WO2017202114A1 - 确定用于检测的光照强度的方法和装置、及光学检测方法和装置 - Google Patents

确定用于检测的光照强度的方法和装置、及光学检测方法和装置 Download PDF

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WO2017202114A1
WO2017202114A1 PCT/CN2017/076916 CN2017076916W WO2017202114A1 WO 2017202114 A1 WO2017202114 A1 WO 2017202114A1 CN 2017076916 W CN2017076916 W CN 2017076916W WO 2017202114 A1 WO2017202114 A1 WO 2017202114A1
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imaging element
illumination
illumination intensity
detection
intensity
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PCT/CN2017/076916
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English (en)
French (fr)
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王旭
刘超强
习征东
刘洋
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京东方科技集团股份有限公司
重庆京东方光电科技有限公司
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Priority to US15/552,126 priority Critical patent/US10510141B2/en
Publication of WO2017202114A1 publication Critical patent/WO2017202114A1/zh

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    • G—PHYSICS
    • G02—OPTICS
    • G02F—OPTICAL DEVICES OR ARRANGEMENTS FOR THE CONTROL OF LIGHT BY MODIFICATION OF THE OPTICAL PROPERTIES OF THE MEDIA OF THE ELEMENTS INVOLVED THEREIN; NON-LINEAR OPTICS; FREQUENCY-CHANGING OF LIGHT; OPTICAL LOGIC ELEMENTS; OPTICAL ANALOGUE/DIGITAL CONVERTERS
    • G02F1/00—Devices or arrangements for the control of the intensity, colour, phase, polarisation or direction of light arriving from an independent light source, e.g. switching, gating or modulating; Non-linear optics
    • G02F1/01—Devices or arrangements for the control of the intensity, colour, phase, polarisation or direction of light arriving from an independent light source, e.g. switching, gating or modulating; Non-linear optics for the control of the intensity, phase, polarisation or colour 
    • G02F1/13—Devices or arrangements for the control of the intensity, colour, phase, polarisation or direction of light arriving from an independent light source, e.g. switching, gating or modulating; Non-linear optics for the control of the intensity, phase, polarisation or colour  based on liquid crystals, e.g. single liquid crystal display cells
    • G02F1/1306—Details
    • G02F1/1309—Repairing; Testing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0004—Industrial image inspection
    • 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
    • G01N21/8806—Specially adapted optical and illumination features
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J1/00—Photometry, e.g. photographic exposure meter
    • 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
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/60—Control of cameras or camera modules
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/80—Camera processing pipelines; Components thereof
    • 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
    • G01N21/8806—Specially adapted optical and illumination features
    • G01N2021/8835—Adjustable illumination, e.g. software adjustable screen
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30108—Industrial image inspection
    • G06T2207/30121—CRT, LCD or plasma display
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30108—Industrial image inspection
    • G06T2207/30141—Printed circuit board [PCB]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30108—Industrial image inspection
    • G06T2207/30148—Semiconductor; IC; Wafer

Definitions

  • Embodiments of the present disclosure relate to the field of automated optical inspection, and more particularly to a method and apparatus for determining illumination intensity for detection, and an optical detection method and apparatus.
  • Automated Optical Inspection is an effective method for industrial automation. It uses machine vision as a standard for inspection. It is widely used in LCD/TFT, transistor and PCB industry processes, and can be extended to the security system for people's death applications. . Automated optical inspection is a common method commonly used in industrial processes. It uses optical methods to obtain the surface state of the object to be detected, and image processing to detect foreign matter or pattern anomalies. Because it is a non-contact inspection, semi-finished products can be inspected in the middle. When automatically detecting, the machine automatically scans the detected object through the camera, collects the image, compares the tested solder joint with the qualified parameters in the database, and after image processing, checks the defect on the detected object, and puts the defect through the display or automatic mark. Displayed/marked for repair by maintenance personnel.
  • AOI Automated Optical Inspection
  • Embodiments of the present disclosure provide a method and apparatus for determining an illumination intensity for detection, and an optical detection method and apparatus capable of obtaining an illumination intensity for detection, when detecting an object to be detected using the illumination intensity, Can improve the accuracy of detection.
  • a method of determining light intensity for detection includes:
  • the illumination intensity for detection of each imaging element is determined based on the gray scale standard deviation.
  • each of the at least one imaging element is configured to take an image of a different region of the sample to be detected.
  • determining the illumination intensity for each imaging element based on the grayscale standard deviation comprises:
  • the illumination intensity for detection of each imaging element is determined based on the intersection.
  • determining the preferred range of illumination intensities for each imaging element includes:
  • a range between the illumination intensities corresponding to the normalized gray standard deviation equal to the predetermined value is determined as the preferred range of illumination intensities for each imaging element.
  • obtaining an intersection between the preferred ranges of illumination intensities of the at least one imaging element comprises:
  • the predetermined value is gradually reduced until there is an intersection between the preferred ranges of the respective illumination intensities of the acquired imaging elements, and the intersection is obtained.
  • the predetermined value is not less than 0.8.
  • determining the illumination intensity for each imaging element based on the intersection includes:
  • the intermediate value of the intersection is determined as the illumination intensity for detection of each imaging element.
  • the checking for each imaging element is determined based on the gray standard deviation
  • the measured light intensity includes:
  • the illumination intensity corresponding to the largest gray standard deviation of the gray standard deviations is determined as the illumination intensity for detection of each imaging element.
  • the sample to be inspected is a color film substrate, a thin film transistor array substrate, or a printed circuit board for a liquid crystal display.
  • an optical detection method includes:
  • the plurality of objects to be inspected are optically detected using the determined illumination intensity.
  • an apparatus for determining a light intensity for detection includes:
  • At least one imaging element for taking an image of the sample to be detected
  • An image acquisition unit configured to acquire an image taken by each imaging element to be detected by the sample under multiple illumination intensities
  • a calculating unit configured to calculate, for each imaging element, a gray standard deviation of each of the images acquired under the plurality of illumination intensities
  • a light intensity determining unit configured to determine the light intensity for detecting of each imaging element according to the gray standard deviation.
  • each of the at least one imaging element is configured to take an image of a different region of the sample to be detected.
  • the illumination intensity determining unit includes:
  • a normalization unit for normalizing the gray standard deviation for each imaging element
  • the illumination intensity range determining unit is configured to determine a preferred illumination intensity range of each imaging element according to the normalized gray standard deviation and its correspondence with the plurality of illumination intensities;
  • An intersection acquisition unit configured to acquire an intersection between a preferred range of illumination intensities of the at least one imaging element
  • a light intensity determination subunit for determining the illumination intensity for detection of each imaging element based on the intersection.
  • the preferred illumination intensity range determining unit is further configured to:
  • a range between the illumination intensities corresponding to the normalized gray standard deviation equal to the predetermined value is determined as the preferred range of illumination intensities for each imaging element.
  • intersection acquisition unit is further configured to:
  • the predetermined value is gradually reduced until there is an intersection between the preferred ranges of illumination intensity of the respective imaging elements that are acquired.
  • the predetermined value is greater than or equal to 0.8.
  • the illumination intensity determination subunit is further configured to:
  • the intermediate value of the intersection is determined as the illumination intensity for detection of each imaging element.
  • the illumination intensity determining unit is further configured to:
  • the illumination intensity corresponding to the largest gray standard deviation of the gray standard deviations is determined as the illumination intensity for detection of each imaging element.
  • an optical detection device includes the apparatus for determining the intensity of illumination for detection as described in any of the above embodiments.
  • the illumination intensity for detection is determined based on the gray standard deviation of the image. Since the gray standard deviation of the image is larger, indicating that the image contains more detailed information, the more favorable the detection of the defect of the sample to be detected, the detection of the object to be detected by using the method determined by the method described in the embodiments herein, Improve the accuracy of the test.
  • 1a and 1b respectively show the relationship between the number of defects and the illumination intensity when reflecting illumination and the illumination intensity when transmitting illumination
  • 2a and 2b respectively show images taken by a reflective illumination using a strong light intensity and a weaker light intensity to be detected
  • 3a and 3b respectively show images taken by the transmission illumination using the stronger illumination intensity and the weaker illumination intensity to be detected
  • FIG. 4 schematically illustrates a flow chart of a method of determining illumination intensity for detection, in accordance with an embodiment
  • FIG. 5 schematically illustrates a flow chart of an exemplary method of determining an illumination intensity for detection based on a gray standard deviation
  • Figure 6 shows schematically the ⁇ -I curve of a single imaging element
  • Figure 7 schematically illustrates a flow chart of an optical detection method in accordance with one embodiment
  • Figure 8 is a block diagram schematically showing the structure of an apparatus for determining the intensity of illumination for detection, according to one embodiment
  • Figure 9 is a schematic flow diagram showing a method of determining the intensity of illumination for detection in one example
  • ⁇ -I curve corresponding to the camera 1/3/7/11/15/19 in the example of Fig. 9 is shown in Fig. 10.
  • the amount of illumination intensity used has a large influence on the accuracy of detection.
  • people firstly detect the sample under different illumination intensities, and determine whether the illumination intensity is the optimal illumination intensity according to the number of defects detected, and the more the number of defects detected, the light intensity is considered. The result of the test is more accurate Indeed, this light intensity can then be used to perform batch inspection of the object to be tested.
  • Fig. 1a and Fig. 1b respectively show the relationship between the number of defects and the illumination intensity at the time of reflection illumination and the illumination intensity at the time of transmission illumination.
  • the stronger the illumination intensity the greater the number of defects detected, whether reflective illumination or transmissive illumination, so theoretically, stronger illumination can improve detection accuracy.
  • Figures 2a and 2b respectively show images taken by a reflective illumination using a stronger illumination intensity and a weaker illumination intensity to be detected
  • Figures 3a and 3b respectively show the treatment with a stronger illumination intensity and a weaker illumination intensity by transmissive illumination. Detect the image taken by the sample.
  • the method for determining the illumination intensity for detection provided by the embodiment of the present disclosure can detect defects as much as possible while reducing the probability of false detection and improving the detection accuracy.
  • one or more objects to be detected may be selected as a sample to be detected from a plurality of objects to be detected, and the illumination intensity determination provided by the embodiment of the present disclosure is implemented by the sample to be detected.
  • the method determines the intensity of the light used for the detection. Single or batch detection of the object to be tested can be performed using the determined illumination intensity.
  • a color filter substrate on which the protective layer is formed may be selected as a sample to be detected for detection to determine the light intensity for detection, and then the The determined light intensity is used for batch detection of the protective layer on the color filter substrate.
  • FIG. 4 schematically illustrates a flow chart of a method of determining illumination intensity for detection, in accordance with an embodiment.
  • a method of determining the intensity of illumination for detection includes the following steps:
  • Image acquisition step 41 acquiring images taken by different regions of each imaging element to be detected under a plurality of illumination intensities
  • - gray scale standard deviation calculation step 42 for each imaging element, calculating a gray standard deviation of an image acquired under a plurality of illumination intensities;
  • - Illumination intensity determination step 43 The illumination intensity for detection of each imaging element is determined from the gray standard deviation.
  • At least one imaging element can take an image of the object to be detected/sample under illumination of multiple illumination intensities.
  • each imaging element is configured to take an image of a different area of the object/sample to be detected, for example, when there are 5 imaging elements, the 5 imaging elements are responsible for 5 of the object/sample to be inspected Take images in different areas.
  • each of the plurality of imaging elements is to be imaged for detection of the sample under illumination of a plurality of different illumination intensities to obtain a plurality of images of the sample to be detected.
  • each imaging element is responsible for taking images of different areas of the sample to be tested.
  • the imaging element can be configured to capture an image of the sample to be detected by a pattern of reflected light illumination, and can also be configured to detect an image of the sample to be detected by a pattern of transmitted light illumination.
  • the illumination intensity can be set to 0-255 levels to correspond to 0-255 gray levels of the image.
  • the plurality of light intensities are selected from the 0-255 levels.
  • the illumination intensity is gradually increased from 10 to 250 at intervals of 10 to sequentially take a sample image to be detected, so that each imaging element can take 25 pictures.
  • the gray standard deviation calculation step 42 the larger the gray standard deviation of the image, the more detailed information the image contains, the more favorable the detection of the defect of the sample to be detected, so in the embodiment described herein, the image is The gray standard deviation is used as the basis for judging whether the light intensity is optimal.
  • the gray standard deviation of each image can be calculated by the following equation:
  • ⁇ is the standard deviation
  • M and N represent the number of pixels in the x and y directions
  • I(x, y) represents the gray value of a point on the image
  • I 0 represents the average gray value of the image.
  • the illumination intensity corresponding to the largest gray standard deviation can be determined as the illumination intensity for each imaging element for detection.
  • the light intensity determined by this method can obtain the best light intensity for each imaging element, but by The hardware performance of each imaging element may not be exactly the same, so the optimal illumination intensity of each imaging element may be different.
  • the illumination intensity for detection can also be determined by the following steps:
  • Normalization step 431 normalizing the gray standard deviation for each imaging element
  • ⁇ -I curve drawing step 432 for each imaging element, plot a normalized gray standard deviation-light intensity curve ( ⁇ -I curve);
  • the illumination intensity range determining step 433 determining a preferred illumination intensity range of each imaging element according to a correspondence between the normalized gray standard deviation and the illumination intensity;
  • An intersection obtaining step 434 obtaining an intersection between preferred light intensity ranges of the respective imaging elements
  • a step 435 of determining the illumination intensity of each imaging element for each imaging element is determined based on the intersection acquired in step 434.
  • the illumination intensity determined by the exemplary method illustrated in FIG. 5 can be such that each of the imaging elements is illuminated with the same illumination intensity when batch detection is performed on the object to be inspected, without setting different illumination intensities for each imaging element.
  • the operation is simple and facilitates the unification of the detection standard.
  • normalization can be performed by:
  • ⁇ is the normalized gray standard deviation of the image
  • ⁇ is the gray standard deviation of the image
  • ⁇ max is the maximum gray standard deviation corresponding to a single imaging element. It can be understood that the gray standard deviation can also be normalized by other methods, for example, by a logarithmic function or an inverse tangent function.
  • ⁇ -I curve drawing step 432 step for each imaging element, a ⁇ -I curve can be plotted.
  • Figure 6 shows schematically the ⁇ -I curve of a single imaging element. As can be seen from Figure 6, the plotted ⁇ -I curve has a peak, so the preferred illumination intensity for detection can be determined from the curve.
  • a preferred range of illumination intensities for each imaging element can be obtained from the ⁇ -I curve plotted in step 432.
  • a range between illumination intensities corresponding to a normalized gray standard deviation equal to a predetermined value may be determined as the preferred range of illumination intensities for each imaging element.
  • a predetermined value of a can be set, where 0 ⁇ a ⁇ 1.
  • the illumination intensity ranges between I 1 and I 2 are determined as imaging corresponding to the two illumination intensities I 1 and I 2 .
  • intersection acquisition step 434 an intersection between these preferred illumination intensity ranges is obtained based on the preferred illumination intensity ranges of the respective imaging elements acquired in the preferred illumination intensity determination step 433.
  • intersection can be obtained as follows:
  • the individual imaging elements of the optical detection device have the same or similar hardware configuration, and when the value of a is reduced sufficiently small, for example less than a predetermined threshold b, there is still no intersection between the preferred illumination intensities of the respective imaging elements, meaning
  • the hardware of the optical detection device may have problems, so the hardware needs to be debugged. After the debugging, the intersection is obtained again by the above method, so as to obtain the illumination intensity for detection according to the intersection.
  • the predetermined threshold is set to 0.8.
  • step 435 the intermediate value of the intersection of the preferred illumination intensity ranges of the respective imaging elements is taken as the illumination intensity for each imaging element for detection such that each imaging element uses the same Illumination captures images for ease of operation and facilitates uniformity of inspection standards.
  • the sample to be tested may be a color film substrate, a thin film transistor (TFT) array substrate, or a printed circuit board (PCB) for a liquid crystal display.
  • TFT thin film transistor
  • PCB printed circuit board
  • the method for providing the light intensity for the detection may be determined for each forming process of the product using the method provided by the embodiments described herein, and then the light intensity is used to detect whether the element formed by the process is defective. In order to repair defects in time.
  • the light intensity for detecting the black matrix can be determined using the method provided by the embodiments described herein, and then Using the determined illumination intensity to detect whether a defect exists in the black matrix on the color filter substrate to repair the defect of the black matrix in time; after forming the color filter on the color filter substrate, using the embodiments provided herein
  • the method determines the illumination intensity for detecting the color filter, and then uses the determined illumination intensity to detect whether a defect exists in the color filter, so as to timely repair the defect of the color filter.
  • defect detection can be performed after each element (such as a protective layer and a column spacer) is formed in order to perform repair in time when there is a defect.
  • the illumination intensity for detection is determined based on the gray standard deviation of the image, as indicated above, the greater the gray standard deviation of the image, the more detailed information the image contains. The more favorable the detection of the defect of the sample to be detected, the detection of the object to be detected by using the light intensity determined by the method described in the above embodiment can improve the accuracy of the detection.
  • Figure 7 schematically illustrates a flow chart of an optical detection method in accordance with one embodiment.
  • the light intensity detecting method includes:
  • Step 73 of optically detecting the object to be detected using the determined illumination intensity is
  • step 72 in order to realize the detection of the object to be detected, one of the objects to be detected may be selected as the sample to be detected, and then the sample shown in FIGS. 4-6 is implemented for the sample to be detected.
  • the method determines the illumination intensity for detection to perform batch optical inspection of the object to be detected using the determined illumination intensity.
  • step 72 since the illumination intensity for detection is determined by the same method as that described in the above embodiment and shown in FIGS. 4-6, in the above embodiment, reference is made to FIGS. 4-6.
  • the explanation and description of the method for determining the light intensity for detection and the advantages thereof are equally applicable to the present embodiment.
  • the accuracy of the detection can be improved by detecting the illumination intensity determined by the method provided by the embodiment described herein.
  • the flowchart depicted in this disclosure is merely an example. Many variations of the flowchart or the steps described therein may exist without departing from the spirit of the present disclosure. For example, the steps may be performed in a different order, or steps may be added, deleted, or modified.
  • the normalization step 431 can be omitted, and the gray standard deviation-light intensity curve can be directly drawn; the gray standard deviation-light intensity curve can also be replaced by the gray scale standard deviation-light intensity correspondence table, and these variations are considered It is part of the claimed aspect.
  • Figure 8 is a schematic block diagram showing the structure of an apparatus for determining the intensity of illumination for detection, according to one embodiment.
  • the means 80 for determining the illumination intensity for detection includes at least one imaging element 81, an image acquisition unit 82, a calculation unit 83, and a light intensity determination unit 84.
  • At least one imaging element 81 can be used to capture an image of the sample to be detected, in particular, the at least one imaging element can be used to capture an image of a different region of the sample to be detected.
  • the image acquisition unit 82 is configured to acquire an image of each of the imaging elements to be detected by the sample under a plurality of illumination intensities.
  • the calculating unit 83 is configured to calculate, for each imaging element, a gray standard deviation of each of the images acquired under the plurality of illumination intensities;
  • the illumination intensity determining unit 84 is configured to determine the illumination intensity for detection of each imaging element based on the grayscale standard deviation.
  • the illumination intensity unit 84 may further include a normalization unit, a preferred illumination intensity range determination unit, an intersection acquisition unit, and a light intensity determination subunit, wherein the normalization unit is configured for each imaging The component normalizes the gray standard deviation; preferably the illumination is strong a range determining unit, configured to determine a preferred range of illumination intensity of each imaging element according to a normalized gray standard deviation and a correspondence between the plurality of illumination intensities; and an intersection obtaining unit configured to acquire the at least An intersection between a preferred range of illumination intensities of an imaging element; an illumination intensity determination sub-unit for determining the illumination intensity for detection of each imaging element based on the intersection.
  • the preferred illumination intensity range determining unit is further configured to: determine a range between the illumination intensities corresponding to the normalized gray standard deviation equal to the predetermined value as the preferred illumination intensity of each imaging element. range.
  • the intersection acquisition unit is further configured to: determine whether there is an intersection between the preferred illumination intensity ranges of the respective imaging elements, and if present, obtain a preferred illumination intensity range of the at least one imaging element The intersection between; otherwise, the predetermined value is gradually reduced until there is an intersection between the preferred ranges of illumination intensity of the respective imaging elements that are acquired.
  • the predetermined value takes a value greater than or equal to 0.8.
  • the illumination intensity determination sub-unit is further configured to determine an intermediate value of the intersection as the illumination intensity for detection of each imaging element.
  • the illumination intensity determining unit 84 is further configured to determine, for each imaging element, the illumination intensity corresponding to the largest gray standard deviation of the gray standard deviations as the illumination intensity for each imaging element for detection.
  • the illumination intensity for detection can be determined by means for determining the illumination intensity for detection provided by the embodiments described herein. Specifically, the method of determining the illumination intensity for detection as described in the above embodiment and shown in FIGS. 4-6 is used to determine the illumination intensity. Therefore, the explanation and explanation of the method of determining the illumination intensity for detection and the advantages thereof produced in the above embodiment with reference to Figs. 4-6 are also suitable for the present embodiment.
  • an optical detection device is also provided for automated optical detection of an object to be detected.
  • the optical detecting device includes the means for determining the intensity of illumination for detection provided by the foregoing embodiments.
  • the optical detecting device includes the device for determining the light intensity for detection provided by the foregoing embodiment, an explanation and explanation of the device for determining the light intensity for detection in the foregoing embodiment The same applies to this embodiment.
  • the protective layer on the color filter substrate is detected by an automated optical inspection device having 19 Reflective Cameras to determine the illumination intensity for detection. Further, the protective layer on the color filter substrate can be mass-detected using the determined illumination intensity.
  • Figure 9 is a schematic flow diagram showing a method of determining the intensity of illumination for detection in one example.
  • the illumination intensity is set to gradually increase from 10 to 10 at intervals of 10, in which case each camera can take 25 images at 25 different illumination intensities.
  • the method of determining the illumination intensity for detection includes the following steps:
  • Step 91 Acquire an image taken by the 19 cameras to be detected under different reflected light intensities
  • Step 92 Calculate the gray standard deviation of each image by image processing software for each camera;
  • Step 93 For each camera, draw a gray standard deviation-light intensity curve
  • the gray standard deviation can be normalized, in which case a normalized gray standard deviation-light intensity curve ( ⁇ -I curve) can be drawn.
  • ⁇ -I curve corresponding to the camera 1/3/7/11/15/19 is shown in FIG. 10, and in FIG. 10, the ordinate is the normalized gradation standard deviation, and the abscissa is the illumination intensity;
  • Step 95 Decrease the value of a at intervals of 0.02;
  • Step 96 Determine whether a is less than a predetermined threshold (such as 0.8), and if so, debug the device, and then return to step 91; if not, execute step 97;
  • a predetermined threshold such as 0.8
  • step 96 if a is less than the predetermined threshold, the intersection is still not found, indicating that there is a problem with the device, and the device can be debugged, for example, adjusting the focus position of the camera lens, adjusting the camera gain, and the like.
  • the illumination intensity range of each camera has an intersection [148, 168], so the preferred illumination intensity range of the automatic optical detection device is [148, 168], and the intermediate value of the preferred illumination intensity range is 158 is set to the light intensity for detection. Using this light intensity to perform automatic optical inspection of the object to be inspected can improve the accuracy of the detection.

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Abstract

一种确定用于检测的光照强度的方法和装置、及光学检测方法和装置。一种确定用于检测的光照强度的方法包括：获取至少一个成像元件中的每个成像元件在多个光照强度下对待检测样品拍摄的图像(41)；对于每个成像元件，计算在多个光照强度下获取的图像中的每幅图像的灰度标准差(42)；根据灰度标准差确定每个成像元件的用于检测的光照强度(43)。根据该方法确定的光照强度对待检测对象进行检测，能够提高检测的准确度。

Description

确定用于检测的光照强度的方法和装置、及光学检测方法和装置
相关申请的交叉引用
本申请要求于2016年05月23日递交的中国专利申请第201610342920.0号的优先权和权益，在此全文引用上述中国专利申请公开的内容以作为本申请的一部分。
技术领域
本公开的实施例涉及自动光学检测领域，尤其涉及一种确定用于检测的光照强度的方法和装置、及光学检测方法和装置。
背景技术
自动光学检测(AOI,Automated Optical Inspection)为工业自动化有效的检测方法，使用机器视觉作为检测标准技术，大量应用于LCD/TFT、晶体管与PCB工业制程上，在民生用途方面则可延伸至保全系统。自动光学检测是工业制程中常见的代表性手法，利用光学方式取得检测对象的表面状态，以影像处理来检出异物或图案异常等瑕疵。因为是非接触式检查，所以可在中间工程检查半成品。当自动检测时，机器通过摄像头自动扫描检测对象，采集图像，测试的焊点与数据库中的合格的参数进行比较，经过图像处理，检查出检测对象上的缺陷，并通过显示器或自动标志把缺陷显示/标示出来，供维修人员修整。
发明内容
本公开的实施例提供了一种确定用于检测的光照强度的方法和装置、及一种光学检测方法和装置，能够获得用于检测的光照强度，使用该光照强度对待检测对象进行检测时，可以提高检测的准确性。
在本文描述的一个实施例中，一种确定用于检测的光照强度的方法，包括：
获取至少一个成像元件中的每个成像元件在多个光照强度下对待检测 样品拍摄的图像；
对于每个成像元件，计算在所述多个光照强度下获取的图像中的每幅图像的灰度标准差；
根据所述灰度标准差确定每个成像元件的所述用于检测的光照强度。
在一个示例中，所述至少一个成像元件中的每个成像元件被配置为对所述待检测样品的不同区域拍摄图像。
在一个示例中，根据所述灰度标准差确定每个成像元件的所述用于检测的光照强度包括：
对于每个成像元件，归一化所述灰度标准差；
根据归一化的灰度标准差及其与所述多个光照强度之间的对应关系，确定每个成像元件的优选光照强度范围；
获取所述至少一个成像元件的优选光照强度范围之间的交集；
根据所述交集确定每个成像元件的所述用于检测的光照强度。
在一个示例中，确定每个成像元件的所述优选光照强度范围包括：
将等于预定值的归一化的灰度标准差所对应的光照强度之间的范围确定为每个成像元件的所述优选光照强度范围。
在一个示例中，获取所述至少一个成像元件的优选光照强度范围之间的交集包括：
判断各个成像元件的所述优选光照强度范围之间是否存在交集，若存在，则获取所述交集；否则，
逐渐减小所述预定值，直到获取的各个成像元件的所述优选光照强度范围之间存在交集，并获取所述交集。
在一个示例中，所述预定值不小于0.8。
在一个示例中，根据所述交集确定每个成像元件的所述用于检测的光照强度包括：
将所述交集中的中间值确定为每个成像元件的所述用于检测的光照强度。
在一个示例中，根据所述灰度标准差确定每个成像元件的所述用于检 测的光照强度包括：
对于每个成像元件，将所述灰度标准差中最大的灰度标准差对应的光照强度确定为每个成像元件的所述用于检测的光照强度。
在一个示例中，所述待检测样品为用于液晶显示器的彩膜基板、薄膜晶体管阵列基板、或印刷电路板。
在另一个实施例中，一种光学检测方法包括：
从多个待检测对象中选择至少一个待检测对象作为待检测样品；
使用所述待检测样品，根据前述任一实施例描述的方法确定至少一个成像元件中的每个成像元件的用于检测的光照强度；
使用所确定的光照强度对所述多个待检测对象进行光学检测。
在又一种实施例中，一种确定用于检测的光照强度的装置，包括：
至少一个成像元件，用于对待检测样品拍摄图像；
图像获取单元，用于获取每个成像元件在多个光照强度下对待检测样品拍摄的图像；
计算单元，用于对于每个成像元件计算在所述多个光照强度下获取的图像中的每幅图像的灰度标准差；
光照强度确定单元，用于根据所述灰度标准差确定每个成像元件的所述用于检测的光照强度。
在一个示例中，所述至少一个成像元件中的每个成像元件用于对所述待检测样品的不同区域拍摄图像。
在一个示例中，所述光照强度确定单元包括：
归一化单元，用于对于每个成像元件归一化所述灰度标准差；
优选光照强度范围确定单元，用于根据归一化的灰度标准差及其与所述多个光照强度之间的对应关系，确定每个成像元件的优选光照强度范围；
交集获取单元，用于获取所述至少一个成像元件的优选光照强度范围之间的交集；
光照强度确定子单元，用于根据所述交集确定每个成像元件的所述用于检测的光照强度。
在一个示例中，所述优选光照强度范围确定单元还用于：
将等于预定值的归一化的灰度标准差所对应的光照强度之间的范围确定为每个成像元件的所述优选光照强度范围。
在一个示例中，所述交集获取单元还用于：
判断各个成像元件的所述优选光照强度范围之间是否存在交集，若存在，则获取所述至少一个成像元件的优选光照强度范围之间的交集；否则，
逐渐减小所述预定值，直到获取的各个成像元件的所述优选光照强度范围之间存在交集。
在一个示例中，所述预定值为大于或等于0.8。
在一个示例中，所述光照强度确定子单元还用于：
将所述交集中的中间值确定为每个成像元件的所述用于检测的光照强度。
在一个示例中，所述光照强度确定单元还用于：
对于每个成像元件，将所述灰度标准差中最大的灰度标准差对应的光照强度确定为每个成像元件的所述用于检测的光照强度。
在又一个实施例中，一种光学检测装置，包括上述任一实施例描述的确定用于检测的光照强度的装置。
在本文中描述的示例性的实施例中，根据图像的灰度标准差来确定用于检测的光照强度。由于图像的灰度标准差越大，表明图像包含的细节信息越多，越利于待检测样品的缺陷的检测，通过使用本文中的实施例描述的方法确定的光照强度对待检测对象进行检测，能够提高检测的准确性。
适应性的进一步的方面和范围从本文中提供的描述变得明显。应当理解，本申请的各个方面可以单独或者与一个或多个其他方面组合实施。还应当理解，本文中的描述和特定实施例旨在仅说明的目的并不旨在限制本申请的范围。
附图说明
本文中描述的附图用于仅对所选择的实施例的说明的目的，并不是所 有可能的实施方式，并且不旨在限制本申请的范围。
在附图中：
图1a和图1b分别示出了缺陷数量与反射照明时的光照强度和透射照明时的光照强度的关系曲线；
图2a和图2b分别示出通过反射照明使用较强光照强度和较弱光照强度对待检测样品拍摄的图像；
图3a和图3b分别示出通过透射照明使用较强光照强度和较弱光照强度对待检测样品拍摄的图像；
图4示意性地示出根据一种实施例的确定用于检测的光照强度的方法的流程图；
图5示意性示出根据灰度标准差确定用于检测的光照强度的示例性方法的流程图；
图6示意性示出单个成像元件的σ-I曲线；
图7示意性示出根据一个实施例的光学检测方法的流程图；
图8示意性示出根据一个实施例的确定用于检测的光照强度的装置的结构框图；
图9示意性示出在一个实例中的确定用于检测的光照强度的方法的流程图；
图10中示出了在图9的实例中的对应于摄像机1/3/7/11/15/19的σ-I曲线。
贯穿这些附图的各个视图，相应的参考编号指示相应的部件或特征。
具体实施方式
现将参照附图更全面地描述示例性的实施例。
在进行自动光学检测时，所使用的光照强度的大小对检测的准确性具有较大的影响。在相关技术中，人们首先通过对待检测样品在不同的光照强度下进行检测，根据检测出的缺陷数量来判断光照强度是否是最佳光照强度，检测出的缺陷数量越多，认为在该光照强度下进行检测的结果越准 确，然后可以使用该光照强度对待检测对象进行批量检测。
图1a和图1b分别示出了缺陷数量与反射照明时的光照强度和透射照明时的光照强度的关系曲线。如图1a和图1b所示，无论是反射照明还是透射照明，光照强度越强，检测出的缺陷数量越多，因此理论上采用较强的照明可以提高检测准确度。但是，实际上，当光照强度较强时，图像细节容易丢失，检测出的缺陷中可能包含误检的成分。图2a和图2b分别示出通过反射照明使用较强光照强度和较弱光照强度对待检测样品拍摄的图像，图3a和图3b分别示出通过透射照明使用较强光照强度和较弱光照强度对待检测样品拍摄的图像。从图2a、2b、3a和3b可知，无论是反射照明还是透射照明，当光照强度较大时，图像细节丢失严重，因此会造成误检。另一方面，虽然光照强度较弱时，图像细节比较明显，但是从图1a和图1b可知光照强度较弱时，没有峰值出现，因此无法确定较佳的光照强度。
本公开的实施例提供的用于确定用于检测的光照强度方法，能够尽量多地检测出缺陷，同时又能够减少误检的概率，提高检测准确性。
需要说明的是，在本文中描述的实施例中，可以从多个待检测对象中选择一个或多个待检测对象作为待检测样品，通过对待检测样品实施本公开的实施例提供的光照强度确定方法来确定用于检测的光照强度。使用该确定的光照强度可以对待检测对象进行单个或批量检测。例如，当需要对液晶显示器的彩膜基板上的保护层进行检测时，可以选择一个做完保护层的彩膜基板作为待检测样品进行检测，以确定用于检测的光照强度，然后可以采用该确定的光照强度对彩膜基板上的保护层进行批量检测。图4示意性地示出根据一种实施例的确定用于检测的光照强度的方法的流程图。
参照图4，一种确定用于检测的光照强度的方法包括以下步骤：
-图像获取步骤41：获取在多个光照强度下每个成像元件对待检测样品的不同区域拍摄的图像；
-灰度标准差计算步骤42：对于每个成像元件，计算在多个光照强度下获取的图像的灰度标准差；
-光照强度确定步骤43：根据灰度标准差确定每个成像元件的用于检测的光照强度。
在本文描述的实施例中，至少一个成像元件可以在多个光照强度的照明下对待检测对象/样品拍摄图像。当成像元件为多个时，每个成像元件被配置为对待检测对象/样品的不同区域拍摄图像，例如，当具有5个成像元件时，该5个成像元件负责对待检测对象/样品的5个不同区域拍摄图像。
将参照相应附图对前述这些步骤中的每个步骤进行详细描述。为了便于描述，本文中公开的实施例以多个成像元件为例进行描述确定用于检测的光照强度的方法。
在图像获取步骤41中，多个成像元件中的每一个在多个不同的光照强度的照明下对待检测样品拍摄图像，以获取待检测样品的多幅图像。如上所述，每个成像元件负责对待检测样品的不同区域拍摄图像。在一个实施例中，成像元件可以配置为通过反射光照明的模式对待检测样品拍摄图像，还可以配置为通过透射光照明的模式对待检测样品拍摄图像。
在可选的实施例中，可以将光照强度设定为0-255个等级，以对应于图像的0-255个灰度级。多个光照强度选自该0-255个等级。例如，对于每个成像元件，将光照强度以10为间隔从10开始逐渐增加到250依次对待检测样品拍摄图像，因此每个成像元件可以拍摄25张图片。
在灰度标准差计算步骤42中，图像的灰度标准差越大，表明图像包含的细节信息越多，越利于待检测样品的缺陷的检测，因此在本文中描述的实施例中，将图像的灰度标准差作为判断光照强度是否最佳的依据。
在操作时，每幅图像的灰度标准差可以通过以下等式计算：
Figure PCTCN2017076916-appb-000001
式中，δ为标准差，M、N分别表示图像在x、y方向上的像素个数，I(x，y)表示图像上某一点的灰度值，I0表示图像的平均灰度值。
在光照强度确定步骤43中，对于每个成像元件，可以将最大的灰度标准差对应的光照强度确定为每个成像元件的用于检测的光照强度。通过这种方法确定的光照强度，可以获得每个成像元件的最佳光照强度，但是由 于每个成像元件的硬件性能可能不完全一致，因此每个成像元件的最佳光照强度可能不同，在对待检测对象进行光学检测时，需要针对每个成像元件设置不同的光照强度。
在另一个示例性的实施例中，参见图5，还可以通过以下步骤来确定用于检测的光照强度：
归一化步骤431：对于每个成像元件，将灰度标准差进行归一化处理；
σ-I曲线绘制步骤432：对于每个成像元件，绘制归一化的灰度标准差-光照强度的曲线(σ-I曲线)；
优选光照强度范围确定步骤433：根据归一化的灰度标准差与光照强度之间的对应关系，确定每个成像元件的优选光照强度范围；
交集获取步骤434：获取各个成像元件的优选光照强度范围之间的交集；
根据在步骤434中获取的交集确定每个成像元件的用于检测的光照强度的步骤435。
通过图5中示出的示例性方法确定的光照强度，可以使得在对待检测对象进行批量检测时，每个成像元件使用相同的光照强度进行照明，不需要为每个成像元件设置不同的光照强度，操作简单，且利于检测标准的统一。
在归一化步骤431中，可以通过下式进行归一化：
Figure PCTCN2017076916-appb-000002
其中，σ为图像的归一化的灰度标准差，δ为图像的灰度标准差，δmax为对应于单个成像元件的最大灰度标准差。可以理解，也可以通过其他的方法对灰度标准差进行归一化处理，例如通过对数函数或者反正切函数进行归一化。
在σ-I曲线绘制步骤432步骤中，针对每个成像元件，可以绘制一个σ-I曲线。图6示意性示出单个成像元件的σ-I曲线。从图6可以看出，绘制的σ-I曲线具有峰值，因此可以根据该曲线确定用于检测的较佳的光照强度。
在优选光照强度范围确定步骤433中，可以根据在步骤432中绘制的σ-I曲线获取每个成像元件的优选光照强度范围。在一个示例性的实施例中，可以将等于预定值的归一化的灰度标准差所对应的光照强度之间的范围确定为每个成像元件的所述优选光照强度范围。对于每个成像元件，可以设定预定值为a，其中0<a≤1。如图6所示，当σ＝a且a≠1时，对应两个光照强度I1和I2，将位于I1和I2之间(含I1和I2)光照强度范围确定为成像元件的优选光照强度范围。在一个特殊的实施例中，当a＝1时，只对应一个光照强度，可以认为优选光照强度范围中只有一个元素。
在交集获取步骤434中，根据在优选光照强度确定步骤433中获取的各个成像元件的优选光照强度范围，获取这些优选光照强度范围之间的交集。
在具体操作时，示例性地，可以按照如下步骤获取交集：
i)设定a＝1，判断a＝1时各个成像元件的相应光照强度是否相同，如果是，则将该光照强度作为用于检测的光照强度；否则执行步骤ii)；
ii)减小a的取值；
iii)判断a是否大于预定阈值b，其中0<b≤1，若是，则执行步骤IV)；否则，对用于检测的光学检测装置的硬件进行调试；
IV)获取σ＝a所对应的优选光照强度范围，判断各个成像元件的优选光照强度范围是否存在交集，若是，则获取各个成像元件的优选光照强度范围之间的交集；否则返回步骤ii)。
通常情况下，光学检测装置的各个成像元件具有相同或相近的硬件配置，当a的值减小到足够小时，例如小于预定阈值b时，各个成像元件的优选光照强度之间依然没有交集，意味着光学检测装置的硬件可能出现问题，因此需要对硬件进行调试，调试后再次通过上述方法获取交集，以便根据交集获取用于检测的光照强度。
在一个实施例中，预定阈值设定为0.8。
在步骤435中，将各个成像元件的优选光照强度范围的交集的中间值作为各个成像元件的用于检测的光照强度，使得每个成像元件使用相同的 照明拍摄图像，便于操作且有利于检测标准的统一。
在一个示例性的实施例中，待检测样品可以为用于液晶显示器的彩膜基板、薄膜晶体管(TFT)阵列基板、或印刷电路板(PCB)。
在产品的制作过程中，可以针对产品的每个形成工艺，使用本文描述的实施例提供的方法来确定用于检测的光照强度，然后采用该光照强度对该工艺形成的元素是否存在缺陷进行检测，以便及时修复缺陷。例如，当待检测对象为显示器的彩膜基板时，在彩膜基板制作过程中，在形成黑矩阵后，可以使用本文中描述的实施例提供的方法确定用于检测黑矩阵的光照强度，然后使用该确定的光照强度对彩膜基板上的黑矩阵中是否存在缺陷进行检测，以便及时修复黑矩阵的缺陷；在彩膜基板上形成彩色滤光片后，使用本文中描述的实施例提供的方法确定用于检测彩色滤光片的光照强度，然后使用该确定的光照强度对彩色滤光片中是否存在缺陷进行检测，以便及时修复彩色滤光片的缺陷。按照相同的方法，可以依次在各个元素(如保护层和柱状隔垫物等)形成后进行缺陷检测，以便当存在缺陷时及时进行修复。
在本文中描述的示例性的实施例中，根据图像的灰度标准差来确定用于检测的光照强度，如上所示，由于图像的灰度标准差越大，表明图像包含的细节信息越多，越利于待检测样品的缺陷的检测，通过使用上述实施例描述的方法确定的光照强度对待检测对象进行检测，能够提高检测的准确性。
图7示意性示出根据一个实施例的光学检测方法的流程图。如图7所示，光照强度检测方法包括：
从多个待检测对象中选择至少一个待检测对象作为待检测样品的步骤71；
使用所述待检测样品确定用于检测的光照强度的步骤72；
使用确定的光照强度对待检测对象进行光学检测的步骤73。
在步骤72中，为了实现对待检测对象的检测，可以首先从待检测对象中选择一个作为待检测样品，然后对待检测样品实施图4-图6中示出的方 法来确定用于检测的光照强度，以便使用该确定的光照强度对待检测对象进行批量光学检测。
在步骤72中，由于采用与上述实施例描述的以及图4-图6中示出的方法相同的方法来确定用于检测的光照强度，因此，在上述实施例中参照图4-图6对确定用于检测的光照强度的方法及其产生的优点的解释、说明同样适于本实施例。
如上所示，由于采用本文中描述的实施例提供的方法确定的光照强度对待检测对象进行检测，可以提高检测的准确度。
本公开中描绘的流程图仅仅是一个例子。在不脱离本公开精神的情况下，可以存在该流程图或其中描述的步骤的很多变型。例如，所述步骤可以以不同的顺序进行，或者可以添加、删除或者修改步骤。例如，可以省略归一化步骤431，直接绘制灰度标准差-光照强度曲线；还可以用灰度标准差-光照强度的对应表来替代灰度标准差-光照强度曲线，这些变型都被认为是所要求保护的方面的一部分。
图8示意性示出根据一个实施例的确定用于检测的光照强度的装置的结构框图。如图8所示，确定用于检测的光照强度的装置80包括至少一个成像元件81、图像获取单元82、计算单元83以及光照强度确定单元84。
至少一个成像元件81可以用于对待检测样品拍摄图像，具体地，该至少一个成像元件可以用于对待检测样品的不同区域拍摄图像。
图像获取单元82用于获取每个成像元件在多个光照强度下对待检测样品拍摄的图像。
计算单元83用于对于每个成像元件计算在多个光照强度下获取的图像中的每幅图像的灰度标准差；
光照强度确定单元84用于根据所述灰度标准差确定每个成像元件的所述用于检测的光照强度。
在一个示例性实施例中，光照强度单元84还可以包括归一化单元、优选光照强度范围确定单元、交集获取单元以及光照强度确定子单元，其中，归一化单元，用于对于每个成像元件归一化所述灰度标准差；优选光照强 度范围确定单元，用于根据归一化的灰度标准差及其与多个光照强度之间的对应关系，确定每个成像元件的优选光照强度范围；交集获取单元，用于获取所述至少一个成像元件的优选光照强度范围之间的交集；光照强度确定子单元，用于根据所述交集确定每个成像元件的所述用于检测的光照强度。
在一个示例性实施例中，优选光照强度范围确定单元还用于：将等于预定值的归一化的灰度标准差所对应的光照强度之间的范围确定为每个成像元件的优选光照强度范围。
在一个示例性实施例中，所述交集获取单元还用于：判断各个成像元件的所述优选光照强度范围之间是否存在交集，若存在，则获取所述至少一个成像元件的优选光照强度范围之间的交集；否则，逐渐减小所述预定值，直到获取的各个成像元件的优选光照强度范围之间存在交集。
在一个示例性实施例中，预定值取值为大于或等于0.8。
在一个示例性实施例中，光照强度确定子单元还用于：将所述交集中的中间值确定为每个成像元件的用于检测的光照强度。
光照强度确定单元84还用于：对于每个成像元件，将灰度标准差中最大的灰度标准差对应的光照强度确定为每个成像元件的用于检测的光照强度。
通过本文描述的实施例提供的确定用于检测的光照强度的装置，可以确定用于检测的光照强度。具体地，采用与上述实施例描述的和图4-图6示出的确定用于检测的光照强度的方法来确定光照强度。因此，在上述实施例中参照图4-图6对确定用于检测的光照强度的方法及其产生的优点的解释、说明同样适于本实施例。
在进一步的实施例中，还提供一种光学检测装置，其用于对待检测对象进行自动光学检测。该光学检测装置包括前述实施例提供的确定用于检测的光照强度的装置。
由于该光学检测装置包括前述实施例提供的确定用于检测的光照强度的装置，在前述实施例中对确定用于检测的光照强度的装置的解释、说明 同样适于该实施例。
实例
为使本公开的目的、技术方案和优点更加清楚，下面通过具体的示例详细说明本公开实施例提供的确定用于检测的光照强度的方法。
在该实例中，通过一台具有19个反射式摄像机(Reflective Camera)的自动光学检测装置对彩膜基板上的保护层进行检测，以确定用于检测的光照强度。进一步地，可以使用该确定的光照强度对彩膜基板上的保护层进行批量检测。
图9示意性示出在一个实例中的确定用于检测的光照强度的方法的流程图。在该实例中，将光照强度的设定为从10开始以10为间隔逐渐增加到250，在该情况下，每个摄像机可以在25个不同光照强度下拍摄25张图像。如图9所示，确定用于检测的光照强度的方法包括以下步骤：
步骤91：采集19个摄像机在不同反射光照强度下对待检测样品拍摄的图像；
步骤92：对于每个摄像机，通过图像处理软件计算每张图像的灰度标准差；
步骤93：对于每个摄像机，绘制灰度标准差-光照强度曲线；
在该步骤93中，可以对灰度标准差作归一化处理，在这种情况下，可以绘制归一化的灰度标准差-光照强度曲线(σ-I曲线)。图10中示出了对应于摄像机1/3/7/11/15/19的σ-I曲线，在图10中，纵坐标为归一化的灰度标准差，横坐标为光照强度；
步骤94：设定a＝1，判断当σ＝a时各个摄像机的相应光照强度是否相同，若是，则将该光照强度确定为用于检测的光照强度；否则，执行步骤95；
步骤95：以0.02为间隔减小a的取值；
步骤96：判断a是否小于预定阈值(如0.8)，若是，则调试设备，然后返回步骤91；若否，执行步骤97；
步骤97：获取σ＝a所对应的两个光照强度I1和I2之间的光照强度范 围作为优选光照强度范围，并判断获取的各个摄像机的优选光照强度范围是否存在交集，若是，则将交集的中间值确定为用于检测的光照强度；否则，返回步骤95；
在步骤96中，如果a小于预定阈值时，依然没有找到交集，则说明设备存在问题，可以对设备进行调试，例如调节摄像机镜头的焦点位置、调节摄像机增益等。
在该实例中，当σ＝a＝0.94时，各个摄像机的光照强度范围具有交集[148,168]，因此该自动光学检测装置的优选光照强度范围为[148,168]，将该优选光照强度范围的中间值158设定为用于检测的光照强度。使用该光照强度对待检测对象进行自动光学检测可以提高检测的准确性。
除非上下文中另外明确地指出，否则在本文和所附权利要求中所使用的词语的单数形式包括复数，反之亦然。因而，当提及单数时，通常包括相应术语的复数。相似地，措辞“包含”和“包括”将解释为包含在内而不是独占性地。同样地，术语“包括”和“或”应当解释为包括在内的，除非本文中明确禁止这样的解释。在本文中使用术语“实例”之处，特别是当其位于一组术语之后时，所述“实例”仅仅是示例性的和阐述性的，且不应当被认为是独占性的或广泛性的。
以上为了说明和描述的目的提供了实施例的前述描述。其并不旨在是穷举的或者限制本申请。特定实施例的各个元件或特征通常不限于特定的实施例，但是，在合适的情况下，这些元件和特征是可互换的并且可用在所选择的实施例中，即使没有具体示出或描述。同样也可以以许多方式来改变。这种改变不能被认为脱离了本申请，并且所有这些修改都包含在本申请的范围内。

Claims (19)

  1. 一种确定用于检测的光照强度的方法，包括：
    获取至少一个成像元件中的每个成像元件在多个光照强度下对待检测样品拍摄的图像；
    对于每个成像元件，计算在所述多个光照强度下获取的图像中的每幅图像的灰度标准差；
    根据所述灰度标准差确定每个成像元件的所述用于检测的光照强度。
  2. 根据权利要求1所述的方法，其中，所述至少一个成像元件中的每个成像元件被配置为对所述待检测样品的不同区域拍摄图像。
  3. 根据权利要求2所述的方法，其中，根据所述灰度标准差确定每个成像元件的所述用于检测的光照强度包括：
    对于每个成像元件，归一化所述灰度标准差；
    根据归一化的灰度标准差及其与所述多个光照强度之间的对应关系，确定每个成像元件的优选光照强度范围；
    获取所述至少一个成像元件的优选光照强度范围之间的交集；
    根据所述交集确定每个成像元件的所述用于检测的光照强度。
  4. 根据权利要求3所述的方法，其中，确定每个成像元件的所述优选光照强度范围包括：
    将等于预定值的归一化的灰度标准差所对应的光照强度之间的范围确定为每个成像元件的所述优选光照强度范围。
  5. 根据权利要求4所述的方法，其中，获取所述至少一个成像元件的优选光照强度范围之间的交集包括：
    判断各个成像元件的所述优选光照强度范围之间是否存在交集，若存在，则获取所述交集；否则，
    逐渐减小所述预定值，直到获取的各个成像元件的所述优选光照强度范围之间存在交集，并获取所述交集。
  6. 根据权利要求5所述的方法，其中，所述预定值不小于0.8。
  7. 根据权利要求3至6中任一项所述的方法，其中，根据所述交集确定每个成像元件的所述用于检测的光照强度包括：
    将所述交集中的中间值确定为每个成像元件的所述用于检测的光照强度。
  8. 根据权利要求1或2所述的方法，其中，根据所述灰度标准差确定每个成像元件的所述用于检测的光照强度包括：
    对于每个成像元件，将所述灰度标准差中最大的灰度标准差对应的光照强度确定为每个成像元件的所述用于检测的光照强度。
  9. 根据权利要求1至8中任一项所述的方法，其中，所述待检测样品为用于液晶显示器的彩膜基板、薄膜晶体管阵列基板、或印刷电路板。
  10. 一种光学检测方法，包括：
    从多个待检测对象中选择至少一个待检测对象作为待检测样品；
    使用所述待检测样品，根据权利要求1-9中任一项所述的方法确定至少一个成像元件中的每个成像元件的用于检测的光照强度；
    使用所确定的光照强度对所述多个待检测对象进行光学检测。
  11. 一种确定用于检测的光照强度的装置，包括：
    至少一个成像元件，用于对待检测样品拍摄图像；
    图像获取单元，用于获取每个成像元件在多个光照强度下对待检测样品拍摄的图像；
    计算单元，用于对于每个成像元件计算在所述多个光照强度下获取的图像中的每幅图像的灰度标准差；
    光照强度确定单元，用于根据所述灰度标准差确定每个成像元件的所述用于检测的光照强度。
  12. 根据权利要求11所述的装置，其中，所述至少一个成像元件中的每个成像元件用于对所述待检测样品的不同区域拍摄图像。
  13. 根据权利要求12所述的装置，其中，所述光照强度确定单元包括：
    归一化单元，用于对于每个成像元件归一化所述灰度标准差；
    优选光照强度范围确定单元，用于根据归一化的灰度标准差及其与所 述多个光照强度之间的对应关系，确定每个成像元件的优选光照强度范围；
    交集获取单元，用于获取所述至少一个成像元件的优选光照强度范围之间的交集；
    光照强度确定子单元，用于根据所述交集确定每个成像元件的所述用于检测的光照强度。
  14. 根据权利要求13所述的装置，其中，所述优选光照强度范围确定单元还用于：
    将等于预定值的归一化的灰度标准差所对应的光照强度之间的范围确定为每个成像元件的所述优选光照强度范围。
  15. 根据权利要求14所述的装置，其中，所述交集获取单元还用于：
    判断各个成像元件的所述优选光照强度范围之间是否存在交集，若存在，则获取所述至少一个成像元件的优选光照强度范围之间的交集；否则，
    逐渐减小所述预定值，直到获取的各个成像元件的所述优选光照强度范围之间存在交集。
  16. 根据权利要求15所述的装置，其中，所述预定值为大于或等于0.8。
  17. 根据权利要求13至16中任一项所述的装置，其中，所述光照强度确定子单元还用于：
    将所述交集中的中间值确定为每个成像元件的所述用于检测的光照强度。
  18. 根据权利要求11或12所述的装置，其中，所述光照强度确定单元还用于：
    对于每个成像元件，将所述灰度标准差中最大的灰度标准差对应的光照强度确定为每个成像元件的所述用于检测的光照强度。
  19. 一种光学检测装置，包括权利要求11至18中任一项所述的确定用于检测的光照强度的装置。
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Families Citing this family (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105911724B (zh) 2016-05-23 2018-05-25 京东方科技集团股份有限公司 确定用于检测的光照强度的方法和装置、及光学检测方法和装置
CN109949725B (zh) * 2019-03-06 2022-09-20 武汉精立电子技术有限公司 一种aoi系统图像灰度标准化方法及系统
US11022562B2 (en) * 2019-04-15 2021-06-01 Illinois Tool Works Inc. Methods and systems for vision system assisted inspections
CN110132976B (zh) * 2019-04-23 2022-03-25 合刃科技（深圳）有限公司 一种检测方法和检测装置
CN114450580A (zh) * 2019-10-02 2022-05-06 柯尼卡美能达株式会社 工件的表面缺陷检测装置及检测方法、工件的表面检查系统以及程序
KR20230067759A (ko) * 2021-11-08 2023-05-17 삼성디스플레이 주식회사 광학 검사 장치 및 이를 이용한 검사 방법

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2007043439A (ja) * 2005-08-03 2007-02-15 Casio Comput Co Ltd ホワイトバランス調整装置、及びホワイトバランス調整方法
CN101419176A (zh) * 2007-10-26 2009-04-29 比亚迪股份有限公司 表面瑕疵检测方法及装置
CN101556380A (zh) * 2008-04-08 2009-10-14 东捷科技股份有限公司 光源校正方法
CN101676695A (zh) * 2008-09-16 2010-03-24 中茂电子(深圳)有限公司 能以适当光度进行检测的图像检测系统以及方法
CN103905731A (zh) * 2014-03-26 2014-07-02 武汉烽火众智数字技术有限责任公司 一种宽动态图像采集方法及系统
JP2014211411A (ja) * 2013-04-22 2014-11-13 凸版印刷株式会社 暗視野光学系欠陥検査機
CN105911724A (zh) * 2016-05-23 2016-08-31 京东方科技集团股份有限公司 确定用于检测的光照强度的方法和装置、及光学检测方法和装置

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6627863B2 (en) * 2000-12-15 2003-09-30 Mitutoyo Corporation System and methods to determine the settings of multiple light sources in a vision system
KR100489658B1 (ko) * 2003-03-14 2005-05-17 삼성전자주식회사 광학측정장치 초점의 최적화방법, 이를 이용한 광학적불량 검출 방법 및 광학적 불량 검출 장치
US8654308B2 (en) * 2004-07-12 2014-02-18 Nikon Corporation Method for determining exposure condition, exposure method, exposure apparatus, and method for manufacturing device
US8111905B2 (en) * 2009-10-29 2012-02-07 Mitutoyo Corporation Autofocus video tool and method for precise dimensional inspection
US8542297B2 (en) * 2011-08-05 2013-09-24 Quality Vision International, Inc. Method for automatically adjusting the levels of illumination sources in an optical measurement machine
DE102013212495A1 (de) * 2013-06-27 2014-12-31 Robert Bosch Gmbh Verfahren und Vorrichtung zur Inspektion einer konturierten Fläche,insbesondere des Unterbodens eines Kraftfahrzeugs
DE102014113258A1 (de) * 2014-09-15 2016-03-17 Carl Zeiss Ag Verfahren zum Erzeugen eines Ergebnisbilds und optische Vorrichtung

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2007043439A (ja) * 2005-08-03 2007-02-15 Casio Comput Co Ltd ホワイトバランス調整装置、及びホワイトバランス調整方法
CN101419176A (zh) * 2007-10-26 2009-04-29 比亚迪股份有限公司 表面瑕疵检测方法及装置
CN101556380A (zh) * 2008-04-08 2009-10-14 东捷科技股份有限公司 光源校正方法
CN101676695A (zh) * 2008-09-16 2010-03-24 中茂电子(深圳)有限公司 能以适当光度进行检测的图像检测系统以及方法
JP2014211411A (ja) * 2013-04-22 2014-11-13 凸版印刷株式会社 暗視野光学系欠陥検査機
CN103905731A (zh) * 2014-03-26 2014-07-02 武汉烽火众智数字技术有限责任公司 一种宽动态图像采集方法及系统
CN105911724A (zh) * 2016-05-23 2016-08-31 京东方科技集团股份有限公司 确定用于检测的光照强度的方法和装置、及光学检测方法和装置

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