CN110991082A - Mura quantification method based on excimer laser annealing - Google Patents
Mura quantification method based on excimer laser annealing Download PDFInfo
- Publication number
- CN110991082A CN110991082A CN201911318622.8A CN201911318622A CN110991082A CN 110991082 A CN110991082 A CN 110991082A CN 201911318622 A CN201911318622 A CN 201911318622A CN 110991082 A CN110991082 A CN 110991082A
- Authority
- CN
- China
- Prior art keywords
- mura
- area
- region
- light intensity
- slope
- 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.)
- Granted
Links
- 238000005224 laser annealing Methods 0.000 title claims abstract description 23
- 238000000034 method Methods 0.000 title claims abstract description 23
- 238000011002 quantification Methods 0.000 title claims abstract description 9
- 238000012545 processing Methods 0.000 claims abstract description 14
- 238000013139 quantization Methods 0.000 claims abstract description 13
- 239000000758 substrate Substances 0.000 claims abstract description 10
- 238000012417 linear regression Methods 0.000 claims description 7
- 229910021420 polycrystalline silicon Inorganic materials 0.000 abstract description 9
- 230000007547 defect Effects 0.000 abstract description 7
- 238000011156 evaluation Methods 0.000 abstract description 3
- 238000001514 detection method Methods 0.000 description 7
- 239000010408 film Substances 0.000 description 4
- 229920005591 polysilicon Polymers 0.000 description 4
- 229910021417 amorphous silicon Inorganic materials 0.000 description 2
- 238000002425 crystallisation Methods 0.000 description 2
- 230000008025 crystallization Effects 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 208000003464 asthenopia Diseases 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 239000010409 thin film Substances 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Images
Landscapes
- Investigating Or Analysing Materials By Optical Means (AREA)
- Recrystallisation Techniques (AREA)
Abstract
The invention discloses a Mura quantification method based on excimer laser annealing, which comprises the following steps: s1, under different light intensities, respectively collecting Mura images of the same region of the same substrate after excimer laser annealing; s2, performing image processing on the Mura image to determine the area of a Mura region; s3, drawing a linear relation curve of light intensity and Mura area; s4, repeating the steps S1-S3, wherein all linear relation curves drawn in the same coordinate system pass through a point G; s5, under certain light intensity, obtaining a Mura image of a selected area of the substrate to be detected, and obtaining the area of the Mura area after image processing; drawing a point A in the coordinate system according to the light intensity and the Mura area; s6, connecting the point G with the point A to obtain a straight line, and calculating the slope of the straight line; s7, adopting the slope or the inverse of the slope to carry out Mura quantization on the selected area. According to the method, the quality of the polycrystalline silicon after the excimer laser annealing process can be quantitatively judged, and the defect of subjective feeling evaluation of human eyes is overcome.
Description
Technical Field
The invention relates to the technical field of display, in particular to a Mura quantification method based on excimer laser annealing.
Background
Because the Low Temperature Poly Silicon (LTPS) film has regular atomic arrangement and high carrier mobility (10-300 cm 2/Vs), when the LTPS film is applied to electronic components and devices, the LTPS film can have higher driving current, so that the LTPS film is widely used as the material of an active layer of one of the core structures of the TFT in the manufacturing process of the TFT. Currently, in modern TFT manufacturing processes, an Excimer Laser Annealing (ELA) method is often used to form a polysilicon active layer. The ELA method mainly performs laser irradiation on the amorphous silicon thin film by excimer laser with a certain energy, and converts amorphous silicon into LTPS at a high temperature by using the energy of a laser beam. Polysilicon TFTs formed by ELA have the advantage of high mobility. However, the crystallization rate, grain size and internal defect density of the obtained polysilicon are different due to instability of the laser energy used and non-uniformity of the energy at different positions of the beam. These differences are in turn closely related to the threshold voltage (Vth) and mobility of the TFT, which in turn gives rise to non-uniform light emission luminance (Mura) in OLED displays.
Currently, the detection of Mura based on excimer laser annealing is mostly not separated from a manual detection stage, and whether the brightness of the display panel has the defect of uneven brightness is determined by direct observation of trained workers. However, because the manual detection cost is high and the detection time is long, only sampling inspection can be performed, manual judgment standards are different, the judgment has no uniform quantization standard, the subjectivity is strong, the datamation can not be maintained, and the eye fatigue is easily caused by long-time work. Meanwhile, the accuracy of manual detection is uncontrollable, the reliability is relatively low, and the efficiency is low.
Disclosure of Invention
In order to solve the defects of the prior art, the invention provides a Mura quantification method based on excimer laser annealing.
The technical problem to be solved by the invention is realized by the following technical scheme:
a Mura quantification method based on excimer laser annealing comprises the following steps:
s1, respectively collecting Mura images of the same region of the same substrate after excimer laser annealing under different light intensities;
s2, performing image processing on the Mura image to determine the area of a Mura region;
s3, drawing a linear relation curve of light intensity and Mura area;
s4, repeating the steps S1-S3, wherein all linear relation curves drawn in the same coordinate system pass through a point G;
s5, under certain light intensity, obtaining a Mura image of a selected area of the substrate to be detected, and obtaining the area of the Mura area after image processing; drawing a point A in the coordinate system according to the light intensity and the Mura area;
s6, connecting the point G with the point A to obtain a straight line, and calculating the slope of the straight line;
s7, adopting the slope or the inverse of the slope to carry out Mura quantization on the selected area.
Further, in step S2, image processing is performed on the Mura image through image processing software to obtain gray-scale intensity of each pixel, and a region with gray-scale intensity smaller than a preset threshold is identified as a Mura region, otherwise, the region is identified as a non-Mura region.
Further, the gray scale intensity of the pixels in the Mura region is changed to 0 through image processing software, the gray scale intensity of the pixels in the non-Mura region is changed to 255, and the area of the Mura region is determined.
Further, in step S3, performing linear regression fitting on a plurality of data points using the light intensity as a vertical coordinate and the Mura region area as a horizontal coordinate to obtain a linear relationship curve of the light intensity and the Mura region area; in step S7, Mura quantization is performed using the slope.
Further, in step S3, performing linear regression fitting on a plurality of data points with the Mura area as a vertical coordinate and the light intensity as a horizontal coordinate to obtain a linear relationship curve of the light intensity and the Mura area; in step S7, the inverse of the slope is used to perform Mura quantization.
The invention has the following beneficial effects:
according to the invention, the quality of the polycrystalline silicon after the excimer laser annealing process can be quantitatively judged, the defect of subjective feeling evaluation of human eyes is overcome, the Mura judgment has a unified standard and a quantifiable index, the product quality deviation caused by artificial subjective factors is reduced, the strict control of the product quality is facilitated, the quality parameters of the polycrystalline silicon after the excimer laser annealing process can be scientifically and objectively judged, and the application significance is achieved.
Drawings
FIG. 1 is a first linear plot of light intensity versus Mura region area for one embodiment of the present invention;
FIG. 2 is a second linear plot of light intensity versus Mura region area for one embodiment of the present invention;
FIG. 3 is a third linear plot of light intensity versus Mura region area for one embodiment of the present invention;
FIG. 4 is a fourth linear plot of light intensity versus Mura region area for one embodiment of the present invention;
FIG. 5 is a fifth linear plot of light intensity versus Mura region area for one embodiment of the present invention;
FIG. 6 is a sixth linear relationship between light intensity and Mura region area for one embodiment of the present invention;
FIG. 7 is a seventh linear relationship of light intensity to Mura region area for one embodiment of the present invention;
FIG. 8 is an eighth linear plot of light intensity versus Mura region area for one embodiment of the present invention;
FIG. 9 is a ninth linear plot of light intensity versus Mura region area for one embodiment of the present invention;
FIG. 10 is a tenth linear plot of light intensity versus Mura region area for one embodiment of the present invention;
FIG. 11 is an eleventh linear plot of light intensity versus Mura region area for one embodiment of the present invention;
FIG. 12 is a graph of linear relationships plotted in the same coordinate system.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
In the description of the present invention, it should be noted that the terms "upper", "lower", "inside", "outside", and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings or orientations or positional relationships conventionally put in use of products of the present invention, and are only for convenience of description and simplification of description, but do not indicate or imply that the devices or elements referred to must have specific orientations, be constructed in specific orientations, and be operated, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," "third," and the like are used solely to distinguish one from another and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it should also be noted that, unless otherwise explicitly specified or limited, the terms "disposed" and "connected" are to be interpreted broadly, e.g., as being either fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present invention can be understood in specific cases to those skilled in the art.
As described in the background art, in the prior art, most of Mura detection based on excimer laser annealing has not been separated from the manual detection stage, and whether the display panel has the defect of uneven brightness is determined by direct observation of trained workers, and the manual judgment standards are different, and the problems of no uniform quantization standard, strong subjectivity and low efficiency are solved. In order to solve the technical problems, repeated research shows that the Mura area of the surface after excimer laser annealing crystallization is photographed and the Mura area is determined through image processing to determine the Mura number, and the Mura area is related to the whole illumination intensity, so that the Mura area is directly used for indicating the Mura number and the Mura number is more and is not real. However, under different light intensities, if the light intensity and the area of the Mura region of the same Mura have a linear relationship, i.e. a constant slope exists, the Mura can be quantized by using the slope or the reciprocal of the slope, so as to remove the unreality caused by the influence of the light intensity. When the inverse slope is larger, the Mura is less, or when the slope is small, the Mura is less. The present invention has been completed based on the above findings and findings.
A Mura quantification method based on excimer laser annealing comprises the following steps:
s1, respectively collecting Mura images of the same region of the same substrate after excimer laser annealing under different light intensities;
s2, performing image processing on the Mura image to determine the area of a Mura region;
s3, drawing a linear relation curve of light intensity and Mura area;
s4, repeating the steps S1-S3, wherein all linear relation curves drawn in the same coordinate system pass through a point G;
s5, under certain light intensity, obtaining a Mura image of a selected area of the substrate to be detected, and obtaining the area of the Mura area after image processing; drawing a point A in the coordinate system according to the light intensity and the Mura area;
s6, connecting the point G with the point A to obtain a straight line, and calculating the slope of the straight line;
s7, adopting the slope or the inverse of the slope to carry out Mura quantization on the selected area.
In the present invention, the apparatus for acquiring the Mura image is not particularly limited, and various apparatuses known to those skilled in the art may be used for the acquisition, and by way of example, a general CCD camera connected to a central processing unit to control the opening/closing, the angle (θ) and the operation may be used, and it is understood that all other cameras capable of acquiring the image may be used.
Specifically, in step S2, image processing is performed on the Mura image through image processing software to obtain gray-scale intensity of each pixel, and a region with gray-scale intensity smaller than a preset threshold is identified as a Mura region, otherwise, the region is identified as a non-Mura region; and changing the gray scale intensity of the pixels in the Mura region into 0 and changing the gray scale intensity of the pixels in the non-Mura region into 255 by using image processing software, and determining the area of the Mura region.
In the present invention, the number of times of repeating steps S1-S3 is not particularly limited, and those skilled in the art can select the number according to actual needs, and the number may be, for example, 8, 9, 10, or 11, but is not limited thereto.
In the present invention, the specific type of the image processing software is not particularly limited, and image processing software known to those skilled in the art may be used as long as the above-described functions are realized. By way of example, the picture processing software is photoshop.
In step S3, linear regression fitting may be performed on a plurality of data points with the light intensity as a vertical coordinate and the Mura region area as a horizontal coordinate to obtain a linear relationship curve of the light intensity and the Mura region area; in step S7, Mura quantization is performed using the slope.
In step S3, linear regression fitting may be performed on a plurality of data points with the Mura area as a vertical coordinate and the light intensity as a horizontal coordinate to obtain a linear relationship curve of the light intensity and the Mura area; in step S7, the inverse of the slope is used to perform Mura quantization.
According to the method, the quality of the polycrystalline silicon after the excimer laser annealing process can be quantitatively judged, the defect of subjective feeling evaluation of human eyes is overcome, the Mura judgment has a unified standard and quantifiable index, the product quality deviation caused by artificial subjective factors is reduced, the strict control of the product quality is facilitated, the quality parameters of the polycrystalline silicon after the excimer laser annealing process can be scientifically and objectively judged, and the method has important application significance.
Example 1
A Mura quantification method based on excimer laser annealing comprises the following steps:
s1, respectively collecting Mura images of the same region of the same substrate after excimer laser annealing under different light intensities;
s2, performing image processing on the Mura image through image processing software to obtain the gray scale intensity of each pixel, and identifying the area with the gray scale intensity smaller than a preset threshold value as a Mura area, or else identifying the area as a non-Mura area; changing the gray scale intensity of the pixels in the Mura region into 0 through image processing software, changing the gray scale intensity of the pixels in the non-Mura region into 255, and determining the area of the Mura region;
s3, performing linear regression fitting on a plurality of data points with the light intensity as a vertical coordinate and the Mura region area as a horizontal coordinate to obtain a first linear relation curve of the light intensity and the Mura region area; (ii) a
S4, repeating the steps S1-S3, and drawing a second linear relation curve, a third linear relation curve, a fourth linear relation curve, a fifth linear relation curve, a sixth linear relation curve, a seventh linear relation curve, an eighth linear relation curve, a ninth linear relation curve, a tenth linear relation curve and an eleventh linear relation curve in the same coordinate system, wherein all the linear relation curves pass through a point G;
s5, under certain light intensity, obtaining a Mura image of a selected area of the substrate to be detected, and obtaining the area of the Mura area after image processing; drawing a point A in the coordinate system according to the light intensity and the Mura area;
s6, connecting the point G with the point A to obtain a straight line, and calculating the slope of the straight line;
and S7, performing Mura quantization on the selected area by adopting the slope.
The above-mentioned embodiments only express the embodiments of the present invention, and the description is more specific and detailed, but not understood as the limitation of the patent scope of the present invention, but all the technical solutions obtained by using the equivalent substitution or the equivalent transformation should fall within the protection scope of the present invention.
Claims (5)
1. A Mura quantification method based on excimer laser annealing is characterized by comprising the following steps:
s1, respectively collecting Mura images of the same region of the same substrate after excimer laser annealing under different light intensities;
s2, performing image processing on the Mura image to determine the area of a Mura region;
s3, drawing a linear relation curve of light intensity and Mura area;
s4, repeating the steps S1-S3, wherein all linear relation curves drawn in the same coordinate system pass through a point G;
s5, under certain light intensity, obtaining a Mura image of a selected area of the substrate to be detected, and obtaining the area of the Mura area after image processing; drawing a point A in the coordinate system according to the light intensity and the Mura area;
s6, connecting the point G with the point A to obtain a straight line, and calculating the slope of the straight line;
s7, adopting the slope or the inverse of the slope to carry out Mura quantization on the selected area.
2. The method of claim 1, wherein in step S2, the Mura image is processed by a picture processing software to obtain gray-scale intensity of each pixel, and the region with gray-scale intensity smaller than a preset threshold is identified as a Mura region, otherwise identified as a non-Mura region.
3. The method of claim 2, wherein the Mura area is determined by changing the gray scale intensity of the pixels in the Mura region to 0 and the gray scale intensity of the pixels in the non-Mura region to 255 with picture processing software.
4. The method according to claim 1, wherein in step S3, linear regression fitting is performed on a plurality of data points using light intensity as ordinate and Mura region area as abscissa, so as to obtain a linear relationship curve between light intensity and Mura region area; in step S7, Mura quantization is performed using the slope.
5. The method according to claim 1, wherein in step S3, linear regression fitting is performed on a plurality of data points using the area of the Mura region as ordinate and the light intensity as abscissa, so as to obtain a linear relationship curve between the light intensity and the area of the Mura region; in step S7, the inverse of the slope is used to perform Mura quantization.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911318622.8A CN110991082B (en) | 2019-12-19 | 2019-12-19 | Mura quantification method based on excimer laser annealing |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911318622.8A CN110991082B (en) | 2019-12-19 | 2019-12-19 | Mura quantification method based on excimer laser annealing |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110991082A true CN110991082A (en) | 2020-04-10 |
| CN110991082B CN110991082B (en) | 2023-11-28 |
Family
ID=70065539
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911318622.8A Active CN110991082B (en) | 2019-12-19 | 2019-12-19 | Mura quantification method based on excimer laser annealing |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110991082B (en) |
Citations (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6104839A (en) * | 1995-10-16 | 2000-08-15 | Eastman Kodak Company | Method and apparatus for correcting pixel values in a digital image |
| US20030048439A1 (en) * | 2001-09-13 | 2003-03-13 | Minoru Yoshida | Method and apparatus for inspecting pattern defects |
| JP2003177713A (en) * | 2001-09-28 | 2003-06-27 | Semiconductor Energy Lab Co Ltd | Light emitting device and electronic apparatus |
| JP2003216100A (en) * | 2002-01-21 | 2003-07-30 | Matsushita Electric Ind Co Ltd | El (electroluminescent) display panel and el display device and its driving method and method for inspecting the same device and driver circuit for the same device |
| CN103219229A (en) * | 2013-03-28 | 2013-07-24 | 昆山维信诺显示技术有限公司 | Quantitative judging method and feedback system for ELA (excimer laser annealing) heterogeneity |
| JP2014063942A (en) * | 2012-09-24 | 2014-04-10 | Hitachi High-Technologies Corp | Polycrystalline silicon film inspection method and device therefor |
| US20140329339A1 (en) * | 2009-11-30 | 2014-11-06 | Ignis Innovation Inc. | Defect detection and correction of pixel circuits for amoled displays |
| WO2017008320A1 (en) * | 2015-07-13 | 2017-01-19 | 武汉华星光电技术有限公司 | Method of detecting quality of polysilicon thin film and system utilizing same |
| CN106783875A (en) * | 2016-12-07 | 2017-05-31 | 信利（惠州）智能显示有限公司 | Low temperature polycrystalline silicon membrane preparation method, thin film transistor (TFT) and preparation method thereof |
| US20170206821A1 (en) * | 2016-01-20 | 2017-07-20 | Samsung Display Co., Ltd. | Method of compensating for an excimer laser annealing mura and display device employing the same |
| US20170213328A1 (en) * | 2016-01-21 | 2017-07-27 | Astral Images Corporation | Method and system for processing image content for enabling high dynamic range (uhd) output thereof and computer-readable medium comprising uhd content created using same |
| CN107391802A (en) * | 2017-06-23 | 2017-11-24 | 苏州大学 | Thin film transistor (TFT) output characteristics model modification 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 |
| CN108682365A (en) * | 2018-04-18 | 2018-10-19 | 武汉精测电子集团股份有限公司 | A kind of detection of OLED color spots with repair integral system, method |
| EP3401815A1 (en) * | 2017-05-09 | 2018-11-14 | Dassault Systèmes | Determining an architectural layout |
| CN109035195A (en) * | 2018-05-08 | 2018-12-18 | 武汉纺织大学 | A kind of fabric defect detection method |
| CN110288566A (en) * | 2019-05-23 | 2019-09-27 | 北京中科晶上科技股份有限公司 | A kind of target defect extracting method |
| CN110349132A (en) * | 2019-06-25 | 2019-10-18 | 武汉纺织大学 | A kind of fabric defects detection method based on light-field camera extraction of depth information |
| WO2019221938A1 (en) * | 2018-05-18 | 2019-11-21 | Kla-Tencor Corporation | Phase filter for enhanced defect detection in multilayer structure |
-
2019
- 2019-12-19 CN CN201911318622.8A patent/CN110991082B/en active Active
Patent Citations (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6104839A (en) * | 1995-10-16 | 2000-08-15 | Eastman Kodak Company | Method and apparatus for correcting pixel values in a digital image |
| US20030048439A1 (en) * | 2001-09-13 | 2003-03-13 | Minoru Yoshida | Method and apparatus for inspecting pattern defects |
| JP2003177713A (en) * | 2001-09-28 | 2003-06-27 | Semiconductor Energy Lab Co Ltd | Light emitting device and electronic apparatus |
| JP2003216100A (en) * | 2002-01-21 | 2003-07-30 | Matsushita Electric Ind Co Ltd | El (electroluminescent) display panel and el display device and its driving method and method for inspecting the same device and driver circuit for the same device |
| US20140329339A1 (en) * | 2009-11-30 | 2014-11-06 | Ignis Innovation Inc. | Defect detection and correction of pixel circuits for amoled displays |
| JP2014063942A (en) * | 2012-09-24 | 2014-04-10 | Hitachi High-Technologies Corp | Polycrystalline silicon film inspection method and device therefor |
| CN103219229A (en) * | 2013-03-28 | 2013-07-24 | 昆山维信诺显示技术有限公司 | Quantitative judging method and feedback system for ELA (excimer laser annealing) heterogeneity |
| WO2017008320A1 (en) * | 2015-07-13 | 2017-01-19 | 武汉华星光电技术有限公司 | Method of detecting quality of polysilicon thin film and system utilizing same |
| US20170206821A1 (en) * | 2016-01-20 | 2017-07-20 | Samsung Display Co., Ltd. | Method of compensating for an excimer laser annealing mura and display device employing the same |
| US20170213328A1 (en) * | 2016-01-21 | 2017-07-27 | Astral Images Corporation | Method and system for processing image content for enabling high dynamic range (uhd) output thereof and computer-readable medium comprising uhd content created using same |
| CN106783875A (en) * | 2016-12-07 | 2017-05-31 | 信利（惠州）智能显示有限公司 | Low temperature polycrystalline silicon membrane preparation method, thin film transistor (TFT) and preparation method thereof |
| EP3401815A1 (en) * | 2017-05-09 | 2018-11-14 | Dassault Systèmes | Determining an architectural layout |
| CN107391802A (en) * | 2017-06-23 | 2017-11-24 | 苏州大学 | Thin film transistor (TFT) output characteristics model modification 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 |
| CN108682365A (en) * | 2018-04-18 | 2018-10-19 | 武汉精测电子集团股份有限公司 | A kind of detection of OLED color spots with repair integral system, method |
| CN109035195A (en) * | 2018-05-08 | 2018-12-18 | 武汉纺织大学 | A kind of fabric defect detection method |
| WO2019221938A1 (en) * | 2018-05-18 | 2019-11-21 | Kla-Tencor Corporation | Phase filter for enhanced defect detection in multilayer structure |
| CN110288566A (en) * | 2019-05-23 | 2019-09-27 | 北京中科晶上科技股份有限公司 | A kind of target defect extracting method |
| CN110349132A (en) * | 2019-06-25 | 2019-10-18 | 武汉纺织大学 | A kind of fabric defects detection method based on light-field camera extraction of depth information |
Non-Patent Citations (5)
| Title |
|---|
| AIL YOUSEFIAN JAZI ET AL.: "Automatic Inspection of TFT-LCD Glass Substrates Using Optimized Support Vector Machines" * |
| MASSKURA，Y ET AL.: "Quantitative analysis of indistinct"Mura"in display based on subjective evaluation" * |
| 吉豪: ""AMOLED Mura外补偿系统的研究与实现"", 《中国优秀硕士学位论文全文数据库 信息科技》 * |
| 唐剑: "TFT-LCD Mura缺陷检测研究" * |
| 屠震涛 等: "灰度与亮度拟合对LCD面板Mura改善的影响", pages 442 - 448 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110991082B (en) | 2023-11-28 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111563889B (en) | Liquid crystal screen Mura defect detection method based on computer vision | |
| US9601060B2 (en) | Image processing method and apparatus | |
| JP4021366B2 (en) | Image quality analysis method and system for display device | |
| CN110225336B (en) | Method and device for evaluating image acquisition precision, electronic equipment and readable medium | |
| US8193008B2 (en) | Method of forming semiconductor thin film and semiconductor thin film inspection apparatus | |
| JP6325520B2 (en) | Unevenness inspection system, unevenness inspection method, and unevenness inspection program | |
| DE102010061505B4 (en) | Method for inspection and detection of defects on surfaces of disc-shaped objects | |
| US6673639B2 (en) | Method and system for evaluating polysilicon, and method and system for fabricating thin film transistor | |
| JP2001110861A (en) | Check method and device of semiconductor film, and manufacturing method of thin film transistor | |
| CN104658461B (en) | The method of testing of display lighting uniformity | |
| KR20150010392A (en) | Inspection method and apparatus of crystallized silicon | |
| US20200211156A1 (en) | Imaging apparatus and driving method of the same | |
| CN111127415B (en) | Mura quantification method based on excimer laser annealing | |
| CN110991082B (en) | Mura quantification method based on excimer laser annealing | |
| KR101939058B1 (en) | Mura quantifying system by Laser crystallization facility and Mura quantifying method by Laser crystallization facility | |
| CN108109138B (en) | Method for self-adaptive light uniformization of high-light area of mirror-like object | |
| KR101068356B1 (en) | Method for inspecting defect of the Pixels in display panel device by image | |
| CN110993491B (en) | Automatic correction method for OED (optical element design) in excimer laser annealing process | |
| JP4537131B2 (en) | Laser crystal silicon inspection method and apparatus | |
| JP6096228B2 (en) | Semiconductor film surface unevenness detection apparatus, laser annealing apparatus, and semiconductor film surface unevenness detection method | |
| CN109201750A (en) | Hot rolling low temperature coiling band steel surface based on water area purges control method | |
| KR100221697B1 (en) | Inspection method and device for perforated plate | |
| Tzu et al. | Non-uniformity evaluation of flat panel display by automatic optical detection | |
| JP2011066084A (en) | Method of forming semiconductor thin film, device for inspecting semiconductor thin film, and semiconductor thin film | |
| JP2006275691A (en) | Inspection method and inspection device |
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 |