 1 to 4,
The method includes：
Obtain the weight data of article on weighing device；
Pattern recognition device action is triggered according to the weight data, obtains the image data of article on weighing device；
It receives described image data and is handled to obtain recognition result；
The recognition result is shown by display device.
6. a kind of weighing method according to claim 5, which is characterized in that the weighing method further includes：Obtain display
The input order of device, and the recognition result is directly chosen according to input order.
7. a kind of weighing method according to claim 5, which is characterized in that receive described image data and handled with
Recognition result is obtained, following steps are specifically included：
Described image data are subjected to sectional drawing processing, to obtain preprocessing image data；
The preprocessing image data is subjected to histogram equalization processing, to obtain first object image data；
The first object image data is subjected to multi-angle rotary processing, to obtain multiple second destination image datas；
Described image data and multiple second destination image datas are sent into preset training pattern to handle, it is multiple to obtain
Recognition result, each recognition result include confidence level probability of the article in each goods categories；
The confidence level probability is subjected to probability summation by the type of each article, obtain the article each article type
Probability value；
Descending arrangement is carried out to the type of goods identified according to the probability value, as the recognition result.
8. a kind of weighing method according to claim 7, which is characterized in that the multi-angle rotary include 90 °, 180 ° and
270 ° of rotations.
9. a kind of weighing method according to claim 7, which is characterized in that the training pattern is regarded using MobileNet
Feel identifying processing model.
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| CN201810392628.9A CN108663105A (en) | 2018-04-27 | 2018-04-27 | A kind of weighing device and corresponding weighing method |
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| CN201810392628.9A CN108663105A (en) | 2018-04-27 | 2018-04-27 | A kind of weighing device and corresponding weighing method |
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109886169A (en) * | 2019-02-01 | 2019-06-14 | 腾讯科技（深圳）有限公司 | Applied to the item identification method of unmanned counter, device, equipment and storage medium |
| CN110718016A (en) * | 2019-09-02 | 2020-01-21 | 上海理工大学 | Give birth to bright system of selling by oneself |
| CN110969149A (en) * | 2019-12-30 | 2020-04-07 | 韩山师范学院 | Intelligent image recognition device of chicken claw weighing machine and weighing method thereof |
| CN111554057A (en) * | 2019-02-12 | 2020-08-18 | 株式会社石田 | Metering machine |
| CN112129386A (en) * | 2019-06-24 | 2020-12-25 | 梅特勒-托利多(常州)测量技术有限公司 | Weighing apparatus and weighing method |
| CN112304410A (en) * | 2019-07-31 | 2021-02-02 | 梅特勒-托利多(常州)测量技术有限公司 | Weighing device with object recognition and weighing method |
| WO2021018161A1 (en) * | 2019-07-31 | 2021-02-04 | Mettler-Toledo (Changzhou) Measurement Technology Ltd. | Weighing system and weighing method with object recognition |
| CN114157813A (en) * | 2022-02-07 | 2022-03-08 | 深圳市慧为智能科技股份有限公司 | Electronic scale camera motion control method and device, control terminal and storage medium |
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Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109886169A (en) * | 2019-02-01 | 2019-06-14 | 腾讯科技（深圳）有限公司 | Applied to the item identification method of unmanned counter, device, equipment and storage medium |
| CN109886169B (en) * | 2019-02-01 | 2022-11-22 | 腾讯科技（深圳）有限公司 | Article identification method, device, equipment and storage medium applied to unmanned container |
| CN111554057A (en) * | 2019-02-12 | 2020-08-18 | 株式会社石田 | Metering machine |
| US11353357B2 (en) | 2019-02-12 | 2022-06-07 | Ishida Co., Ltd. | Point of sale scale with a control unit that sets the price calculated when the product is removed from the scale |
| CN112129386A (en) * | 2019-06-24 | 2020-12-25 | 梅特勒-托利多(常州)测量技术有限公司 | Weighing apparatus and weighing method |
| CN112304410A (en) * | 2019-07-31 | 2021-02-02 | 梅特勒-托利多(常州)测量技术有限公司 | Weighing device with object recognition and weighing method |
| WO2021018162A1 (en) * | 2019-07-31 | 2021-02-04 | Mettler-Toledo (Changzhou) Measurement Technology Ltd. | A weighing device and a method of weighing using object recognition |
| WO2021018161A1 (en) * | 2019-07-31 | 2021-02-04 | Mettler-Toledo (Changzhou) Measurement Technology Ltd. | Weighing system and weighing method with object recognition |
| CN110718016A (en) * | 2019-09-02 | 2020-01-21 | 上海理工大学 | Give birth to bright system of selling by oneself |
| CN110969149A (en) * | 2019-12-30 | 2020-04-07 | 韩山师范学院 | Intelligent image recognition device of chicken claw weighing machine and weighing method thereof |
| CN114157813A (en) * | 2022-02-07 | 2022-03-08 | 深圳市慧为智能科技股份有限公司 | Electronic scale camera motion control method and device, control terminal and storage medium |
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