An image error-proofing detection method, system, electronic device and readable storage medium

Abstract

The application discloses an image mistake-proof detection method and system, electronic equipment and a readable storage medium, and relates to the mistake-proof detection field. The method comprises the following steps: acquiring standard image data of a standard sample group of a target type device; acquiring standard states corresponding to all standard parts in a target model device under the target type device; acquiring actual measurement image data of an entity device; comparing the actual measurement image data and the standard image data to determine actual states corresponding to morphological parameters of all actual measurement parts corresponding to the standard parts in the actual measurement image data; and comparing whether the actual states conform to the standard states of the target model device to determine whether the entity device conforms to the standard of the target model device. According to the method, the mistake-proof object can be replaced by simply adjusting the standard states of the target model device, and the workload required for modification in later engineering changes is obviously reduced. Meanwhile, the method can effectively guarantee the mistake-proof checking between different models.

Description

Technical Field

[0001] The present invention relates to the field of error prevention detection, and in particular to an image error prevention detection method, system, electronic device and readable storage medium. Background Art

[0002] Image error-proofing detection systems are used on traditional production lines to detect missing or incorrectly installed products, as well as incorrect parts usage. A specific image detection program is typically designed for a specific product variant. This program can only detect that specific variant. If the product variant being detected is replaced with another model, the image detection program must be modified and adjusted accordingly.

[0003] When there are multiple variant models of the same product type, the operation and maintenance of the image inspection program is more difficult. If there are subsequent engineering changes, each image inspection program needs to be adjusted one by one, which is time-consuming and labor-intensive. In addition, it is difficult to verify the programs of multiple variant products with each other. For example, it is impossible to determine whether the program of product A can prevent errors for products B and C, and the verification workload is huge.

[0004] Therefore, how to provide a solution to the above technical problems is a problem that those skilled in the art need to solve. Summary of the Invention

[0005] In view of this, the purpose of the present invention is to provide an image error-proofing detection method, system, electronic device, and readable storage medium with less workload and higher efficiency. The specific solution is as follows:

[0006] An image error-proofing detection method, comprising:

[0007] Acquire standard image data of a standard sample set of a target type device, wherein the standard sample set includes a plurality of standard parts, each of the standard parts corresponds to at least one morphological parameter, and each of the morphological parameters corresponds to at least two standard states;

[0008] Obtain the standard states corresponding to all the standard parts in the target model device under the target type device;

[0009] Acquiring measured image data of a physical device;

[0010] Comparing the measured image data with the standard image data, and determining the actual states corresponding to the morphological parameters of all measured parts corresponding one by one to the standard parts in the measured image data;

[0011] comparing whether the actual state conforms to the standard state of the target model device;

[0012] If so, determining that the physical device meets the standards of the target model device;

[0013] If not, it is determined that the physical device does not meet the standard of the target model device.

[0014] Preferably, each of the morphological parameters corresponds to two standard states. Accordingly, the process of obtaining standard image data of a standard sample set of target type devices includes:

[0015] Acquire first image data of a first model device and second image data of a second model device; wherein the first model device and the second model device both belong to the target type device, and all the standard states of the first model device are different from all the standard states of the second model device.

[0016] Preferably, after obtaining the standard image data of the standard sample set of the target type device, the method further includes:

[0017] Assigning different standard values ​​to different standard states of the same morphological parameter;

[0018] After obtaining the standard states corresponding to all the standard parts in the target model device under the target type device, the method further includes:

[0019] Filling all the standard states with the standard values ​​into the sequence bits corresponding to the morphological parameters to obtain a target model sequence;

[0020] Accordingly, after determining the actual states corresponding to the morphological parameters of all measured parts corresponding to the standard parts one by one in the measured image data, the method further includes:

[0021] Filling the standard values ​​corresponding to all the actual states into the sequence bits corresponding to the morphological parameters to obtain a measured sequence;

[0022] Accordingly, the process of comparing whether the actual state conforms to the standard state of the target model device includes:

[0023] Comparing whether the measured sequence is consistent with the target model sequence;

[0024] If so, determining that the actual state meets the standard state of the target model device;

[0025] If not, it is determined that the actual state does not conform to the standard state of the target model device.

[0026] Preferably, the standard values ​​are all binary numbers.

[0027] Preferably, the image error-proofing detection method further includes:

[0028] The measured sequence and the target model sequence are converted into decimal numbers and output.

[0029] Preferably, the standard value is 2 N The value in base form, N is a positive integer, 2 N Not less than the maximum number of the standard values ​​corresponding to each of the morphological parameters.

[0030] Preferably, when it is determined that the physical device does not meet the standards of the target model device, the method further includes:

[0031] The measured parts and the corresponding morphological parameters in the physical device that do not conform to the target signal device are marked.

[0032] Accordingly, the present application also discloses an image error-proofing detection system, comprising:

[0033] A standard sample group module is used to obtain standard image data of a standard sample group of a target type device, wherein the standard sample group includes a plurality of standard parts, each of the standard parts corresponds to at least one morphological parameter, and each of the morphological parameters corresponds to at least two standard states;

[0034] A target model module, configured to obtain the standard states corresponding to all the standard parts in the target model device under the target type device;

[0035] A measurement module, used to obtain measured image data of a physical device;

[0036] a first comparison module, configured to compare the measured image data with the standard image data, and determine the actual states corresponding to the morphological parameters of all measured parts corresponding one by one to the standard parts in the measured image data;

[0037] The second comparison module is used to compare whether the actual state meets the standard state of the target model device; if so, determine that the physical device meets the standard of the target model device; if not, determine that the physical device does not meet the standard of the target model device.

[0038] Accordingly, the present application also discloses an electronic device, comprising:

[0039] memory for storing computer programs;

[0040] A processor is used to implement the steps of the image error prevention detection method as described in any one of the above items when executing the computer program.

[0041] Correspondingly, the present application also discloses a readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the image error prevention detection method as described in any one of the above items are implemented.

[0042] The present application designs a more general image error prevention detection method. Based on standard image data including all possible morphological parameters of all standard parts and the standard states of all morphological parameters, the standard image data is compared with the measured image data. The actual state of each morphological parameter of each measured part in the measured image data can be quickly obtained, and the actual state can be compared with the standard state of the target model device that needs error prevention to obtain the detection result.

[0043] The method of the present application uses the same set of program methods to realize error-proofing detection of multiple target signal devices. There is no need to set different detection programs for different variant products. The error-proofing object can be replaced by simply adjusting the standard state of the target model device. Even if the project changes in the later stage, the workload required for modification is significantly reduced. At the same time, all target model devices in the present method use a unified judgment method to determine the corresponding combination of different standard states, so it can effectively ensure error-proofing verification between different models. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0045] Figure 1 This is a flowchart of the steps of an image error prevention detection method according to an embodiment of the present invention;

[0046] Figure 2 This is a structural distribution diagram of a specific image error prevention detection method according to an embodiment of the present invention;

[0047] Figure 3a This is a structural distribution diagram of a specific model device in an embodiment of the present invention;

[0048] Figure 3b This is a structural distribution diagram of another specific model device in an embodiment of the present invention;

[0049] Figure 4 This is a structural distribution diagram of a display interface in an embodiment of the present invention;

[0050] Figure 5 2 is a structural distribution diagram of an image error-proofing detection system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0051] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0052] Traditional impact error prevention detection usually designs a specific image detection program for a variant product of a certain model. Therefore, the program can only be used to detect variant products of that signal. When the variant product to be detected is replaced with another model, the image detection program must also be modified and adjusted accordingly.

[0053] When there are multiple variant models of the same product type, the operation and maintenance of the image detection program is more difficult. If there are subsequent engineering changes, each image detection program needs to be adjusted one by one, which is time-consuming and labor-intensive. In addition, it is difficult to verify the programs of multiple variant products with each other.

[0054] The present application uses the same set of program methods to realize error-proofing detection of multiple target signal devices. There is no need to set different detection programs for different variant products. The error-proofing object can be replaced by simply adjusting the standard state of the target model device. Even if the project changes later, the workload required for modification is significantly reduced. At the same time, all target model devices in this method use a unified judgment method to determine the corresponding combination of different standard states, so it can effectively ensure error-proofing verification between different models.

[0055] The embodiment of the present invention discloses an image error detection method, see Figure 1 As shown, including:

[0056] S01: Acquire standard image data of a standard sample set of a target type device, where the standard sample set includes a plurality of standard parts, each standard part corresponds to at least one morphological parameter, and each morphological parameter corresponds to at least two standard states;

[0057] It is understandable that a standard sample group includes multiple standard parts. For example, if the target type device is a switch unit, the multiple standard parts in the switch unit include buttons, light guide bars, slots, and other objects that can be identified by image recognition. The multiple optional morphological parameters of each standard part include but are not limited to the existence state of the standard part, the model of the standard part, the color of the standard part, and the size of the standard part. Accordingly, the standard state corresponding to each morphological parameter is set according to the working condition and morphological parameters of the standard part. For example, if the morphological parameter is the existence state of the standard part, the morphological parameter includes two standard states: existence and non-existence. For another example, when the morphological parameter is the color of the standard part, the multiple standard states of the morphological parameter correspond to all possible colors of the standard part. The same applies to other morphological parameters.

[0058] Furthermore, in order to improve the sampling efficiency of standard parts, each morphological parameter can be set to correspond to two standard states. Accordingly, the process of obtaining standard image data of a standard sample group of a target type device includes:

[0059] First image data of a first model device and second image data of a second model device are obtained; wherein the first model device and the second model device are both target type devices, and all standard states of the first model device are different from all standard states of the second model device.

[0060] It can be seen that at this time, the standard state of all standard parts in the complete standard sample set can be determined by using only the measured image data of two specific model devices. For example, the standard parts in the switch unit include 5 buttons, and the morphological parameters of these 5 buttons are mainly color. The two standard states are black and white. At this time, the standard sample with 5 buttons all white can be selected as the first model device, and the standard sample with 5 buttons all black can be selected as the second model device. Through these two standard samples, the standard state of all standard parts in the complete standard sample set can be obtained, which greatly reduces the number of standard samples.

[0061] It can be understood that if the number of standard states of a certain morphological parameter exceeds 2, or there is a logical order between the morphological parameters, the number of standard samples providing standard image data can be adjusted according to the actual working conditions, as long as all standard states of all standard parts of the complete standard sample group can be obtained.

[0062] S02: Obtaining the standard states corresponding to all standard parts in the target model device under the target type device;

[0063] It is understood that the target model device is a subset of the target type device, further restricting the standard states of each standard component. In this embodiment, the target model device no longer requires a specially manufactured standard sample; the corresponding standard state can be directly found from the standard sample group. For example, the five buttons in the switch unit of the target type device are standard components, and their morphological parameters are color. The standard states include black and white. The target model device can select the standard states of the five buttons as white, black, white, black, and white, respectively. The specific standard state of each standard component in the target signal device is determined according to the error-proofing detection target. It is also possible that multiple standard states of the same morphological parameter for the same standard component may exist, and one or more standard states meet the requirements of the target model device. This is not limited here.

[0064] S03: Acquire measured image data of the physical device;

[0065] It can be understood that the physical device here is a physical component that needs to perform error prevention detection.

[0066] It is understandable that the acquisition of standard image data in step S01 and the acquisition of measured image data in this step S03 are generally achieved through an image acquisition device. Since the method of this embodiment is implemented by a program, the image content acquired by the image acquisition device is described as measured image data and standard image data. The image content acquired by the image acquisition device can be various forms of images such as color photos, black and white photos, X-ray structures, etc., which are not limited here. In addition, standard image data can also be generated by modeling and rendering the structural diagram through other software, or directly using design drawings and / or design parameters. There should be a definite mapping relationship between standard image data and measured image data, which is the basis and prerequisite for the implementation of error-proofing detection in this embodiment.

[0067] S04: comparing the measured image data with the standard image data to determine the actual states corresponding to the morphological parameters of all measured parts that correspond one by one to the standard parts in the measured image data;

[0068] S05: Compare whether the actual state conforms to the standard state of the target model device;

[0069] S06: If yes, then determine that the physical device meets the standards of the target model device;

[0070] S07: If not, it is determined that the physical device does not meet the standards of the target model device.

[0071] It can be understood that steps S04-S07 are the main image error prevention detection process, wherein step S04 compares the measured image data with the standard image data, performs standard positioning on each measured part in the measured image data, and determines the standard state closest to each morphological parameter of the measured part as the actual state; step S05 compares whether the actual state of the measured part is consistent with the standard state of the target signal device. If they are consistent, the physical device meets the standards of the target model device; if they are inconsistent, the physical device does not meet the standards of the target model device, and the error prevention is successful.

[0072] Specifically, still taking the five buttons in the switch unit of the target type device as a standard part as an example, assuming that its morphological parameter is color, the standard states include black and white, and the target model device can select the standard states of the five buttons as white, black, white, black, and white in sequence; obtain the measured image data of the physical device and compare it with the standard image data, determine that the actual states of the five buttons of the physical part are white, black, black, black, and white, and then compare the actual states with the standard states of the target model device. It can be found that the actual state of the third button does not meet the standard states of the target model device, and therefore it is determined that the physical device does not meet the standards of the target model device.

[0073] Since this embodiment can determine the measured parts whose actual state does not conform to the standard state of the target model device, further, when it is determined that the physical device does not conform to the standard of the target model device, it also includes:

[0074] Mark the measured parts and corresponding morphological parameters in the physical device that do not conform to the target signal device.

[0075] It is understandable that traditional error-proofing detection generally only compares the target sample image and the measured sample image to see if they are completely consistent, and then outputs a unique conclusion that the device meets the target model or does not meet the target model, and cannot provide specific error locations or parameters. The analysis granularity of this embodiment is at the level of morphological parameters of standard parts, measured parts, etc., and the measured parts that do not meet the requirements are located and marked, which further improves the depth of error-proofing detection, provides staff with more valuable reference detection results, and reduces the subsequent workload of staff.

[0076] The present application designs a more general image error prevention detection method. Based on standard image data including all possible morphological parameters of all standard parts and the standard states of all morphological parameters, the standard image data is compared with the measured image data. The actual state of each morphological parameter of each measured part in the measured image data can be quickly obtained, and the actual state can be compared with the standard state of the target model device that needs error prevention to obtain the detection result.

[0077] The embodiment of the present application can use the same set of program methods to realize error prevention detection of multiple target signal devices. There is no need to set different detection programs for different variant products. The error prevention object can be replaced by simply adjusting the standard state of the target model device. Even if the project changes later, the workload required for modification is significantly reduced. At the same time, all target model devices in this method use a unified judgment method to determine the corresponding combination of different standard states, so it can effectively ensure error prevention verification between different models.

[0078] The embodiment of the present invention discloses a specific image error prevention detection method. Compared with the previous embodiment, this embodiment further explains and optimizes the technical solution. Specifically:

[0079] In order to facilitate the processor's program processing of data information, different standard states can be assigned different standard states for the same morphological parameter, so that the states of the standard part and the measured part in the same position can be quickly compared through numerical values ​​to see whether they are consistent, without having to directly compare whether the images of the standard part and the measured part are consistent; further, all morphological parameters can be arranged into a sequence, where different morphological parameters correspond to different sequence positions in the sequence, and the target type device can generate different sequences according to the different standard states of the morphological parameters. All sequences are regarded as a sequence group including all possible models of the target type device, and each specific sequence corresponds to a specific model of device, which can be used to quickly compare whether the model of the physical device is the target model device.

[0080] Therefore, after the step of obtaining the standard image data of the standard sample set of the target type device, the step further includes:

[0081] Assign different standard values ​​to different standard states of the same morphological parameter;

[0082] Furthermore, after obtaining the standard states corresponding to all standard parts in the target model device under the target type device, the method further includes:

[0083] Fill all standard states with standard values ​​into the sequence bits of the corresponding morphological parameters to obtain the target model sequence;

[0084] Accordingly, after determining the actual states corresponding to the morphological parameters of all measured parts corresponding to the standard parts in the measured image data, the method further includes:

[0085] Fill the standard values ​​corresponding to all actual states into the sequence bits of the corresponding morphological parameters to obtain the measured sequence;

[0086] Accordingly, the process of comparing whether the actual state conforms to the standard state of the target model device includes:

[0087] Compare the measured sequence to see if it is consistent with the target model sequence;

[0088] If so, it is determined that the actual state meets the standard state of the target model device;

[0089] If not, it is determined that the actual state does not conform to the standard state of the target model device.

[0090] From the above, the method of the entire embodiment can be as follows Figure 2 As shown, including:

[0091] S11: acquiring standard image data of a standard sample group of a target type device, and assigning different standard values ​​to different standard states of the same morphological parameter;

[0092] S12: Obtain the standard states corresponding to all standard parts in the target model device under the target type device, fill all standard states into the sequence bits of the corresponding morphological parameters with standard values, and obtain the target model sequence;

[0093] S13: Acquire measured image data of the physical device;

[0094] S14: comparing the measured image data with the standard image data, determining the actual states corresponding to the morphological parameters of all measured parts corresponding to the standard parts in the measured image data, and filling the standard values ​​corresponding to all the actual states into the sequence bits of the corresponding morphological parameters to obtain a measured sequence;

[0095] S15: Compare the measured sequence to see if it is consistent with the target model sequence;

[0096] S16: If yes, then determine that the actual state meets the standard state of the target model device;

[0097] S17: If not, it is determined that the actual state does not conform to the standard state of the target model device.

[0098] Furthermore, for the assignment of standard status, considering that the program runs in binary, the standard values ​​can be set to binary numbers, or the standard value can be set to 2 N The value in base form, N is a positive integer, 2 N Not less than the maximum number of standard values ​​corresponding to each morphological parameter.

[0099] It can be understood that for a morphological parameter of a certain standard part, if there are two standard states, the two standard states can be assigned respectively by 0 / 1, and a digit on the sequence position can be assigned to the morphological parameter; if there are three standard states, three standard values ​​need to be set. These three standard values ​​can be 00 / 01 / 10 after adding digits in binary. At this time, two digits on the sequence position need to be assigned to the morphological parameter. In addition, it can also be a base number that changes the assignment principle of the overall standard state, that is, changing the assignment principle to other bases, such as decimal or 2N The preferred embodiment is binary.

[0100] It should be noted that all standard values ​​after standard state assignment are generally expressed in the same base, so that a sequence of complete numerical values ​​can be formed. The base of the standard value is generally determined during the initial configuration of the program. During subsequent operation, if there are adjustments to standard parts, morphological parameters, and standard states, the base will generally not be changed, only the corresponding numerical value will be increased. When the number of digits of the numerical value exceeds the number of digits corresponding to the current morphological parameter, the digits of the morphological parameter can be increased.

[0101] Specifically, still taking the five buttons in the switch unit of the target type device as standard parts as an example, assuming that its morphological parameter is color, the standard states include black and white, and the corresponding standard values ​​after assignment are 0 and 1 respectively, and the morphological parameter occupies only one position in the sequence; the target model device can select the standard states of the five buttons as white, black, white, black, and white, then the target model sequence is 10101; obtain the measured image data of the physical device and compare it with the standard image data, and determine that the actual states of the five buttons of the physical part are white, black, black, black, and white, that is, the measured sequence is 10001, and then compare the actual states with the standard states of the target model device, it can be found that the actual state of the third button does not meet the standard state of the target model device, so it is determined that the physical device does not meet the standards of the target model device.

[0102] Furthermore, in the process of producing the device and performing error prevention detection using the current image error prevention detection method, new model devices were developed for the target type device, such as adding new standard states to the buttons of the switch unit. The added new standard states are blue and red. At this time, one digit of the morphological parameter cannot meet the four standard values, so one digit is added to the morphological parameter, and the standard states include black, white, blue, and red, and the standard values ​​are 00 / 01 / 10 / 11 respectively. It can be seen that the standard value of the original standard state has not changed, but one digit of the morphological parameter has been added, and the display method has been adjusted. This adjustment method is conducive to program adjustment during later engineering changes, and the workload is less.

[0103] Alternatively, during the process of producing the device and performing error prevention detection using the current image error prevention detection method, a new model device is developed for the target type device, such as adding new morphological parameters. The morphological parameters can correspond to the original standard parts, such as adding the morphological parameters of the existence state of the first button in the above switch unit, or they can correspond to the newly added standard parts, such as adding the morphological parameters of the sixth button and its color in the above switch unit. At this time, a new digit is added to the original sequence to represent the morphological parameter.

[0104] It should be noted that there is usually no correlation between the morphological parameters of different standard parts, while different logical relationships may exist between multiple morphological parameters of the same standard part. For example, the model, color, size, etc. of the standard part should be based on the existence of the standard part. If the standard part does not exist, the remaining morphological parameters are invalid. These logical relationships need to be adjusted and selected according to actual conditions when setting up the standard sample group, so that all possible situations can be comprehensively listed through the sequence group.

[0105] like Figure 3a and Figure 3b Two specific model devices of a certain target type device are shown, where the numbers 1-11 in the first column correspond to the number of sequence bits in each morphological parameter, and the second column 11111000000 and 11111001111 are the sequences corresponding to the specific model devices.

[0106] Furthermore, in order to display more concise and effective information, the measured sequence and target model sequence can be converted into decimal numbers for output.

[0107] In some specific embodiments, the error prevention detection program executed within the processor is based on the standard image data of the standard sample set and the target model sequence of the target type device. The standard values ​​of each morphological parameter in the standard image data can be as shown in the following example in Table 1:

[0108] Table 1: Standard value status table of a specific target type standard sample group

[0109]

[0110] It can be understood that this state table includes all target device models to be used in the target device category, namely, all target device models to be detected or error-proofed. The processor performs comparison operations based on this state table to determine whether the physical device belongs to a specific target device model, error-proof other signal devices, and locate state parameters that are inconsistent with a specific target device model. If new target device models are subsequently added, the processor only needs to update the state table, without having to re-debug the image detection program.

[0111] Furthermore, after executing the method of this embodiment, the processor can display the comparison results on a touch screen or a display, which is convenient for staff to check and analyze. The interface can be as follows: Figure 4As shown, the detection value and set value are the output results of the measured sequence and the target model sequence converted into decimal numbers respectively. The image status is the number of sequence bits in each morphological parameter. The sequence bit can also be marked in the measured image data using a box icon. The measured sequence will fill in the actual status of the specific sequence bit corresponding to each morphological parameter, and the actual status different from the target model sequence is indicated by the font or background color setting. The device status and alarm information mainly refer to the device management of the processor.

[0112] Accordingly, the present application also discloses an image error-proofing detection system, such as Figure 5 As shown, including:

[0113] A standard sample group module 1 is used to obtain standard image data of a standard sample group of a target type device, wherein the standard sample group includes a plurality of standard parts, each of the standard parts corresponds to at least one morphological parameter, and each of the morphological parameters corresponds to at least two standard states;

[0114] Target model module 2, used for obtaining the standard states corresponding to all the standard parts in the target model device under the target type device;

[0115] The measurement module 3 is used to obtain the measured image data of the physical device;

[0116] A first comparison module 4 is configured to compare the measured image data with the standard image data to determine the actual states corresponding to the morphological parameters of all measured parts corresponding to the standard parts in the measured image data;

[0117] The second comparison module 5 is used to compare whether the actual state meets the standard state of the target model device; if so, it is determined that the physical device meets the standard of the target model device; if not, it is determined that the physical device does not meet the standard of the target model device.

[0118] In some specific embodiments, each of the morphological parameters corresponds to two standard states. Accordingly, the standard sample set module 1 is specifically used to:

[0119] Acquire first image data of a first model device and second image data of a second model device; wherein the first model device and the second model device both belong to the target type device, and all the standard states of the first model device are different from all the standard states of the second model device.

[0120] In some specific embodiments, after acquiring the standard image data of the standard sample set of the target type device, the standard sample set module 1 further includes:

[0121] Assigning different standard values ​​to different standard states of the same morphological parameter;

[0122] After the target signal module 2 obtains the standard states corresponding to all the standard parts in the target model device under the target type device, the target signal module 2 further includes:

[0123] Filling all the standard states with the standard values ​​into the sequence bits corresponding to the morphological parameters to obtain a target model sequence;

[0124] Accordingly, after the first comparison module 4 determines the actual states corresponding to the morphological parameters of all measured parts corresponding to the standard parts in the measured image data, the first comparison module 4 further includes:

[0125] Filling the standard values ​​corresponding to all the actual states into the sequence bits corresponding to the morphological parameters to obtain a measured sequence;

[0126] Accordingly, the process of the second comparison module 5 comparing whether the actual state conforms to the standard state of the target model device includes:

[0127] Comparing whether the measured sequence is consistent with the target model sequence;

[0128] If so, determining that the actual state meets the standard state of the target model device;

[0129] If not, it is determined that the actual state does not conform to the standard state of the target model device.

[0130] In some specific embodiments, the standard values ​​are all binary numbers.

[0131] In some specific embodiments, before the second comparison module 5 compares whether the measured sequence is consistent with the target model sequence, it further includes:

[0132] The measured sequence and the target model sequence are converted into decimal numbers.

[0133] In some specific embodiments, the standard value is 2 N The value in base form, N is a positive integer, 2 N Not less than the maximum number of the standard values ​​corresponding to each of the morphological parameters.

[0134] In some specific embodiments, when it is determined that the physical device does not meet the criteria of the target model device, the second comparison module 5 is further configured to:

[0135] The measured parts and the corresponding morphological parameters in the physical device that do not conform to the target signal device are marked.

[0136] In this embodiment, there is no need to set up different detection procedures for different product variants. The error-proofing object can be replaced by simply adjusting the standard state of the target model device. Even if the project changes at a later stage, the workload required for modification is significantly reduced. At the same time, all target model devices in this method use a unified judgment method to determine the corresponding combinations of different standard states, thereby effectively ensuring error-proofing verification between different models.

[0137] Accordingly, an embodiment of the present application further discloses an electronic device, including:

[0138] memory for storing computer programs;

[0139] A processor is used to implement the steps of the image error prevention detection method as described in any one of the above items when executing the computer program.

[0140] Correspondingly, an embodiment of the present application further discloses a readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the image error prevention detection method as described in any one of the above items are implemented.

[0141] For details about the image error-proofing detection method, please refer to the relevant description in the above embodiment, which will not be repeated here.

[0142] Among them, the electronic device and the readable storage medium in this embodiment have the same technical effects as the image error prevention detection method in the above embodiment, and will not be repeated here.

[0143] Finally, it should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or device comprising the element.

[0144] The above is a detailed introduction to the image error-proofing detection method, system, electronic device and readable storage medium provided by the present invention. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the ideas of the present invention, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. An image error-proofing detection method, characterized in that: include: Acquire standard image data of a standard sample set of a target type device, wherein the standard sample set includes a plurality of standard parts, each of the standard parts corresponds to at least one morphological parameter, and each of the morphological parameters corresponds to at least two standard states; Obtaining the standard states corresponding to all the standard parts in the target model device under the target type device; wherein the standard state of each standard part in the target model device is determined according to the error-proofing detection target; Acquiring measured image data of a physical device; Comparing the measured image data with the standard image data to determine the actual states corresponding to the morphological parameters of all measured parts in the measured image data that correspond one by one to the standard parts, wherein by comparing the measured image data with the standard image data, each measured part in the measured image data is standardly positioned, and the standard state to which each morphological parameter of the measured part is closest is determined as the actual state; comparing whether the actual state conforms to the standard state of the target model device; If so, determining that the physical device meets the standards of the target model device; If not, determining that the physical device does not meet the standards of the target model device; After obtaining the standard image data of the standard sample set of the target type device, the method further includes: Assigning different standard values ​​to different standard states of the same morphological parameter; After obtaining the standard states corresponding to all the standard parts in the target model device under the target type device, the method further includes: Filling all the standard states with the standard values ​​into the sequence bits corresponding to the morphological parameters to obtain a target model sequence; Accordingly, after determining the actual states corresponding to the morphological parameters of all measured parts corresponding to the standard parts one by one in the measured image data, the method further includes: Filling the standard values ​​corresponding to all the actual states into the sequence bits corresponding to the morphological parameters to obtain a measured sequence; Accordingly, the process of comparing whether the actual state conforms to the standard state of the target model device includes: Comparing whether the measured sequence is consistent with the target model sequence; If so, determining that the actual state meets the standard state of the target model device; If not, it is determined that the actual state does not conform to the standard state of the target model device.

2. The image error-proofing detection method according to claim 1, characterized in that: Each of the morphological parameters corresponds to the two standard states. Accordingly, the process of obtaining standard image data of a standard sample set of target type devices includes: Acquire first image data of a first model device and second image data of a second model device; wherein the first model device and the second model device both belong to the target type device, and all the standard states of the first model device are different from all the standard states of the second model device.

3. The image error-proofing detection method according to claim 1, characterized in that: The standard values ​​are all binary numbers.

4. The image error-proofing detection method according to claim 3, characterized in that: Also includes: The measured sequence and the target model sequence are converted into decimal numbers and output.

5. The image error-proofing detection method according to claim 1, characterized in that: The standard value is 2 N The value in base form, N is a positive integer, 2 N Not less than the maximum number of the standard values ​​corresponding to each of the morphological parameters.

6. The image error-proofing detection method according to any one of claims 1 to 5, characterized in that: When it is determined that the physical device does not meet the standards of the target model device, the method further includes: The measured parts and the corresponding morphological parameters in the physical device that do not conform to the target model device are marked.

7. An image error-proofing detection system, characterized in that: include: A standard sample group module is used to obtain standard image data of a standard sample group of a target type device, wherein the standard sample group includes a plurality of standard parts, each of the standard parts corresponds to at least one morphological parameter, and each of the morphological parameters corresponds to at least two standard states; A target model module is configured to obtain the standard states corresponding to all the standard parts in the target model device under the target type device; wherein the standard state of each standard part in the target model device is determined according to an error-proofing detection target; A measurement module, used to obtain measured image data of a physical device; a first comparison module, configured to compare the measured image data with the standard image data, and determine the actual states corresponding to the morphological parameters of all measured parts in the measured image data that correspond one by one to the standard parts, wherein by comparing the measured image data with the standard image data, each measured part in the measured image data is standardly positioned, and the standard state to which each morphological parameter of the measured part is closest is determined as the actual state; a second comparison module, configured to compare whether the actual state conforms to the standard state of the target model device; if so, determining that the physical device conforms to the standard of the target model device; if not, determining that the physical device does not conform to the standard of the target model device; After acquiring the standard image data of the standard sample set of the target type device, the standard sample set module further includes: Assigning different standard values ​​to different standard states of the same morphological parameter; After the target model module obtains the standard states corresponding to all the standard parts in the target model device under the target type device, the method further includes: Filling all the standard states with the standard values ​​into the sequence bits corresponding to the morphological parameters to obtain a target model sequence; Accordingly, after the first comparison module determines the actual states corresponding to the morphological parameters of all measured parts corresponding to the standard parts in the measured image data, the first comparison module further includes: Filling the standard values ​​corresponding to all the actual states into the sequence bits corresponding to the morphological parameters to obtain a measured sequence; Accordingly, the process of the second comparison module comparing whether the actual state conforms to the standard state of the target model device includes: Comparing whether the measured sequence is consistent with the target model sequence; If so, determining that the actual state meets the standard state of the target model device; If not, it is determined that the actual state does not conform to the standard state of the target model device.

8. An electronic device, characterized in that: include: memory for storing computer programs; A processor, configured to implement the steps of the image error-proofing detection method according to any one of claims 1 to 6 when executing the computer program.

9. A readable storage medium, characterized in that: The readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the image error prevention detection method according to any one of claims 1 to 6 are implemented.

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