CN109447194B - Capsule data identification method of beverage machine - Google Patents
Capsule data identification method of beverage machine Download PDFInfo
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- CN109447194B CN109447194B CN201811078938.XA CN201811078938A CN109447194B CN 109447194 B CN109447194 B CN 109447194B CN 201811078938 A CN201811078938 A CN 201811078938A CN 109447194 B CN109447194 B CN 109447194B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K17/00—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations
- G06K17/0022—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisious for transferring data to distant stations, e.g. from a sensing device
- G06K17/0029—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisious for transferring data to distant stations, e.g. from a sensing device the arrangement being specially adapted for wireless interrogation of grouped or bundled articles tagged with wireless record carriers
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07F—COIN-FREED OR LIKE APPARATUS
- G07F13/00—Coin-freed apparatus for controlling dispensing or fluids, semiliquids or granular material from reservoirs
- G07F13/06—Coin-freed apparatus for controlling dispensing or fluids, semiliquids or granular material from reservoirs with selective dispensing of different fluids or materials or mixtures thereof
- G07F13/065—Coin-freed apparatus for controlling dispensing or fluids, semiliquids or granular material from reservoirs with selective dispensing of different fluids or materials or mixtures thereof for drink preparation
Abstract
The invention discloses a capsule data identification method of a beverage machine. The capsule data identification method of the beverage machine comprises the following steps: receiving data obtained by identifying the capsule identification code by the identification lens; when the data are continuously received, storing the data meeting the identification condition in a data set in the received data; and counting the occurrence times of the data in the data set, and determining the final identification result of the capsule identification code according to the statistical result. The technical scheme of the invention can improve the recognition rate of the capsule data.
Description
Technical Field
The invention relates to the technical field of beverage machines, in particular to a capsule data identification method of a beverage machine.
Background
Along with the improvement of living standard and the adjustment of eating habits of people, the brewing beverage machine is more and more popular. The brewing beverage machine identifies the OID on the surface of the beverage capsule through an OID (Optical Identification code) Identification lens to obtain capsule data.
When the capsule data is identified by the aid of the OID identification lens, the data can be transmitted to the main control chip. The data is subject to interference distortion during transmission, thereby transmitting erroneous identification data.
The related capsule data recognition method generally employs a sequential recognition algorithm, and when the same data is received N times (e.g., 3 to 20 times) in succession, valid data is considered to have been received. This determination method has a low recognition rate.
Disclosure of Invention
The embodiment of the invention provides a capsule data identification method of a beverage machine, which can improve the identification rate of capsule data.
The embodiment of the invention provides a capsule data identification method of a beverage machine, which comprises the following steps:
receiving data obtained by identifying the capsule identification code by the identification lens;
when the data are continuously received, storing the data meeting the identification condition in a data set in the received data;
and counting the occurrence times of the data in the data set, and determining the final identification result of the capsule identification code according to the statistical result.
Compared with the prior art, according to the capsule data identification method of the beverage machine, the identification module identifies the capsule identification code through the identification lens to obtain data and sends the data to the main control module, the main control module stores the data meeting the identification condition in the received data in a data set when the data are continuously received, counts the occurrence frequency of the data in the data set, and determines the final identification result of the capsule identification code according to the statistical result. According to the technical scheme of the embodiment of the invention, the identification rate of the capsule data can be improved by filtering out data which do not meet identification conditions (invalid) and error data (data with few occurrence times).
Drawings
Fig. 1 is a flowchart of a method for identifying capsule data of a beverage machine according to embodiment 1 of the present invention;
fig. 2 is a schematic view of a beverage machine according to embodiment 2 of the present invention;
FIG. 3 is a flow chart of a method of identifying data in a data set according to example 1 of the present invention;
fig. 4 is a flow chart of a method of identifying data in a data set according to example 2 of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be noted that the embodiments and features of the embodiments in the present application may be arbitrarily combined with each other without conflict.
Example 1
As shown in fig. 1, an embodiment of the present invention provides a method for identifying capsule data of a beverage machine, including:
step S110, receiving data obtained by identifying the lens and the capsule identification code;
step S120, when the data are continuously received, storing the data meeting the identification condition in a data set;
step S130, counting the occurrence frequency of the data in the data set, and determining the final identification result of the capsule identification code according to the counting result.
In one embodiment, the capsule Identification code is OID (Optical Identification) data;
in one embodiment, the method further comprises:
when the data is a single receipt, the single data received is taken as the final result of identifying the capsule identification code.
In one embodiment, the interval for transmitting data by the identification lens may be set as required, for example, m data are transmitted within 1 second.
The identification lens can be configured to be in a continuous sending mode or a single sending mode, data is sent only once after the capsule identification code (film) is identified in the single sending mode, and data is sent continuously after the capsule identification code is identified in the continuous sending mode. Configuring the recognition shot in a continuous transmission mode may improve the recognition rate.
The identification distance of the identification lens is 0-5mm, and the preferred distance is 2 mm. The number of recognition frames per second of the recognition shots can be configured by software, and is preferably 5, 20, 30, 40, 50, etc. For example, if the number of recognition frames per second of the recognition camera is set to 20 frames/second, the recognition camera transmits data 20 times per second.
In one embodiment, the storing, in a data set, data that satisfies the identification condition among the received plurality of data includes:
recognizing the closing of the brewing switch, and storing data received in a first time period T1 before the brewing switch is closed and a second time period T2 after the brewing switch is closed in a data set;
wherein T1 is more than 0s and less than or equal to 5s, and T2 is more than 0s and less than or equal to 5 s.
Optionally, the first time period T1 is less than the second time period T2. For example, T1 equals 2 seconds, T2 equals 3 seconds;
in one embodiment, the saving, in a data set, data that satisfies the identification condition among the received plurality of data further includes:
recognizing the disconnection of the brewing switch, and clearing the data received in a third time period T3 after the disconnection of the brewing switch from the data set;
wherein T3 is more than 0s and less than or equal to 2s, and T3 is more than T1.
Optionally, the third time period T3 is equal to 500 ms;
in one embodiment, the saving, in a data set, data that satisfies the identification condition among the received plurality of data further includes:
judging whether the time interval T4 between the current closing and the last opening of the brewing switch is less than or equal to a third time period T3, if so, clearing all data received before the current closing of the brewing switch from the data set; otherwise, the following judgment is carried out:
and judging whether the time interval T4 between the closing and the last opening of the brewing switch is less than or equal to a first time period T1, if so, storing the data in the time period T4-T3 before the brewing switch is closed in a data set, otherwise, storing the data in the time period T1 before the brewing switch is closed in the data set.
Wherein, the brewing cavity is externally provided with a microswitch (brewing switch), and when a user rotates the screw cover, the microswitch is changed from off to on. The main control module MCU will save the data of 0-5 seconds (T1, preferably 2 seconds) before the micro switch is closed and the data of 0-5 seconds (T2, preferably 3 seconds) after the micro switch is closed, thus not only improving the identification rate, but also not wasting too much time under the condition of not putting the capsule.
In order to prevent the data identified when the user opens the screw cap to take out the capsule from interfering with the logical judgment of the next function performed by the machine, i.e. the data should be cleared in time when the user opens the screw cap to prevent the next operation from being affected, the machine may not store the data during a period of time (T3, preferably 500 ms) during which the inching has just been switched off. This logic can eliminate the situation where the user quickly removes the capsule and screws on the screw cap, the entire process being completed in 2 seconds (the chip is now holding the identified data). Assuming that the data saved 500ms before the micro-motion was opened is not cleared, a misidentification may occur when the user takes out the capsule and then closes the screw cap to perform cleaning or preparation.
That is, the time point of the on or off of the brewing switch is used as the staking time point, and the identification program uses the staking time point as the scale to identify the data before and after the staking time point.
In one embodiment, the determining the final recognition result of the capsule identification code according to the statistical result includes:
and taking the data with the largest occurrence number in the data set as a final identification result of the capsule identification code identified by the identification lens.
In one embodiment, the determining the final recognition result of the capsule identification code according to the statistical result includes:
taking the data with the occurrence frequency equal to or more than N/2 in the data set as a final identification result of the capsule identification code identified by the identification lens; n is the total number of data in the data set.
In one embodiment, the storing data satisfying the identification condition in a data set, counting the number of occurrences of the data in the data set, and determining the final identification result of the capsule identification code according to the statistical result includes:
when the number of the identification shots is multiple, storing data meeting identification conditions in multiple data received from each identification shot in a data set corresponding to the identification shot; counting the occurrence times of data in the data set corresponding to each identification lens, and determining the result of identifying the capsule identification code by each identification lens according to the counting result;
comparing the results of the capsule identification codes identified by the identification lenses, and determining the final identification result of the capsule identification codes according to the comparison result:
if the identification results of all the identification lenses are the same, taking the identification result of any one identification lens as the final identification result of the capsule identification code;
if the recognition results of the recognition lenses are different, storing data meeting the recognition conditions in a plurality of data received by all the recognition lenses in a unified data set, counting the occurrence times of the data in the unified data set again, and taking the data with the most occurrence times as the final recognition result of the capsule recognition code; or if the recognition results of the recognition shots are different, comparing the occurrence times of the recognition results of the recognition shots in the data set of the recognition shots, and taking the recognition result of the recognition shot with the largest occurrence time as the final recognition result of the capsule identification code.
In one embodiment, the counting the number of occurrences of the data in the data set and determining the final identification result of the capsule identification code according to the counting result includes:
step a: setting a candidate main element counter c by taking the 1 st data D0 in the data set as a candidate main element;
step b: traversing data one by one from the 2 nd element in the data set, if the ith data Di-1 is the same as the candidate main element, the candidate main element counter c increases the count, and if the ith data Di-1 is not the same as the candidate main element, the ith data Di-1 is counted separately; comparing the count value of the counter c of the candidate main element with the count values of other data, and if the count value of the candidate main element is maximum, keeping the candidate main element unchanged; if the count value of the candidate main element is not the maximum, taking the data with the maximum count value as a new candidate main element, and updating the count value of the candidate main element counter c to the count value of the new candidate main element; wherein i is more than or equal to 2 and less than or equal to N, and N is the total number of data in the data set;
step c: and after all data traversal is finished, taking the finally obtained candidate main element as a final recognition result of the capsule recognition code.
In one embodiment, the step c comprises:
and judging whether the finally obtained count value of the candidate main element is greater than or equal to N/2, if so, taking the finally obtained candidate main element as the final recognition result of the capsule recognition code.
In one embodiment, the counting the number of occurrences of the data in the data set and determining the final identification result of the capsule identification code according to the counting result includes:
step A: sorting N data in the data set according to sizes;
b, setting a candidate main element counter c by taking the 1 st data D0 in the data set as a candidate main element;
and C: traversing data one by one from the 2 nd element in the data set, if the ith data Di-1 is the same as the candidate main element, increasing the count of the candidate main element counter c, and if the ith data Di-1 is not the same as the candidate main element, taking the ith data Di-1 as a new candidate main element, and counting again by the candidate main element counter c; wherein i is more than or equal to 2 and less than or equal to N, and N is the total number of data in the data set;
step D: and after all data traversal is finished, comparing the count values of all the presented candidate main elements, and selecting the candidate main element with the largest count number as the final identification result of the capsule identification code.
Example 2
As shown in fig. 2, an embodiment of the present invention provides a beverage machine, including:
the identification module 10 is used for identifying the capsule identification code through the identification lens to obtain data and sending the data to the main control module;
the main control module 20 is configured to store, in a data set, data that meets the identification condition among the received multiple data when the data are continuously received; and counting the occurrence times of the data in the data set, and determining the final identification result of the capsule identification code according to the statistical result.
The beverage machine further comprises an identification lens 30 for optically identifying the capsule identification code;
the beverage machine is provided with a brewing switch 40, the brewing switch is triggered by the capsule for the beverage machine in the installation process, and the data identification of the beverage machine is matched with the on or off of the brewing switch.
In one embodiment, the capsule Identification code is OID (Optical Identification) data;
in one embodiment, the master control module 20 is further configured to use the received single data as a final result of identifying the capsule identification code when the data is received in a single time.
In one embodiment, the interval for transmitting data by the identification lens may be set as required, for example, m data are transmitted within 1 second. Thus, the master control module may receive multiple data within 1 second.
The identification lens can be configured to be in a continuous sending mode or a single sending mode, data is sent only once after the capsule identification code (film) is identified in the single sending mode, and data is sent continuously after the capsule identification code is identified in the continuous sending mode. Configuring the recognition shot in a continuous transmission mode may improve the recognition rate.
In one embodiment, the main control module 20 is configured to store, in the data set, data that meets the identification condition in the received multiple data in the following manner:
recognizing the closing of the brewing switch, and storing data received in a first time period T1 before the brewing switch is closed and a second time period T2 after the brewing switch is closed in a data set;
wherein T1 is more than 0s and less than or equal to 5s, and T2 is more than 0s and less than or equal to 5 s.
Optionally, the first time period T1 is less than the second time period T2. For example, T1 equals 2 seconds, T2 equals 3 seconds;
in an embodiment, the main control module 20 is further configured to store, in the data set, data that meets the identification condition in the received multiple data in the following manner:
recognizing the disconnection of the brewing switch, and clearing the data received in a third time period T3 after the disconnection of the brewing switch from the data set;
wherein T3 is more than 0s and less than or equal to 2s, and T3 is more than T1.
Optionally, the third time period T3 is equal to 500 ms;
in an embodiment, the main control module 20 is further configured to store, in the data set, data that meets the identification condition in the received multiple data in the following manner:
judging whether the time interval T4 between the current closing and the last opening of the brewing switch is less than or equal to a third time period T3, if so, clearing all data received before the current closing of the brewing switch from the data set; otherwise, the following judgment is carried out:
and judging whether the time interval T4 between the current closing and the last opening of the brewing switch is less than or equal to a first time period T1, if so, storing the data in the time period T4-T3 before the brewing switch is closed in a data set, otherwise, storing the data in the time period T1 before the brewing switch is closed in the data set.
In the above mode, the time point of the on or off of the brewing switch is used as the staking time point, and the identification program uses the staking time point as the scale to identify data before and after the staking time point.
In one embodiment, the main control module 20 is configured to determine the final identification result of the capsule identification code according to the statistical result by the following method:
and taking the data with the largest occurrence number in the data set as a final identification result of the capsule identification code identified by the identification lens.
In one embodiment, the main control module 20 is configured to determine the final identification result of the capsule identification code according to the statistical result by the following method:
taking the data with the occurrence frequency equal to or more than N/2 in the data set as a final identification result of the capsule identification code identified by the identification lens; n is the total number of data in the data set.
In one embodiment, the main control module 20 is configured to store data meeting the identification condition in a data set, count the number of occurrences of the data in the data set, and determine a final identification result of the capsule identification code according to the statistical result, in the following manner:
when the number of the identification shots is multiple, storing data meeting identification conditions in multiple data received from each identification shot in a data set corresponding to the identification shot; counting the occurrence times of data in the data set corresponding to each identification lens, and determining the result of identifying the capsule identification code by each identification lens according to the counting result;
comparing the results of the capsule identification codes identified by the identification lenses, and determining the final identification result of the capsule identification codes according to the comparison result:
if the identification results of all the identification lenses are the same, taking the identification result of any one identification lens as the final identification result of the capsule identification code;
if the recognition results of the recognition lenses are different, storing data meeting the recognition conditions in a plurality of data received by all the recognition lenses in a unified data set, counting the occurrence times of the data in the unified data set again, and taking the data with the most occurrence times as the final recognition result of the capsule recognition code; or if the recognition results of the recognition shots are different, comparing the occurrence times of the recognition results of the recognition shots in the data set of the recognition shots, and taking the recognition result of the recognition shot with the largest occurrence time as the final recognition result of the capsule identification code.
In one embodiment, the main control module 20 is configured to count the number of occurrences of the data in the data set in the following manner, and determine a final identification result of the capsule identification code according to the statistical result:
step a: setting a candidate main element counter c by taking the 1 st data D0 in the data set as a candidate main element;
step b: traversing data one by one from the 2 nd element in the data set, if the ith data Di-1 is the same as the candidate main element, the candidate main element counter c increases the count, and if the ith data Di-1 is not the same as the candidate main element, the ith data Di-1 is counted separately; comparing the count value of the counter c of the candidate main element with the count values of other data, and if the count value of the candidate main element is maximum, keeping the candidate main element unchanged; if the count value of the candidate main element is not the maximum, taking the data with the maximum count value as a new candidate main element, and updating the count value of the candidate main element counter c to the count value of the new candidate main element; wherein i is more than or equal to 2 and less than or equal to N, and N is the total number of data in the data set;
step c: and after all data traversal is finished, taking the finally obtained candidate main element as a final recognition result of the capsule recognition code.
In one embodiment, the main control module 20 is configured to use the finally obtained candidate main element as the final recognition result of the capsule identification code in the following manner: and judging whether the finally obtained count value of the candidate main element is greater than or equal to N/2, if so, taking the finally obtained candidate main element as the final recognition result of the capsule recognition code.
In one embodiment, the main control module 20 is configured to count the number of occurrences of the data in the data set in the following manner, and determine a final identification result of the capsule identification code according to the statistical result:
step A: sorting N data in the data set according to sizes;
b, setting a candidate main element counter c by taking the 1 st data D0 in the data set as a candidate main element;
and C: traversing data one by one from the 2 nd element in the data set, if the ith data Di-1 is the same as the candidate main element, increasing the count of the candidate main element counter c, and if the ith data Di-1 is not the same as the candidate main element, taking the ith data Di-1 as a new candidate main element, and counting again by the candidate main element counter c; wherein i is more than or equal to 2 and less than or equal to N, and N is the total number of data in the data set;
step D: and after all data traversal is finished, comparing the count values of all the presented candidate main elements, and selecting the candidate main element with the largest count number as the final identification result of the capsule identification code.
Example 3
The embodiment of the invention provides a capsule for a drink machine, which comprises:
the capsule is provided with a capsule Identification code for identifying by the capsule data Identification method of the beverage machine of embodiment 1, and the capsule Identification code is an Optical Identification code (Optical Identification, abbreviated as OID).
The identification method of the capsule data is explained below by examples 1 and 2.
Example 1
In addition, when the OID lens identifies data, due to a reflection phenomenon of a capsule film, an image analysis error may occur, and the transmitted data is also error data.
In this example, the main control module defines an array with a length of N (e.g. 100) inside, and is used for storing data meeting the identification condition. For example, 40 data are used to save data 2 seconds before the brew switch is closed (assuming 20 frames of data are transmitted per second), and 60 data are used to save data 3 seconds after the brew switch is closed. And identifying N data in the data set, and taking the data with the most occurrence times as a final identification result, so that the influence of error codes on identification can be reduced.
As shown in fig. 3, identifying data in a data set according to the number of occurrences may include the following steps:
step 301: sorting N data in the data set from small to large;
step 302: taking the 1 st data D0 in the data set as a candidate main element v, setting the initial value of a candidate main element counter c, c to be 1, and setting the initial value of a data traversal counter i, i to be 2;
step S303: judging whether i is less than or equal to N, if so, executing step S304, otherwise, executing step S308;
step S304: judging whether the ith data Di-1 is the same as the candidate main element v, if so, executing a step S305, otherwise, executing a step S306;
step S305: the candidate main element counter c is incremented by 1, and step S307 is executed;
step S306: taking the ith data Di-1 as a new candidate main element v, and setting a candidate main element counter c to be 1;
step S307: the data traversal counter i is increased by 1, and the step S303 is returned;
step S308: and comparing the counting values of all the presented candidate main elements, and selecting the candidate main element with the largest counting number as the final identification result of the capsule identification code.
Example 2
In this example, an array with a length of N is defined inside the main control module, and is used for storing data meeting the identification condition. And identifying N data in the data set, and taking the data with the occurrence frequency of more than or equal to N/2 as a final identification result, so that the influence of error codes on identification can be reduced.
As shown in fig. 4, identifying the data in the data set according to the occurrence number may include the following steps:
step 401: taking the 1 st data D0 in the data set as a candidate main element v, setting the initial value of a candidate main element counter c, c to be 1, and setting the initial value of a data traversal counter i, i to be 2;
step S402, judging whether i is less than or equal to N, if so, executing step S403, otherwise, executing step S411;
step S403, judging whether the ith data Di-1 is the same as the candidate main element v, if so, executing step S404, otherwise, executing step S405;
step S404, the candidate main element counter c is increased by 1, and step S406 is executed;
step S405, counting the ith data Di-1 individually, and executing step S406;
step S406: the data traversal counter i is increased by 1;
step S407: comparing the count value of the counter c of the candidate main element with the count values of other data;
step S408: judging whether the count value c of the candidate main element is the maximum, if so, executing the step S409, otherwise, executing the step S410;
step S409: keeping the candidate main elements unchanged, and returning to the step S402;
step S410: taking the data with the largest count value as a new candidate main element, updating the count value of the candidate main element counter c to the count value of the new candidate main element, and returning to the step S402;
step S411: judging whether the finally obtained count value c of the candidate main element is greater than or equal to N/2, if so, executing the step S412, otherwise, executing the step S413;
step S412: and taking the finally obtained candidate main elements as the final recognition result of the capsule recognition code, and ending.
Step S413: and (5) failing to identify, and ending.
It should be noted that the present invention can be embodied in other specific forms, and various changes and modifications can be made by those skilled in the art without departing from the spirit and scope of the invention.
Claims (9)
1. A method of capsule data identification for a beverage machine, comprising:
receiving data obtained by identifying the capsule identification code by the identification lens;
when the data are continuously received, storing the data meeting the identification condition in a data set in the received data;
counting the occurrence times of the data in the data set, and determining the final identification result of the capsule identification code according to the counting result;
the storing, in a data set, data that satisfies an identification condition among the received plurality of data includes:
recognizing the closing of the brewing switch, and storing data received within a first time period T1 before the brewing switch is closed in a data set;
recognizing the disconnection of the brewing switch, and clearing the data received in a third time period T3 after the disconnection of the brewing switch from the data set;
judging whether the time interval T4 between the current closing and the last opening of the brewing switch is less than or equal to a third time period T3, if so, clearing all data received before the current closing of the brewing switch from the data set; otherwise, the following judgment is carried out:
and judging whether the time interval T4 between the current closing and the last opening of the brewing switch is less than or equal to a first time period T1, if so, storing the data in the time period T4-T3 before the brewing switch is closed in a data set, otherwise, storing the data in the time period T1 before the brewing switch is closed in the data set.
2. The method of claim 1, wherein:
the storing, in a data set, data that satisfies an identification condition among the received plurality of data includes:
storing data received within a second time period T2 after the brewing switch is closed in a data set;
wherein T1 is more than 0s and less than or equal to 5s, and T2 is more than 0s and less than or equal to 5 s.
3. The method of claim 2, wherein:
t3 is more than 0s and less than or equal to 2s, and T3 is more than T1.
4. The method of claim 1, wherein:
the determining the final recognition result of the capsule recognition code according to the statistical result includes:
and taking the data with the largest occurrence number in the data set as a final identification result of the capsule identification code identified by the identification lens.
5. The method of claim 4, wherein:
the determining the final recognition result of the capsule recognition code according to the statistical result includes:
taking the data with the occurrence frequency equal to or more than N/2 in the data set as a final identification result of the capsule identification code identified by the identification lens; n is the total number of data in the data set.
6. The method of claim 1, wherein:
the step of storing data meeting the identification condition in a data set, counting the occurrence times of the data in the data set, and determining the final identification result of the capsule identification code according to the statistical result includes:
when the number of the identification shots is multiple, storing data meeting identification conditions in multiple data received from each identification shot in a data set corresponding to the identification shot; counting the occurrence times of data in the data set corresponding to each identification lens, and determining the result of identifying the capsule identification code by each identification lens according to the counting result;
comparing the results of the capsule identification codes identified by the identification lenses, and determining the final identification result of the capsule identification codes according to the comparison result:
if the identification results of all the identification lenses are the same, taking the identification result of any one identification lens as the final identification result of the capsule identification code;
if the recognition results of the recognition lenses are different, storing data meeting the recognition conditions in a plurality of data received by all the recognition lenses in a unified data set, counting the occurrence times of the data in the unified data set again, and taking the data with the most occurrence times as the final recognition result of the capsule recognition code; or if the recognition results of the recognition shots are different, comparing the occurrence times of the recognition results of the recognition shots in the data set of the recognition shots, and taking the recognition result of the recognition shot with the largest occurrence time as the final recognition result of the capsule identification code.
7. The method of claim 1, wherein:
the counting the occurrence times of the data in the data set and determining the final recognition result of the capsule identification code according to the counting result comprise:
step a: setting a candidate main element counter c by taking the 1 st data D0 in the data set as a candidate main element;
step b: traversing data one by one from the 2 nd element in the data set, if the ith data Di-1 is the same as the candidate main element, the candidate main element counter c increases the count, and if the ith data Di-1 is not the same as the candidate main element, the ith data Di-1 is counted separately; comparing the count value of the counter c of the candidate main element with the count values of other data, and if the count value of the candidate main element is maximum, keeping the candidate main element unchanged; if the count value of the candidate main element is not the maximum, taking the data with the maximum count value as a new candidate main element, and updating the count value of the candidate main element counter c to the count value of the new candidate main element; wherein i is more than or equal to 2 and less than or equal to N, and N is the total number of data in the data set;
step c: and after all data traversal is finished, taking the finally obtained candidate main element as a final recognition result of the capsule recognition code.
8. The method of claim 7, wherein:
the step c comprises the following steps:
and judging whether the finally obtained count value of the candidate main element is greater than or equal to N/2, if so, taking the finally obtained candidate main element as the final recognition result of the capsule recognition code.
9. The method of claim 1, wherein:
the counting the occurrence times of the data in the data set and determining the final recognition result of the capsule identification code according to the counting result comprise:
step A: sorting N data in the data set according to sizes;
b, setting a candidate main element counter c by taking the 1 st data D0 in the data set as a candidate main element;
and C: traversing data one by one from the 2 nd element in the data set, if the ith data Di-1 is the same as the candidate main element, increasing the count of the candidate main element counter c, and if the ith data Di-1 is not the same as the candidate main element, taking the ith data Di-1 as a new candidate main element, and counting again by the candidate main element counter c; wherein i is more than or equal to 2 and less than or equal to N, and N is the total number of data in the data set;
step D: and after all data traversal is finished, comparing the count values of all the presented candidate main elements, and selecting the candidate main element with the largest count number as the final identification result of the capsule identification code.
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| CN107108114A (en) * | 2014-12-11 | 2017-08-29 | Qbo咖啡有限责任公司 | Drink capsule, beverage preparation system and drink capsule recognition methods |
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