CN110298857A - A kind of celadon glazed thickness method for automatic measurement based on SD-OCT image - Google Patents
A kind of celadon glazed thickness method for automatic measurement based on SD-OCT image Download PDFInfo
- Publication number
- CN110298857A CN110298857A CN201910576067.2A CN201910576067A CN110298857A CN 110298857 A CN110298857 A CN 110298857A CN 201910576067 A CN201910576067 A CN 201910576067A CN 110298857 A CN110298857 A CN 110298857A
- Authority
- CN
- China
- Prior art keywords
- glaze layer
- celadon
- image
- pixel
- oct image
- 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
- 238000000034 method Methods 0.000 title claims abstract description 37
- 238000005259 measurement Methods 0.000 title claims abstract description 23
- 230000000877 morphologic effect Effects 0.000 claims abstract description 15
- 238000006243 chemical reaction Methods 0.000 claims abstract description 8
- 239000012634 fragment Substances 0.000 claims description 11
- 230000010339 dilation Effects 0.000 claims description 8
- 230000003628 erosive effect Effects 0.000 claims description 6
- 238000001914 filtration Methods 0.000 claims description 6
- 238000000926 separation method Methods 0.000 claims description 5
- 230000003044 adaptive effect Effects 0.000 claims description 3
- 230000008602 contraction Effects 0.000 claims description 3
- 238000003708 edge detection Methods 0.000 claims description 3
- 230000002708 enhancing effect Effects 0.000 claims description 3
- 238000000691 measurement method Methods 0.000 claims description 3
- 238000011946 reduction process Methods 0.000 claims description 3
- 238000007788 roughening Methods 0.000 claims description 3
- 238000001514 detection method Methods 0.000 abstract description 3
- 230000009897 systematic effect Effects 0.000 abstract description 2
- 238000004519 manufacturing process Methods 0.000 description 5
- 238000011161 development Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 238000003384 imaging method Methods 0.000 description 3
- 239000000919 ceramic Substances 0.000 description 2
- 210000003298 dental enamel Anatomy 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000000605 extraction Methods 0.000 description 2
- 229910052573 porcelain Inorganic materials 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000005336 cracking Methods 0.000 description 1
- 230000001066 destructive effect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000009659 non-destructive testing Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000012634 optical imaging Methods 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000003595 spectral effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B9/00—Measuring instruments characterised by the use of optical techniques
- G01B9/02—Interferometers
- G01B9/0209—Low-coherence interferometers
- G01B9/02091—Tomographic interferometers, e.g. based on optical coherence
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/02—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness
- G01B11/06—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness for measuring thickness ; e.g. of sheet material
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/70—Denoising; Smoothing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/13—Edge detection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/70—Determining position or orientation of objects or cameras
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Radiology & Medical Imaging (AREA)
- Image Analysis (AREA)
- Image Processing (AREA)
Abstract
The present invention discloses a kind of celadon glazed thickness method for automatic measurement based on SD-OCT image.Noise reduction and binary conversion treatment are carried out to the SD-OCT image of celadon glaze layer, optimize positioned glaze layer coboundary comprising the most target positioning glaze layer coboundary of pixel and by Lagrange's interpolation in detection image；The background and target of image are separated and carry out image flaky process；Glaze layer lower boundary is positioned by morphological operation；The pixel axial resolution of different type celadon glaze layer SD-OCT image is calibrated by SD-OCT systematic survey glazed thickness；It calculates the pixel distance between glaze layer up-and-down boundary and combines corresponding pixel axial resolution, calculate glazed thickness.The present invention realizes the measurement to various types celadon glazed thickness by the pixel axial resolution of calibration different type celadon glaze layer SD-OCT image, has stronger robustness and applicability, effectively raises the efficiency to the measurement of celadon glazed thickness.
Description
Technical field
The invention belongs to the automatic measurement fields of celadon glazed thickness, and in particular to a kind of blueness based on SD-OCT image
Enamel layer method for measuring thickness.
Background technique
The manufacture craft of celadon is the tidemark in China's porcelain making history, possesses huge market value.Since modern times,
Different degrees of stagnation is also encountered in the development of celadon manufacture craft, high-quality works are few, and yield rate is low to hinder dragon's fountain
The development of celadon.In actual production, glazed thickness influences the quality of ceramics, with the increase of glazed thickness, glaze color saturation
Increase, while glazed thickness influences the glaze stress between glaze layer and carcass.Glazed thickness is controlled, glaze layer can be effectively improved and prevent
Cracking improves the quality of celadon, therefore in celadon production, the measurement of glazed thickness then becomes a kind of having for detection celadon quality
Efficacious prescriptions method.
Spectral domain optical coherence chromatographic imaging (SD-OCT) technology is a kind of former based on confocal microscope and Michelson interference
The novel optical imaging technique of reason can show the near surface structure of glaze layer, tool by detecting the back-scattering light of celadon
There is the characteristics of high-resolution and non-destructive testing.Currently, SD-OCT imaging technique has been successfully applied to the structural research of ceramics, pottery
Porcelain classification and Qualitative Identification.By combining SD-OCT imaging technique and image processing techniques to can be realization to celadon glazed thickness
In real time, nothing undermines precise measurement, and measurement position is not limited.Therefore there is important research to the development of celadon manufacture craft
With reference value.
Summary of the invention
The problem of being directed to background technique, the present invention provides a kind of celadon glaze thickness based on SD-OCT image
Measurement method is spent, the thickness for measuring celadon glaze layer precisely in real time is realized, while cooperating the method for celadon glazing, to effectively improve
Celadon quality improves celadon yield rate and has established technical foundation.
The present invention carries out noise reduction and binary conversion treatment by the SD-OCT image to celadon glaze layer, includes picture in detection image
The position of plain at most target, using the pixel of each column topmost of this target as glaze layer coboundary pixel, and it is bright by glug
The positioned glaze layer coboundary of day interpolation method optimization.Separate picture background is with target and to progress image flaky process.Pass through
Enhance the grey-scale contrast of flattening image, combining form operation positioning glaze layer lower boundary.Pass through OCT systematic survey glaze thickness
The pixel axial resolution of degree calibration different type celadon glaze layer SD-OCT image.Pixel between celadon glaze layer up-and-down boundary away from
Product from the pixel axial resolution with corresponding type celadon glaze layer SD-OCT image is celadon glazed thickness.Key is
The logic of the pixel axial resolution of calculated different type celadon glaze layer SD-OCT image, software algorithm and whole flow process.
The technical solution adopted by the present invention the following steps are included:
Step 1) acquires the SD-OCT image of different types of celadon glaze layer；
Step 2) carries out noise reduction to the celadon glaze layer SD-OCT image that step 1) acquires；
Glaze layer coboundary in the celadon glaze layer SD-OCT image of step 3) positioning acquisition；
Celadon glaze layer SD-OCT image is carried out background separation and image flaky process by step 4)；
Glaze layer lower boundary in the celadon glaze layer SD-OCT image of step 5) positioning acquisition；
Step 6) calibrates the pixel axial resolution of different types of celadon glaze layer SD-OCT image；
Step 7) calculates glazed thickness.
The step 2) specifically: the celadon glaze layer SD-OCT image that step 1) is acquired using the template that size is 3 × 5
Carry out median filtering.
The step 3) specifically:
3.1) using OSTU method calculate celadon glaze layer SD-OCT image binarization threshold t, using binarization threshold t as
The threshold value of canny operator carries out edge detection to the SD-OCT image after step 2) noise reduction process, obtains bianry image Bw；
3.2) define a radius be 5 length in pixels circular configuration member se, using structural elements se to bianry image Bw into
Row closing operation of mathematical morphology obtains image fc, calculates as follows:
In formula, symbolIt indicates morphological dilation, completes the object in " growth " or " roughening " bianry image Bw；Symbol
Number Θ indicates morphological erosion operation, completes the object in " contraction " or " refinement " bianry image Bw；
3.3) each pixel listed first existing gray value and be 1 in image fc is searched for from top to bottom and records this point
As to match pixel point, and the line position to match pixel point for recording each column sets Top (i), and wherein i is indicated to match pixel
Column position where point；
Using be located in the most connected domain of number of pixels to match pixel point as the coboundary pixel of celadon glaze layer；If
It is not belonging to the coboundary pixel of celadon glaze layer to match pixel point, then updates line position using Lagrange's interpolation and sets Top's (i)
Value calculates as follows:
Top (i)=2 × Top (x)-Top (y)
Wherein, i indicates the column position to match pixel point；
If the column of i-th column the right and left, there are the coboundary pixel of celadon glaze layer, x indicates that distance i-th arranges nearest deposit
The left column of pixel in coboundary, y indicate that distance i-th arranges the right column of nearest glaze layer coboundary pixel；If the column on the i-th column left side are deposited
In coboundary pixel, coboundary pixel is not present in the column on the right, then it is nearest there are coboundary pixel to indicate that distance i-th arranges by x
Left column, y indicate that distance i-th arranges that time close there are the left columns of coboundary pixel；If glaze layer coboundary is not present in the column on the i-th column left side
Pixel, the column on the right are there are glaze layer coboundary pixel, then x indicates that distance i-th arranges that nearest there are the right sides of glaze layer coboundary pixel
Column, y indicate that distance i-th arranges that time close there are the right column of glaze layer coboundary pixel.
The step 4) specifically:
4.1) for the image after median filtering, column line position each in image is set to the gray value of the pixel less than Top (i)
It resets, separate picture background；
4.2) using the minimum value in Top (i) as the coboundary benchmark of celadon glaze layer, by translating up each column pixel
Position, set the line position of all coboundary pixels and be in same horizontal line, to obtain flattening image fl, simultaneously will
Position U of the minimum value as glaze layer coboundary in Top (i), the measurement for celadon glazed thickness.
The step 5) is described specifically:
5.1) it using the grey-scale contrast of contrast limited adaptive histogram equalization method enhancing flattening image fl, obtains
To the enhanced image fa of grey-scale contrast, morphology opening operation then is carried out to image fa using structural elements se, obtains image
The calculating of fo, morphology opening operation are as follows:
In formula, symbolIndicate that morphological dilation, symbol Θ indicate morphological erosion operation；
5.2) using flattening image fl as mask, continuous expansive working, completion morphology image are carried out to image fo
It rebuilds, obtains image fr；
5.3) the circular configuration member that a radius is 3 length in pixels is defined, image fr is carried out using this circular configuration member
Morphological dilation obtains image fd；
5.4) binary conversion treatment is carried out to image fd using OSTU method, with behavior unit from the image Jing Guo binary conversion treatment
The bottommost of glaze layer is begun stepping through in fd, traverses every a line from the bottom to top, until the row traversed does not include glaze layer region
Pixel, then stop traversing and record this behavior and stop traversal row, count the line position for being located in each column and stopping traversal row lower section
The line number where the smallest pixel is set, and finds out the average value B of line number in all column, using B as the glaze layer of SD-OCT image
The line position of lower boundary is set, the measurement for celadon glazed thickness.
The step 6) specifically:
6.1) the celadon fragment of difference scan different types, obtains the section SD-OCT image of celadon fragment；
6.2) using the thickness T of glaze layer in the section SD-OCT image of the calliper to measure celadon fragment of SD-OCT systemx；
6.3) the celadon glaze layer SD-OCT image with section SD-OCT image the same area of celadon fragment is scanned, is pressed simultaneously
The up-and-down boundary of step (2)-step (5) method positioning celadon glaze layer simultaneously finds out the pixel distance D between up-and-down boundary, calculates
It is as follows:
D=B-U
Wherein, B is glaze layer lower boundary, and U is glaze layer coboundary；
6.4) the pixel axial resolution of different types of celadon glaze layer SD-OCT image is found out respectively using following formula
Prx:
The step 7) specifically: calculate glaze layer in the celadon glaze layer SD-OCT image of step 1) scanning according to the following formula
Pixel distance D between up-and-down boundary:
D=B-U
Wherein, B is glaze layer lower boundary, and U is glaze layer coboundary；
The pixel of celadon glaze layer SD-OCT image identical with the celadon glaze channel type that step 1) scans is chosen in step 6)
Axial resolution Prx, it is calculated using the following equation different types of celadon glazed thickness Tx:
Wherein, PrxFor the pixel axial resolution of the celadon glaze layer SD-OCT image of step 1) scanning, D is glaze layer or more
Pixel distance D between boundary.
The beneficial effects of the present invention are:
1) present invention can be got rid of with the glazed thickness of any position for accurately measuring different type celadon of real non-destructive
The problem of celadon glazing uniformity only could be judged by glazing number.
2) present invention is accurately positioned the position of celadon glaze layer up-and-down boundary in the picture, by carrying out at flattening to image
Reason, overcomes error problem caused by curvature measurement, ensure that the accuracy and robustness of measurement, while to different type celadon
The pixel axial resolution of glaze layer SD-OCT image is calibrated, and the thickness measure of different type celadon glaze layer is completed, and is improved
The universality that the method for the present invention measures celadon glazed thickness.
Detailed description of the invention
Fig. 1 is the flow chart of the method for the present invention.
Fig. 2 is the celadon sample pictorial diagram of glazed thickness to be measured, and (a)-(f) respectively corresponds a kind of sample.
Fig. 3 is the celadon sample SD-OCT image of glazed thickness to be measured, and (a)-(f) is corresponding in turn to (a)-(f) in Fig. 2.
Fig. 4 is the SD-OCT image of embodiment background separation and image flattening, and (a)-(f) is corresponding in turn in Fig. 3
(a)-(f)。
Fig. 5 is embodiment celadon glaze layer cross section figure and corresponding SD-OCT image, and (a) is celadon glaze layer cross section figure, is (b)
The SD-OCT image of celadon glaze layer cross section.
Fig. 6 is the extraction effect figure of embodiment celadon glaze layer up-and-down boundary, and (a)-(f) is corresponding in turn to (a)-in Fig. 3
(f)。
Specific embodiment
The present invention will be described in further detail with reference to the accompanying drawings and embodiments.
Specific embodiment:
A kind of celadon glazed thickness measurement method based on SD-OCT image, comprising the following steps:
1) the SD-OCT image of different types of celadon glaze layer is acquired；
The SD-OCT of the OQ LabScope system acquisition different type celadon glaze layer produced using Lumedica company is schemed
Picture, scanning range are set as 3.5mm, and acquired image is having a size of 512pixel*512pixel.Fig. 2 is glazed thickness to be measured
Celadon sample pictorial diagram, (a)-(f) respectively correspond a kind of sample；Fig. 3 is the celadon glaze layer SD-OCT figure of glazed thickness to be measured
Picture, (a)-(f) are corresponding in turn to (a)-(f) in Fig. 2.
2) carry out noise reduction to the celadon glaze layer SD-OCT image of acquisition: the template for the use of size being 3 × 5 is to the blueness of step 1)
Enamel layer SD-OCT image carries out median filtering.
3) the glaze layer coboundary in the celadon glaze layer SD-OCT image of positioning acquisition；
3.1) using OSTU method calculate celadon glaze layer SD-OCT image binarization threshold t, using binarization threshold t as
The threshold value of canny operator carries out edge detection to the SD-OCT image after step 2) noise reduction process, obtains bianry image Bw；
3.2) define a radius be 5 length in pixels circular configuration member se, using structural elements se to bianry image Bw into
Row closing operation of mathematical morphology obtains image fc, calculates as follows:
In formula, symbolIt indicates morphological dilation, completes the object in " growth " or " roughening " bianry image Bw；Symbol
Number Θ indicates morphological erosion operation, completes the object in " contraction " or " refinement " bianry image Bw；
3.3) each pixel listed first existing gray value and be 1 in image fc is searched for from top to bottom and records this point
As to match pixel point, and the line position to match pixel point for recording each column sets Top (i), and wherein i is indicated to match pixel
Column position where point；
3.4) each adjacent pixel is searched with eight connection domain modes and form connected domain, obtain all connections in image
Domain；
3.5) using be located in the most connected domain of number of pixels to match pixel point as the coboundary picture of celadon glaze layer
Element；If being not belonging to the coboundary pixel of celadon glaze layer to match pixel point, being updated using Lagrange's interpolation should be wait be fitted
The line position of pixel sets the value of Top (i), calculates as follows:
Top (i)=2 × Top (x)-Top (y)
Wherein, i indicates the column position to match pixel point；
If the column of i-th column the right and left, there are the coboundary pixel of celadon glaze layer, x indicates that distance i-th arranges nearest deposit
The left column of pixel in coboundary, y indicate that distance i-th arranges the right column of nearest glaze layer coboundary pixel；If the column on the i-th column left side are deposited
In coboundary pixel, coboundary pixel is not present in the column on the right, then it is nearest there are coboundary pixel to indicate that distance i-th arranges by x
Left column, y indicate that distance i-th arranges that time close there are the left columns of coboundary pixel；If glaze layer coboundary is not present in the column on the i-th column left side
Pixel, the column on the right are there are glaze layer coboundary pixel, then x indicates that distance i-th arranges that nearest there are the right sides of glaze layer coboundary pixel
Column, y indicate that distance i-th arranges that time close there are the right column of glaze layer coboundary pixel.
4) celadon glaze layer SD-OCT image is subjected to background separation and image flaky process；
4.1) value of Top (i) is corresponded in the image after median filtering, column line position each in image is set and is less than
The gray value of the pixel of Top (i) is reset, separate picture background；
4.2) using the minimum value in Top (i) as the coboundary benchmark of celadon glaze layer, by translating up each column pixel
Position, set the line position of all coboundary pixels and be in same horizontal line, to obtain flattening image fl, simultaneously will
Position U of the minimum value as glaze layer coboundary in Top (i), the measurement for celadon glazed thickness.Fig. 4 be background separation and
SD-OCT image after image flaky process, (a)-(f) are corresponding in turn to (a)-(f) in Fig. 3.
5) the glaze layer lower boundary of celadon glaze layer SD-OCT image is positioned；
5.1) it using the grey-scale contrast of contrast limited adaptive histogram equalization method enhancing flattening image fl, obtains
To the enhanced image fa of grey-scale contrast, morphology opening operation then is carried out to image fa using structural elements se, obtains image
The calculating of fo, morphology opening operation are as follows:
In formula, symbolIndicate that morphological dilation, symbol Θ indicate morphological erosion operation；
5.2) using flattening image fl as mask, continuous expansive working, completion morphology image are carried out to image fo
It rebuilds, obtains image fr；
5.3) the circular configuration member that a radius is 3 length in pixels is defined, image fr is carried out using this circular configuration member
Morphological dilation obtains image fd；
5.4) binary conversion treatment is carried out to image fd using OSTU method, with behavior unit from the image Jing Guo binary conversion treatment
The bottommost of glaze layer is begun stepping through in fd, traverses every a line from the bottom to top, until the row traversed does not include glaze layer region
Pixel, then stop traversing and record this behavior and stop traversal row, count the line position for being located in each column and stopping traversal row lower section
The line number where the smallest pixel is set, and finds out the average value B of line number in all column, using B as the glaze layer of SD-OCT image
The line position of lower boundary is set, the measurement for celadon glazed thickness.
6) the pixel axial resolution of different types of celadon glaze layer SD-OCT image is calibrated；
6.1) sweep parameter for the OQ LabScope system that setting Lumedica company produces: transversal scanning range
3.5mm exports picture size 512pixel*512pixel, and the celadon fragment of scan different types, obtains the section of fragment respectively
SD-OCT image.Fig. 5 is embodiment celadon glaze layer cross section figure and corresponding SD-OCT image, and (a) is celadon glaze layer cross section figure,
(b) be celadon glaze layer cross section SD-OCT image；
6.2) using the thickness T of the included calliper to measure different type celadon glaze layer of SD-OCT systemx；
6.3) for the same area of the celadon fragment section SD-OCT image scanned, celadon is scanned according to step (1)
The SD-OCT image of glaze layer, while according to (2)-(5) described step positioning glaze layer up-and-down boundary and finding out between up-and-down boundary
Pixel distance D is calculated as follows:
D=B-U
Wherein, B is glaze layer lower boundary, and U is glaze layer coboundary；
6.4) the pixel axial resolution of different types of celadon glaze layer SD-OCT image is found out respectively using following formula
Prx:
7) glazed thickness is calculated.
Calculate the pixel distance in the celadon glaze layer SD-OCT image of step 1) acquisition between the up-and-down boundary of celadon glaze layer
D, in conjunction with the pixel axial resolution of the celadon glaze layer SD-OCT image of institute's scan type in step 6), using described in step 6.4)
Formula calculates different types of celadon glazed thickness Tx.Fig. 6 is the extraction effect figure of celadon glaze layer up-and-down boundary, (a)-(f) according to
(a)-(f) in secondary corresponding diagram 3.
Claims (7)
1. a kind of celadon glazed thickness method for automatic measurement based on SD-OCT image, which comprises the following steps:
Step 1) acquires the SD-OCT image of different types of celadon glaze layer；
Step 2) carries out noise reduction to the celadon glaze layer SD-OCT image that step 1) acquires；
Glaze layer coboundary in the celadon glaze layer SD-OCT image of step 3) positioning acquisition；
Celadon glaze layer SD-OCT image is carried out background separation and image flaky process by step 4)；
Glaze layer lower boundary in the celadon glaze layer SD-OCT image of step 5) positioning acquisition；
Step 6) calibrates the pixel axial resolution of different types of celadon glaze layer SD-OCT image；
Step 7) calculates glazed thickness.
2. a kind of celadon glazed thickness measurement method based on SD-OCT image according to claim 1, it is characterised in that:
The step 2) specifically: the template for the use of size being 3 × 5 carries out intermediate value to the celadon glaze layer SD-OCT image that step 1) acquires
Filtering.
3. a kind of celadon glazed thickness method for automatic measurement based on SD-OCT image according to claim 1, feature
It is: the step 3) specifically:
3.1) the binarization threshold t that celadon glaze layer SD-OCT image is calculated using OSTU method, using binarization threshold t as canny
The threshold value of operator carries out edge detection to the SD-OCT image after step 2) noise reduction process, obtains bianry image Bw；
3.2) the circular configuration member se that a radius is 5 length in pixels is defined, shape is carried out to bianry image Bw using structural elements se
State closed operation obtains image fc, calculates as follows:
Fc=(Bw ⊕ se) Θ se
In formula, symbol ⊕ indicates morphological dilation, completes the object in " growth " or " roughening " bianry image Bw；Symbol Θ
It indicates morphological erosion operation, completes the object in " contraction " or " refinement " bianry image Bw；
3.3) each pixel listed first existing gray value and be 1 in image fc is searched for from top to bottom and records this conduct
To match pixel point, and the line position to match pixel point for recording each column sets Top (i), and wherein i is indicated to match pixel point institute
Column position；
3.4) each adjacent pixel is searched with eight connection domain modes and form connected domain, obtain all connected domains in image；
3.5) using be located in the most connected domain of number of pixels to match pixel point as the coboundary pixel of celadon glaze layer；If
The coboundary pixel of celadon glaze layer is not belonging to match pixel point, then updating using Lagrange's interpolation should be to match pixel point
Line position set the value of Top (i), calculate as follows:
Top (i)=2 × Top (x)-Top (y)
Wherein, i indicates the column position to match pixel point；
If the column of i-th column the right and left, there are the coboundary pixel of celadon glaze layer, x indicates that distance i-th arranges in nearest presence
The left column of boundary pixel, y indicate that distance i-th arranges the right column of nearest glaze layer coboundary pixel；If there are upper for the column on the i-th column left side
Coboundary pixel is not present in boundary pixel, the column on the right, then it is nearest there are the left column of coboundary pixel to indicate that distance i-th arranges by x,
Y indicates that distance i-th arranges that time close there are the left columns of coboundary pixel；If glaze layer coboundary pixel is not present in the column on the i-th column left side,
The column on the right are there are glaze layer coboundary pixel, then x indicates that distance i-th arranges that nearest there are the right column of glaze layer coboundary pixel, y tables
Show that distance i-th arranges that time close there are the right column of glaze layer coboundary pixel.
4. a kind of celadon glazed thickness method for automatic measurement based on SD-OCT image according to claim 3, feature
It is: the step 4) specifically:
4.1) for image after step 2) median filtering, column line position each in image is set to the gray value of the pixel less than Top (i)
It resets, separate picture background；
4.2) using the minimum value in Top (i) as the coboundary benchmark of celadon glaze layer, by the position for translating up each column pixel
It sets, sets the line position of all coboundary pixels and be in same horizontal line, to obtain flattening image fl, while by Top
(i) position U of the minimum value as glaze layer coboundary in, the measurement for celadon glazed thickness.
5. a kind of celadon glazed thickness method for automatic measurement based on SD-OCT image according to claim 1, feature
It is: the step 5) specifically:
5.1) using the grey-scale contrast of contrast limited adaptive histogram equalization method enhancing flattening image fl, ash is obtained
The enhanced image fa of contrast is spent, morphology opening operation then is carried out to image fa using structural elements se, obtains image fo, shape
The calculating of state opening operation is as follows:
Fo=(fa Θ se) ⊕ se
In formula, symbol ⊕ indicates that morphological dilation, symbol Θ indicate morphological erosion operation；
5.2) using flattening image fl as mask, expansive working is carried out to image fo, completion morphology image reconstruction obtains figure
As fr；
5.3) the circular configuration member that a radius is 3 length in pixels is defined, form is carried out to image fr using this circular configuration member
Expansive working is learned, image fd is obtained；
5.4) binary conversion treatment is carried out to image fd using OSTU method, with behavior unit from the image fd Jing Guo binary conversion treatment
The bottommost of glaze layer is begun stepping through, and traverses every a line from the bottom to top, until the row traversed does not include the picture of glaze layer region
Element then stops traversing and recording this behavior stopping traversal row, counts in each column and set most positioned at the line position for stopping traversing row lower section
Line number where small pixel, and the average value B of line number in all column is found out, B is following as the glaze layer of SD-OCT image
The line position on boundary is set, the measurement for celadon glazed thickness.
6. a kind of celadon glazed thickness method for automatic measurement based on SD-OCT image according to claim 1, feature
It is: the step 6) specifically:
6.1) the celadon fragment of difference scan different types, obtains the section SD-OCT image of celadon fragment；
6.2) using the thickness T of glaze layer in the section SD-OCT image of the calliper to measure celadon fragment of SD-OCT systemx；
6.3) the celadon glaze layer SD-OCT image with section SD-OCT image the same area of celadon fragment is scanned, while according to step
It is rapid 2)-up-and-down boundary of the method for step 5) positioning celadon glaze layer and find out the pixel distance D between up-and-down boundary, calculate such as
Under:
D=B-U
Wherein, B is glaze layer lower boundary, and U is glaze layer coboundary；
6.4) the pixel axial resolution Pr of different types of celadon glaze layer SD-OCT image is found out respectively using following formulax:
7. a kind of celadon glazed thickness method for automatic measurement based on SD-OCT image according to claim 1, feature
It is: the step 7) specifically: calculated in the celadon glaze layer SD-OCT image of step 1) scanning according to the following formula in glaze layer
Pixel distance D between lower boundary:
D=B-U
Wherein, B is glaze layer lower boundary, and U is glaze layer coboundary；
The pixel axis of celadon glaze layer SD-OCT image identical with the celadon glaze channel type that step 1) scans is chosen in step 6)
To resolution ratio Prx, then it is calculated using the following equation different types of celadon glazed thickness Tx:
Wherein, PrxFor step 1) scanning celadon glaze layer SD-OCT image pixel axial resolution, D be glaze layer up-and-down boundary it
Between pixel distance D.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910576067.2A CN110298857B (en) | 2019-06-28 | 2019-06-28 | Automatic celadon glaze layer thickness measuring method based on SD-OCT image |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910576067.2A CN110298857B (en) | 2019-06-28 | 2019-06-28 | Automatic celadon glaze layer thickness measuring method based on SD-OCT image |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110298857A true CN110298857A (en) | 2019-10-01 |
| CN110298857B CN110298857B (en) | 2021-06-04 |
Family
ID=68029410
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910576067.2A Active CN110298857B (en) | 2019-06-28 | 2019-06-28 | Automatic celadon glaze layer thickness measuring method based on SD-OCT image |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110298857B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113284133A (en) * | 2021-06-16 | 2021-08-20 | 北京瑞莱智慧科技有限公司 | Method, device and equipment for determining photovoltaic cell piece spacing and storage medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20110137611A (en) * | 2010-06-17 | 2011-12-23 | 한국해양연구원 | Method for model ice's thickness measuring |
| CN108519059A (en) * | 2018-04-20 | 2018-09-11 | 中国矿业大学 | Thermal barrier coating multi-layered thickness detection method based on reflection-type terahertz time-domain spectroscopic technology |
| CN109859199A (en) * | 2019-02-14 | 2019-06-07 | 浙江科技学院 | A kind of method of the fresh water pipless pearl quality testing of SD-OCT image |
| CN110196021A (en) * | 2019-01-16 | 2019-09-03 | 苏州大学 | Coating layer thickness and its application are measured based on Optical coherence tomography technology |
-
2019
- 2019-06-28 CN CN201910576067.2A patent/CN110298857B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20110137611A (en) * | 2010-06-17 | 2011-12-23 | 한국해양연구원 | Method for model ice's thickness measuring |
| CN108519059A (en) * | 2018-04-20 | 2018-09-11 | 中国矿业大学 | Thermal barrier coating multi-layered thickness detection method based on reflection-type terahertz time-domain spectroscopic technology |
| CN110196021A (en) * | 2019-01-16 | 2019-09-03 | 苏州大学 | Coating layer thickness and its application are measured based on Optical coherence tomography technology |
| CN109859199A (en) * | 2019-02-14 | 2019-06-07 | 浙江科技学院 | A kind of method of the fresh water pipless pearl quality testing of SD-OCT image |
Non-Patent Citations (3)
| Title |
|---|
| M.-L.YANG 等: "USING OPTICAL COHERENCE TOMOGRAPHY TO EXAMINE THE SUBSURFACE MORPHOLOGY OF CHINESE GLAZES", 《ARCHAEOMETRY》 * |
| 陈俊红 等: "基于光学相干层析图像的珍珠质厚度自动测量算法", 《黑龙江大学自然科学学报》 * |
| 高阳 等: "光学相干层析成像图像中角膜厚度的自动测量方法", 《光学学报》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113284133A (en) * | 2021-06-16 | 2021-08-20 | 北京瑞莱智慧科技有限公司 | Method, device and equipment for determining photovoltaic cell piece spacing and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110298857B (en) | 2021-06-04 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108921176B (en) | Pointer instrument positioning and identifying method based on machine vision | |
| JP6620477B2 (en) | Method and program for detecting cracks in concrete | |
| CN114723701A (en) | Gear defect detection method and system based on computer vision | |
| CN109658381A (en) | A kind of copper face defect inspection method of the flexible IC package substrate based on super-pixel | |
| US20090034827A1 (en) | Inspection device, inspection method, method of manufacturing color filter, and computer-readable storage medium containing inspection device control program | |
| CN104897071B (en) | A kind of twisted-pair feeder method for measuring pitch based on machine vision | |
| CN106780726A (en) | The dynamic non-rigid three-dimensional digital method of fusion RGB D cameras and colored stereo photometry | |
| CN106969708A (en) | A kind of detection means and method of aggregate quality morphology | |
| CN109540925B (en) | Complex ceramic tile surface defect detection method based on difference method and local variance measurement operator | |
| CN117274240B (en) | Bearing platform foundation concrete surface crack identification method | |
| CN111354047B (en) | Computer vision-based camera module positioning method and system | |
| CN108765433A (en) | One kind is for carrying high-precision leafy area measurement method | |
| CN117315289B (en) | Aeroengine blade contour edge detection method based on image processing | |
| CN109211918B (en) | Fabric bow weft detection method based on weft trend | |
| JP2014513292A (en) | Method and related system for preparing a quantitative video microscope | |
| CN109410205B (en) | Crack extraction method under complex pavement background | |
| WO2022178653A1 (en) | Biochip image analysis method and apparatus, and computer device and storage medium | |
| CN113034474A (en) | Test method for wafer map of OLED display | |
| JP2020169994A (en) | Method for optically detecting biomarkers | |
| CN113012105B (en) | Yarn hairiness detection and rating method based on image processing | |
| CN110298857A (en) | A kind of celadon glazed thickness method for automatic measurement based on SD-OCT image | |
| CN111968079B (en) | Three-dimensional pavement crack extraction method based on local extremum of section and segmentation sparsity | |
| CN110926339A (en) | Real-time three-dimensional measurement method based on one-time projection structured light parallel stripe pattern | |
| CN112241964B (en) | Light strip center extraction method for line structured light non-contact measurement | |
| CN110146027B (en) | Method for measuring thickness of celadon glaze layer of SD-OCT image |
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 |