CN109580632B - Defect determination method, device and storage medium - Google Patents
Defect determination method, device and storage medium Download PDFInfo
- Publication number
- CN109580632B CN109580632B CN201811413017.4A CN201811413017A CN109580632B CN 109580632 B CN109580632 B CN 109580632B CN 201811413017 A CN201811413017 A CN 201811413017A CN 109580632 B CN109580632 B CN 109580632B
- Authority
- CN
- China
- Prior art keywords
- scale value
- gray
- gray scale
- area
- comparison
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
- G01N2021/8854—Grading and classifying of flaws
- G01N2021/8874—Taking dimensions of defect into account
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
- G01N2021/8887—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques
Abstract
The embodiment of the invention provides a defect determining method, a defect determining device and a storage medium, wherein the defect determining method comprises the following steps: acquiring a first gray scale value corresponding to a target area of a sample to be detected after a first process and a second gray scale value corresponding to a comparison area; acquiring a third gray scale value corresponding to the target area and a fourth gray scale value corresponding to the comparison area after the sample to be detected passes through a second process, wherein the second process is the next process of the first process; and determining whether the target area is a defect area according to the first gray scale value, the second gray scale value, the third gray scale value and the fourth gray scale value. The defect determining method of the embodiment of the invention can remove the influence of the front-layer process graph on the gray scale value of the sample to be detected in the prior art, reduce the fluctuation range of the gray scale difference value, and can realize that the misjudgment rate of the defect area is controlled within an acceptable range under a stricter threshold condition, thereby improving the accuracy and the detection rate of AOI equipment and calculating the size of the defect area more accurately.
Description
Technical Field
The present invention relates to the field of optical inspection, and in particular, to a defect determination method and apparatus, and a storage medium.
Background
Currently, AOI (Automatic optical Inspection) equipment is an important Inspection tool and process quality control tool for ensuring product quality in the electronic manufacturing industry, and the work flow of the AOI equipment is as follows: the sample to be detected enters the device → the sample to be detected is scanned, a gray scale map shown in fig. 1 is obtained, meanwhile, gray scale values (shown in fig. 2) corresponding to all the areas in fig. 1 are obtained through the gray scale map, the gray scale values shown in fig. 2 are screened and compared to calculate the information of the defects shown in fig. 3 or fig. 4 → the defects are photographed → image and data are uploaded → the device for removing the sample to be detected. With continued reference to fig. 3, 33 regions are labeled as defective regions, but not all of these defective regions have real defects, resulting in a reduced detection accuracy of the AOI device.
Disclosure of Invention
In order to solve the above technical problem, embodiments of the present invention provide a defect determining method, apparatus and storage medium, so as to solve the problem of low detection accuracy of the existing AOI device.
According to an aspect of an embodiment of the present invention, there is provided a defect determining method including:
acquiring a first gray scale value corresponding to a target area of a sample to be detected after a first process and a second gray scale value corresponding to a comparison area;
obtaining a third gray scale value corresponding to the target area and a fourth gray scale value corresponding to the comparison area after a sample to be detected passes through a second process, wherein the second process is the next process of the first process;
and determining whether the target area is a defective area or not according to the first gray scale value, the second gray scale value, the third gray scale value and the fourth gray scale value.
Optionally, the determining whether the target area is a defective area according to the first gray scale value, the second gray scale value, the third gray scale value, and the fourth gray scale value includes:
determining a target gray scale value corresponding to the target area according to the first gray scale value and the third gray scale value;
determining a comparison gray level value corresponding to the comparison area according to the second gray level value and the fourth gray level value;
judging whether the absolute value of the difference between the comparison gray-scale value and the target gray-scale value is greater than a preset threshold value or not;
if the absolute value of the difference between the comparison gray-scale value and the target gray-scale value is greater than a preset threshold value, determining that the target area is a defective area;
and if the absolute value of the difference between the comparison gray-scale value and the target gray-scale value is less than or equal to a preset threshold value, determining that the target area is not a defect area.
Optionally, the determining a target gray scale value corresponding to the target area according to the first gray scale value and the third gray scale value includes:
and determining a difference value obtained by subtracting the first gray-scale value from the third gray-scale value as a target gray-scale value corresponding to the target area.
Optionally, the determining, according to the second gray scale value and the fourth gray scale value, a comparison gray scale value corresponding to the comparison area includes:
and determining a difference value obtained by subtracting the second gray scale value from the fourth gray scale value as a comparison gray scale value corresponding to the comparison area.
According to another aspect of the embodiments of the present invention, there is also provided a defect determining apparatus including:
the first acquisition module is used for acquiring a first gray scale value corresponding to a target area of a sample to be detected after a first process and a second gray scale value corresponding to a comparison area;
the second acquisition module is used for acquiring a third gray scale value corresponding to the target area and a fourth gray scale value corresponding to the comparison area after the sample to be detected passes through a second process, and the second process is the next process of the first process;
and the determining module is used for determining whether the target area is a defect area according to the first gray scale value, the second gray scale value, the third gray scale value and the fourth gray scale value.
Optionally, the determining module includes:
the first determining unit is used for determining a target gray scale value corresponding to the target area according to the first gray scale value and the third gray scale value;
the second determining unit is used for determining a comparison gray level value corresponding to the comparison area according to the second gray level value and the fourth gray level value;
the judging unit is used for judging whether the absolute value of the difference value between the comparison gray-scale value and the target gray-scale value is larger than a preset threshold value or not;
a third determining unit, configured to determine that the target area is a defective area if an absolute value of a difference between the comparison gray scale value and the target gray scale value is greater than a preset threshold;
a fourth determining unit, configured to determine that the target area is not a defective area if an absolute value of a difference between the comparison gray-scale value and the target gray-scale value is less than or equal to a preset threshold.
Optionally, the first determining unit includes:
and the first determining subunit is configured to determine, as the target gray-scale value corresponding to the target area, a difference obtained by subtracting the first gray-scale value from the third gray-scale value.
Optionally, the second determining unit includes:
and the second determining subunit is configured to determine a difference obtained by subtracting the second gray-scale value from the fourth gray-scale value as a comparison gray-scale value corresponding to the comparison area.
According to still another aspect of the embodiments of the present invention, there is also provided a defect determining apparatus including: a processor, a memory and a program stored on the memory and executable on the processor, which program, when executed by the processor, carries out the steps of the defect determination method as described above.
According to still another aspect of embodiments of the present invention, there is also provided a computer-readable storage medium storing thereon a program which, when executed by a processor, implements the steps of the defect determination method as described above.
The embodiment of the invention has the following beneficial effects:
in the embodiment of the invention, whether the target area is the defect area is determined according to the first gray scale value corresponding to the target area after the first process and the second gray scale value corresponding to the comparison area, and the third gray scale value corresponding to the target area after the second process and the fourth gray scale value corresponding to the comparison area, so that the influence of the front-layer process graph on the gray scale value of the sample to be detected of the existing process can be removed, the fluctuation range of the gray scale difference value is reduced, the misjudgment rate of the defect area can be controlled within an acceptable range under a stricter threshold condition, the accuracy and the detection rate of the AOI equipment are improved, and the size of the defect area can be calculated more accurately.
Drawings
FIG. 1 is a gray scale diagram of a sample to be tested according to an embodiment of the present invention;
FIG. 2 is a table of gray scale values obtained by testing a sample to be tested according to an embodiment of the present invention;
FIG. 3 is a distribution diagram of defect regions obtained by a prior art algorithm;
FIG. 4 is a schematic diagram of a three-dimensional distribution of defect regions obtained by a prior art algorithm;
FIG. 5 is a flowchart illustrating a defect determination method according to an embodiment of the present invention;
FIG. 6 is a flowchart illustrating another defect determining method according to an embodiment of the invention;
FIG. 7 is a second gray scale diagram corresponding to a sample to be tested according to the embodiment of the present invention;
FIG. 8 is a second gray scale table obtained by testing a sample to be tested according to an embodiment of the present invention;
FIG. 9 is a distribution diagram of a defect region obtained by a defect determining method according to an embodiment of the present invention;
fig. 10 is a schematic diagram of a three-dimensional distribution of defect regions obtained by the defect determining method of the embodiment of the present invention;
FIG. 11 is a schematic structural diagram of a defect determining apparatus according to an embodiment of the present invention;
fig. 12 is a schematic structural diagram of another defect determining apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the technical problems, technical solutions and advantages of the present invention more apparent, the following detailed description is given with reference to the accompanying drawings and specific embodiments.
The terms first, second and the like in the description and in the claims of the present invention are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are, for example, capable of operation in sequences other than those illustrated or otherwise described herein.
The prior art is to compare the gray scale values of the samples to be detected directly by cycles, for example: the difference between the gray scale values of the region to be detected and the adjacent region thereof can be used as a judgment condition, when the difference between the gray scale values of the region to be detected and the adjacent region thereof is greater than a preset threshold value, the region to be detected is marked as a defective region, and the size of the defective region is calculated. The area continuously higher than the preset threshold value in a certain range is marked as a defect area, and the size of the defect area is determined by the size of the continuous area.
A certain area is marked as a defect area between the transition area of the real defect and the normal area, so that the size of the AOI detected defect is slightly larger than that of the real defect. This phenomenon may be affected by the fluctuation of the gray scale difference itself of the area without real defects, and the larger the fluctuation, the larger the difference between the measured size and the real size. However, in the existing algorithm logic, the gray scale difference value fluctuation between the region to be detected and the adjacent region is very large (as shown in fig. 4), which will seriously affect the accuracy of defect detection.
Next, the reason why the detection accuracy of the AOI device is low is analyzed by taking the manufacturing process of the array substrate as an example. The array substrate is composed of a multi-layer structure and is obtained by depositing and etching one layer by one layer. In the manufacturing process of the Array substrate, the pattern of the front process can cause certain influence on the gray scale pattern of the product of the back process, and in the LPTS/OLED Array process, the influence is particularly prominent due to the complex process flow, the complex pattern design and the dense arrangement. Since the defect detection result of the current process is affected by the previous process pattern to a certain extent, the calibrated defect regions have differences and very large fluctuation, which causes the position and size of the defect region to be inaccurate, as shown in fig. 3 and 4.
Based on the above analysis, fig. 5 is a flowchart of a defect determining method provided in an embodiment of the present invention, and referring to fig. 5, the defect determining method includes:
step 501: acquiring a first gray scale value corresponding to a target area of a sample to be detected after a first process and a second gray scale value corresponding to a comparison area;
in the embodiment of the present invention, the target region refers to an image region (e.g., a grayscale image) obtained by scanning a region to be detected of the sample to be detected by an AOI device, and the target region may be a region corresponding to one or more pixels. The first gray scale value refers to the size of the gray scale value of the image area corresponding to the target area after the first process.
In the embodiment of the present invention, the comparison region and the target region may be adjacent regions with equal size, and it can be understood that the comparison region is an image region with equal size obtained by scanning the adjacent regions of the to-be-detected region of the to-be-detected sample through an AOI device, for example: with continued reference to fig. 1, the region 11 is a target region of the sample to be detected after the first process, the region 12 is a comparison region of the sample to be detected after the first process, and the region 11 and the region 12 are adjacent regions with equal size. The second gray scale value refers to the gray scale value of the image data corresponding to the comparison area after the first process.
It should be noted that the above description of the target region and the comparison region is only an example and is not limiting.
Step 502: obtaining a third gray scale value corresponding to the target area and a fourth gray scale value corresponding to the comparison area after a sample to be detected passes through a second process, wherein the second process is the next process of the first process;
taking the array substrate as an example, the array substrate is composed of multiple layers, the first process may be a process of depositing an nth layer structure on the array substrate, and the second process may be a process of depositing an N +1 th layer structure on the array substrate.
It should be noted that the above description of the first process and the second process is only an example and is not limiting.
In an embodiment of the disclosure, the third grayscale value is a grayscale value of the image data corresponding to the target region after the second process, and the fourth grayscale value is a grayscale value of the image data corresponding to the comparison region after the second process.
Step 503: and determining whether the target area is a defective area or not according to the first gray scale value, the second gray scale value, the third gray scale value and the fourth gray scale value.
For example: when the first gray scale value, the second gray scale value, the third gray scale value and the fourth gray scale value meet the following conditions, determining the target area as a defect area:
(third gray scale value-first gray scale value) - (fourth gray scale value-second gray scale value) | > preset threshold
In the embodiment of the invention, the gray scale difference value fluctuation caused by partial pre-process defects can be eliminated by making a difference between the gray scale values of the pre-process and the gray scale values of the post-process, so that the misjudged defect area is not judged as the defect area, and the misjudged defect area can be filtered.
It should be noted that, there may be a plurality of manners for determining the target area, and the above description on the manner for determining the target area is only one of a plurality of priority manners, and it should be understood that the embodiment of the present invention does not specifically limit the manner for determining the target area.
In the embodiment of the invention, whether the target area is the defect area is determined according to the first gray scale value corresponding to the target area after the first process and the second gray scale value corresponding to the comparison area, and the third gray scale value corresponding to the target area after the second process and the fourth gray scale value corresponding to the comparison area, so that the influence of the front-layer process graph on the gray scale value of the sample to be detected of the existing process can be removed, the fluctuation range of the gray scale difference value is reduced, the misjudgment rate of the defect area can be controlled within an acceptable range under a stricter threshold condition, the accuracy and the detection rate of the AOI equipment are improved, and the size of the defect area can be calculated more accurately.
Fig. 6 is a flowchart of a defect determining method according to an embodiment of the present invention, and referring to fig. 6, the defect determining method includes:
step 601: acquiring a first gray scale value corresponding to a target area of a sample to be detected after a first process and a second gray scale value corresponding to a comparison area;
in the embodiment of the present invention, the implementation principle of step 601 is the same as that of step 501, and the description of the similar parts is omitted.
Step 602: obtaining a third gray scale value corresponding to the target area and a fourth gray scale value corresponding to the comparison area after a sample to be detected passes through a second process, wherein the second process is the next process of the first process;
in the embodiment of the present invention, the implementation principle of step 602 is the same as that of step 502, and the description of the similar parts is omitted.
Step 603: determining a target gray scale value corresponding to the target area according to the first gray scale value and the third gray scale value;
in this embodiment of the present invention, a difference obtained by subtracting the first grayscale value from the third grayscale value may be determined as a target grayscale value corresponding to the target region.
Step 604: determining a comparison gray level value corresponding to the comparison area according to the second gray level value and the fourth gray level value;
in this embodiment of the present invention, a difference obtained by subtracting the second gray scale value from the fourth gray scale value may be determined as the comparison gray scale value corresponding to the comparison area.
Step 605: judging whether the absolute value of the difference between the comparison gray-scale value and the target gray-scale value is greater than a preset threshold value or not; if the absolute value of the difference between the comparison gray scale value and the target gray scale value is greater than the preset threshold, step 606 is executed, and if the absolute value of the difference between the comparison gray scale value and the target gray scale value is less than or equal to the preset threshold, step 607 is executed.
For example: fig. 1 shows a gray scale diagram corresponding to the target area 11 and the comparison area 12 after the second process, and further, the gray scale values of the areas corresponding to fig. 1 can be obtained, as shown in fig. 2, where the numerical value in the left box is the third gray scale value corresponding to the target area, and the numerical value in the right box is the fourth gray scale value corresponding to the comparison area. Fig. 2 shows a gray scale diagram corresponding to the target region 11 and the comparison region 12 after the first process, and a first gray scale value corresponding to the target region 11 and a second gray scale value corresponding to the comparison region 12 after the first process can be obtained according to the gray scale diagram shown in fig. 2. According to the data shown in fig. 1, 2, 3, and 7, and by using the step 603, the target gray-scale value and the comparison gray-scale value can be calculated, as shown in fig. 8, the data in the left-side box in fig. 8 is the target gray-scale value corresponding to the target area, the data in the right-side box in fig. 8 is the comparison gray-scale value corresponding to the comparison area, and the difference between the target gray-scale value and the comparison gray-scale value is obtained, so as to obtain the data shown in fig. 9 and 10. If the preset threshold is set to 15, only one area in fig. 9 and 10 is a defective area, the number of misjudgments of the defective area is greatly reduced, and the accuracy of the equipment is greatly improved.
If the preset threshold value is adjusted from 15 to 8, the number of misjudgments at this time is 32, which is consistent with the existing algorithm logic. However, the reduction of the preset threshold value can judge the real defect that the difference of the gray level values is between 8 and 15, so that the detection rate of the equipment is effectively improved.
And as can be seen by comparing fig. 4 and fig. 10, the fluctuation of fig. 10 becomes smaller compared with that of fig. 4, it can be understood that the defect determining method of the embodiment of the present invention has high accuracy and small fluctuation compared with the existing defect determining method, the number of misjudgments of the defect area is greatly reduced, and the accuracy of the apparatus is greatly improved.
In the embodiment of the invention, the preset threshold value can be adjusted according to the actual condition, and an optimal preset threshold value can be selected in the actual application process, so that the accuracy and the detection rate of the equipment are synchronously improved. It should be noted that, the size of the preset threshold is not specifically limited in the embodiments of the present invention.
Step 606: if the absolute value of the difference between the comparison gray-scale value and the target gray-scale value is greater than a preset threshold value, determining that the target area is a defective area;
in the embodiment of the invention, an area continuously higher than the preset threshold value in a certain range is marked as a defective area, and the size of the defective area is determined by the size of the continuous area.
Step 607: and if the absolute value of the difference between the comparison gray-scale value and the target gray-scale value is less than or equal to a preset threshold value, determining that the target area is not a defect area.
In the embodiment of the invention, a difference is made between the first gray scale value and the third gray scale value to obtain a target gray scale value, a difference is made between the second gray scale value and the fourth gray scale value to obtain a comparison gray scale value, and then the defect area is obtained by comparing the target gray scale value with the comparison gray scale value. Firstly, gray scale difference value fluctuation caused by partial pre-process defects can be eliminated by making difference between gray scale values of the pre-process and the post-process, and the misjudged defect area can be filtered. The influence of the front-layer process graph on the gray scale value of the sample to be detected in the prior art can be removed, the fluctuation range of the gray scale difference value is reduced, the misjudgment rate of the defect area can be controlled within an acceptable range under a stricter threshold value condition, the accuracy and the detection rate of the AOI equipment are improved, and the size of the defect area can be calculated more accurately.
In order to solve the problem of low detection accuracy of the existing AOI device, the embodiment of the present invention further provides a defect determining apparatus, and since the principle of solving the problem by the defect determining apparatus is similar to the defect determining method in the embodiment of the present invention, the implementation of the defect determining apparatus can refer to the implementation of the method, and the repeated parts are not repeated.
Referring to fig. 11, an embodiment of the present invention further provides a defect determining apparatus 1100, including:
the first obtaining module 1101 is configured to obtain a first gray scale value corresponding to a target region of a sample to be detected after a first process and a second gray scale value corresponding to a comparison region;
a second obtaining module 1102, configured to obtain a third gray scale value corresponding to the target region and a fourth gray scale value corresponding to the comparison region after the sample to be detected undergoes a second process, where the second process is a next process of the first process;
a determining module 1103, configured to determine whether the target area is a defective area according to the first gray scale value, the second gray scale value, the third gray scale value, and the fourth gray scale value.
Optionally, the determining module 1103 includes:
the first determining unit is used for determining a target gray scale value corresponding to the target area according to the first gray scale value and the third gray scale value;
the second determining unit is used for determining a comparison gray level value corresponding to the comparison area according to the second gray level value and the fourth gray level value;
the judging unit is used for judging whether the absolute value of the difference value between the comparison gray-scale value and the target gray-scale value is larger than a preset threshold value or not;
a third determining unit, configured to determine that the target area is a defective area if an absolute value of a difference between the comparison gray scale value and the target gray scale value is greater than a preset threshold;
a fourth determining unit, configured to determine that the target area is not a defective area if an absolute value of a difference between the comparison gray-scale value and the target gray-scale value is less than or equal to a preset threshold.
Optionally, the first determining unit includes:
and the first determining subunit is configured to determine, as the target gray-scale value corresponding to the target area, a difference obtained by subtracting the first gray-scale value from the third gray-scale value.
Optionally, the second determining unit includes:
and the second determining subunit is configured to determine a difference obtained by subtracting the second gray-scale value from the fourth gray-scale value as a comparison gray-scale value corresponding to the comparison area.
It should be noted that the defect determining apparatus provided in the embodiment of the present invention can implement each process in the method embodiments of fig. 5 to fig. 6, and the implementation principle and the technical effect are similar, which are not described herein again.
Fig. 12 is a schematic structural diagram of a defect determining apparatus according to another embodiment of the present invention. As shown in fig. 12, the defect determining apparatus 1200 shown in fig. 12 includes: at least one processor 1201, a memory 1202. The various components in defect determination apparatus 1200 are coupled together by a bus system 1205. It is understood that bus system 1205 is used to enable connected communication between these components. Bus system 1205 includes, in addition to a data bus, a power bus, a control bus, and a status signal bus. But for clarity of illustration the various buses are labeled as bus system 1205 in figure 12.
It is to be understood that the memory 1202 in embodiments of the present invention may be either volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The non-volatile Memory may be a Read-Only Memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable PROM (EEPROM), or a flash Memory. Volatile Memory can be Random Access Memory (RAM), which acts as external cache Memory. By way of illustration and not limitation, many forms of RAM are available, such as Static random access memory (Static RAM, SRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic random access memory (Synchronous DRAM, SDRAM), Double Data Rate Synchronous Dynamic random access memory (ddr Data Rate SDRAM, ddr SDRAM), Enhanced Synchronous SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), and Direct Rambus RAM (DRRAM). The memory 1202 of the subject systems and methods is intended to comprise, without being limited to, these and any other suitable types of memory.
In some embodiments, memory 1202 stores the following elements, executable modules or data structures, or a subset thereof, or an expanded set thereof: an operating system 12021 and application programs 12022.
The operating system 12021 includes various system programs, such as a framework layer, a core library layer, a driver layer, and the like, and is used for implementing various basic services and processing hardware-based tasks. The application 12022 contains various applications such as a Media Player (Media Player), a Browser (Browser), and the like, and is used to implement various application services. A program implementing a method according to an embodiment of the present invention may be included in the application 12022.
In the embodiment of the present invention, the processor 1201 may execute the defect determining method by calling a program or an instruction stored in the memory 1202, specifically, a program or an instruction stored in the application program 12022.
The method disclosed by the embodiment of the invention can be applied to the processor 1201 or implemented by the processor 1201. The processor 1201 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be implemented by integrated logic circuits of hardware or instructions in the form of software in the processor 1201. The Processor 1201 may be a general-purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, or discrete hardware components. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in the memory 1202, and the processor 1201 reads information in the memory 1202 and completes the steps of the above method in combination with hardware thereof.
It is to be understood that the embodiments described herein may be implemented in hardware, software, firmware, middleware, microcode, or any combination thereof. For a hardware implementation, the Processing units may be implemented within one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), general purpose processors, controllers, micro-controllers, microprocessors, other electronic units designed to perform the functions described herein, or a combination thereof.
For a software implementation, the techniques described in this disclosure may be implemented with modules (e.g., procedures, functions, and so on) that perform the functions described in this disclosure. The software codes may be stored in a memory and executed by a processor. The memory may be implemented within the processor or external to the processor.
In this embodiment, the processor 1201 is specifically configured to: acquiring a first gray scale value corresponding to a target area of a sample to be detected after a first process and a second gray scale value corresponding to a comparison area; obtaining a third gray scale value corresponding to the target area and a fourth gray scale value corresponding to the comparison area after a sample to be detected passes through a second process, wherein the second process is the next process of the first process; and determining whether the target area is a defective area or not according to the first gray scale value, the second gray scale value, the third gray scale value and the fourth gray scale value.
An embodiment of the present invention further provides a computer-readable storage medium, on which a program is stored, where the program, when executed by a processor, implements the steps in the defect determining method described above.
It should be appreciated that reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, the appearances of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
In various embodiments of the present invention, it should be understood that the sequence numbers of the above-mentioned processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.
In the embodiments provided herein, it should be understood that "B corresponding to a" means that B is associated with a from which B can be determined. It should also be understood that determining B from a does not mean determining B from a alone, but may be determined from a and/or other information.
In the several embodiments provided in the present application, it should be understood that the disclosed method and apparatus may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be physically included alone, or two or more units may be integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network-side device) to perform some steps of the transceiving method according to various embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (8)
1. A method of defect determination, comprising:
acquiring a first gray scale value corresponding to a target area of a sample to be detected after a first process and a second gray scale value corresponding to a comparison area;
obtaining a third gray scale value corresponding to the target area and a fourth gray scale value corresponding to the comparison area after a sample to be detected passes through a second process, wherein the second process is the next process of the first process;
determining whether the target area is a defect area according to the first gray scale value, the second gray scale value, the third gray scale value and the fourth gray scale value;
determining whether the target area is a defect area according to the first gray scale value, the second gray scale value, the third gray scale value and the fourth gray scale value, including:
determining a target gray scale value corresponding to the target area according to the first gray scale value and the third gray scale value;
determining a comparison gray level value corresponding to the comparison area according to the second gray level value and the fourth gray level value;
judging whether the absolute value of the difference between the comparison gray-scale value and the target gray-scale value is greater than a preset threshold value or not;
if the absolute value of the difference between the comparison gray-scale value and the target gray-scale value is greater than a preset threshold value, determining that the target area is a defective area;
and if the absolute value of the difference between the comparison gray-scale value and the target gray-scale value is less than or equal to a preset threshold value, determining that the target area is not a defect area.
2. The method according to claim 1, wherein determining the target gray scale value corresponding to the target area according to the first gray scale value and the third gray scale value comprises:
and determining a difference value obtained by subtracting the first gray-scale value from the third gray-scale value as a target gray-scale value corresponding to the target area.
3. The method according to claim 1 or 2, wherein the determining a comparison gray scale value corresponding to the comparison area according to the second gray scale value and the fourth gray scale value comprises:
and determining a difference value obtained by subtracting the second gray scale value from the fourth gray scale value as a comparison gray scale value corresponding to the comparison area.
4. A defect determining apparatus, comprising:
the first acquisition module is used for acquiring a first gray scale value corresponding to a target area of a sample to be detected after a first process and a second gray scale value corresponding to a comparison area;
the second acquisition module is used for acquiring a third gray scale value corresponding to the target area and a fourth gray scale value corresponding to the comparison area after the sample to be detected passes through a second process, and the second process is the next process of the first process;
a determining module, configured to determine whether the target area is a defective area according to the first gray scale value, the second gray scale value, the third gray scale value, and the fourth gray scale value;
the determining module comprises:
the first determining unit is used for determining a target gray scale value corresponding to the target area according to the first gray scale value and the third gray scale value;
the second determining unit is used for determining a comparison gray level value corresponding to the comparison area according to the second gray level value and the fourth gray level value;
the judging unit is used for judging whether the absolute value of the difference value between the comparison gray-scale value and the target gray-scale value is larger than a preset threshold value or not;
a third determining unit, configured to determine that the target area is a defective area if an absolute value of a difference between the comparison gray scale value and the target gray scale value is greater than a preset threshold;
a fourth determining unit, configured to determine that the target area is not a defective area if an absolute value of a difference between the comparison gray-scale value and the target gray-scale value is less than or equal to a preset threshold.
5. The defect determination apparatus according to claim 4, wherein the first determination unit includes:
and the first determining subunit is configured to determine, as the target gray-scale value corresponding to the target area, a difference obtained by subtracting the first gray-scale value from the third gray-scale value.
6. The defect determination apparatus according to claim 4 or 5, wherein the second determination unit includes:
and the second determining subunit is configured to determine a difference obtained by subtracting the second gray-scale value from the fourth gray-scale value as a comparison gray-scale value corresponding to the comparison area.
7. A defect determining apparatus, comprising: processor, memory and program stored on the memory and executable on the processor, which program, when executed by the processor, carries out the steps of the defect determination method as claimed in any one of claims 1 to 3.
8. A computer-readable storage medium, characterized in that a program is stored on the computer-readable storage medium, which program, when being executed by a processor, carries out the steps of the defect determination method as set forth in any one of claims 1 to 3.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811413017.4A CN109580632B (en) | 2018-11-23 | 2018-11-23 | Defect determination method, device and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811413017.4A CN109580632B (en) | 2018-11-23 | 2018-11-23 | Defect determination method, device and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109580632A CN109580632A (en) | 2019-04-05 |
| CN109580632B true CN109580632B (en) | 2021-03-30 |
Family
ID=65924571
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811413017.4A Active CN109580632B (en) | 2018-11-23 | 2018-11-23 | Defect determination method, device and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109580632B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110517318B (en) * | 2019-08-28 | 2022-05-17 | 昆山国显光电有限公司 | Positioning method and device, and storage medium |
| CN110987945B (en) * | 2019-12-24 | 2023-03-28 | 合肥维信诺科技有限公司 | Defect detection method, defect detection device and detection method of touch display panel |
| CN114022059B (en) * | 2022-01-06 | 2022-05-27 | 锱云(上海)物联网科技有限公司 | Method, system, terminal device and storage medium for analyzing bad reason of product |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1400922A1 (en) * | 2002-09-20 | 2004-03-24 | Nitto Denko Corporation | Print inspection method and apparatus |
| JP2015206702A (en) * | 2014-04-22 | 2015-11-19 | キヤノン株式会社 | Image inspection method and image inspection device |
| CN107764832A (en) * | 2017-09-29 | 2018-03-06 | 青海黄河上游水电开发有限责任公司光伏产业技术分公司 | The hidden of photovoltaic module splits defect inspection method |
| CN108352063A (en) * | 2015-11-18 | 2018-07-31 | 科磊股份有限公司 | System and method for region adaptivity defects detection |
| CN108387587A (en) * | 2018-01-22 | 2018-08-10 | 京东方科技集团股份有限公司 | Defect inspection method and defect detection equipment |
| CN108734690A (en) * | 2018-03-02 | 2018-11-02 | 苏州汉特士视觉科技有限公司 | A kind of defects of vision detection device and its detection method |
-
2018
- 2018-11-23 CN CN201811413017.4A patent/CN109580632B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1400922A1 (en) * | 2002-09-20 | 2004-03-24 | Nitto Denko Corporation | Print inspection method and apparatus |
| JP2015206702A (en) * | 2014-04-22 | 2015-11-19 | キヤノン株式会社 | Image inspection method and image inspection device |
| CN108352063A (en) * | 2015-11-18 | 2018-07-31 | 科磊股份有限公司 | System and method for region adaptivity defects detection |
| CN107764832A (en) * | 2017-09-29 | 2018-03-06 | 青海黄河上游水电开发有限责任公司光伏产业技术分公司 | The hidden of photovoltaic module splits defect inspection method |
| CN108387587A (en) * | 2018-01-22 | 2018-08-10 | 京东方科技集团股份有限公司 | Defect inspection method and defect detection equipment |
| CN108734690A (en) * | 2018-03-02 | 2018-11-02 | 苏州汉特士视觉科技有限公司 | A kind of defects of vision detection device and its detection method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109580632A (en) | 2019-04-05 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109871895B (en) | Method and device for detecting defects of circuit board | |
| CN109580632B (en) | Defect determination method, device and storage medium | |
| US7801353B2 (en) | Method for defect detection using computer aided design data | |
| US9916653B2 (en) | Detection of defects embedded in noise for inspection in semiconductor manufacturing | |
| US11189019B2 (en) | Method for detecting defects, electronic device, and computer readable medium | |
| CN108896278B (en) | Optical filter silk-screen defect detection method and device and terminal equipment | |
| CN109671078B (en) | Method and device for detecting product surface image abnormity | |
| CN110969600A (en) | Product defect detection method and device, electronic equipment and storage medium | |
| CN111369492B (en) | Display screen detection method, detection device and detection system | |
| CN114677348A (en) | IC chip defect detection method and system based on vision and storage medium | |
| CN115375608A (en) | Detection method and device, detection equipment and storage medium | |
| US10241000B2 (en) | Method for checking the position of characteristic points in light distributions | |
| CN115731186A (en) | Fabric quality detection method, device, equipment and storage medium | |
| CN111709951B (en) | Target detection network training method and system, network, device and medium | |
| CN110634124A (en) | Method and equipment for area detection | |
| CN114529543A (en) | Installation detection method and device for peripheral screw gasket of aero-engine | |
| CN115375610A (en) | Detection method and device, detection equipment and storage medium | |
| Nahar et al. | Computer aided system for inspection of assembled PCB | |
| CN114757869A (en) | Product flaw detection method and computer device | |
| CN111693533A (en) | Workpiece surface quality detection method and device and appearance machine | |
| CN117129480B (en) | Intelligent detection method and device for computer main board components based on machine vision | |
| CN113658183B (en) | Workpiece quality inspection method and device and computer equipment | |
| US20220253996A1 (en) | Method, apparatus, and device for labeling images | |
| CN117350946A (en) | Printed matter surface defect detection method, device, equipment and storage medium | |
| CN110717880B (en) | Defect detection method and device and electronic equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |