CN109712147A - A kind of interference fringe center line approximating method extracted based on Zhang-Suen image framework - Google Patents
A kind of interference fringe center line approximating method extracted based on Zhang-Suen image framework Download PDFInfo
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Abstract
The present invention discloses a kind of interference fringe center line approximating method extracted based on Zhang-Suen image framework, comprising: the image comprising interference fringe S1: is converted into grayscale image；S2: pre-processing grayscale image, obtains bianry image；S3: scanning all pixels of bianry image, the pixel structure neighborhood territory pixel template scan to each；S4: condition judgement is carried out to the neighborhood territory pixel template scanned using the condition distinguishing method of Zhang-Suen image framework extraction method and neighborhood territory pixel, under the premise of retaining the framework information of interference fringe, delete the redundant sub-pixels point at interference fringe edge, after iterating, the center line of interference fringe is obtained.Present invention uses the methods of concurrent operation, reduce the criterion of redundancy, the sum for only using neighborhood territory pixel point differentiates stripes edge pixels point, the operational efficiency of interference fringe fitting algorithm is improved significantly, the burr for reducing image after being fitted simultaneously, can quickly and accurately be fitted the center line of interference fringe.
Description
Technical field
The present invention relates to structure light imaging fields, are extracted more particularly, to one kind based on Zhang-Suen image framework
Interference fringe center line approximating method.
Background technique
Interference fringe analysis is one of the committed step in structure light imaging, can be with by analyzing interference fringe
Obtain striped quantity, fringe period, the information such as fringe spacing.Using these information, body surface defects detection, wave can be carried out
The measurements such as preceding detection, optical mirror plane detection.It has been widely used using the technology that interference fringe is detected.
The image acquired using optical camera, be by the identification ability of interference fringe image pretreatment and interference fringe
Obtain the effective information of interference fringe.And being fitted to interference fringe is that the primary study that an interference fringe image is handled is adjacent
Domain.Common method has Sobel Operator Method and Hilditch serial algorithm, and the above method is due to using serial computing and using
More criterion, so the problems such as being taken a long time there are algorithm.
Summary of the invention
The present invention in order to overcome at least one of the drawbacks of the prior art described above, provides a kind of based on Zhang-Suen image
The interference fringe center line approximating method of skeletal extraction, reduces calculation amount significantly, quickly and efficiently extracts interference fringe
Framework information.
In order to solve the above technical problems, technical scheme is as follows:
A kind of interference fringe center line approximating method extracted based on Zhang-Suen image framework, comprising the following steps:
S1: the image comprising interference fringe is converted into grayscale image；
S2: pre-processing grayscale image, obtains bianry image；
S3: scanning all pixels of bianry image, the pixel structure neighborhood territory pixel template scan to each；
S4: using the condition distinguishing method of Zhang-Suen image framework extraction method and neighborhood territory pixel to the neighbour scanned
Domain template pixel carries out condition judgement, under the premise of retaining the framework information of interference fringe, deletes the superfluous of interference fringe edge
Afterimage vegetarian refreshments after iterating, obtains the center line of interference fringe.
Zhang-Suen image framework extraction method can be reduced compared with serial algorithm significantly using concurrent operation
Calculation amount.Meanwhile Zhang-Suen image framework extraction method can utilize less and effective criterion mark striped
Edge pixel point reduces the burr of image after fitting.Interference fringe is extracted using Zhang-Suen image framework extraction method
Center line after can immediately arrive at the key messages such as interference fringe spacing.Zhang-Suen image framework extraction method passes through deletion
The redundant sub-pixels point of interference fringe, quickly and efficiently extracts the framework information of interference fringe.
Preferably, grayscale image is pre-processed in the step S2 the following steps are included:
S2.1: noise reduction is carried out to grayscale image using the median filtering that kernel is n × n；
S2.2: the binarization operation that threshold value is λ is carried out to filtered picture.
Preferably, the neighborhood territory pixel template of the step S3 includes 9 pixels, is 3 × 3 neighborhood territory pixel templates, wherein from
Left-to-right, from top to bottom, respectively P9 pixel, P2 pixel, P3 pixel, P8 pixel, P1 pixel, P4 pixel,
P7 pixel, P6 pixel, P5 pixel.
Preferably, the condition distinguishing of Zhang-Suen image framework extraction method and neighborhood territory pixel is utilized in the step S3
Method carries out condition judgement to the pixel scanned, wherein carrying out condition to the neighborhood territory pixel template centered on P1 pixel
Judgement, including the following conditions:
1)2≤N(P1)≤6, wherein N (P1) be P1 neighborhood of pixels P2, P3 ..., in P9 all non-zero pixels pixel
Number summation；
2)S(P1)=1, wherein S (P1) be in P1 neighborhood of pixels, using P2, P3 ..., P9 as the value of the pixel of sequence from
0 to 1 change frequency summation；
3)P2*P4*P6=0；
4)P2*P4*P8=0；
5)P4*P6*P8=0；
6)P2*P6*P8=0；
If P1 pixel meets above six conditions simultaneously, P1 pixel is deleted；If P1 pixel do not meet simultaneously with
Upper six conditions then retain P1 pixel, complete an iteration.
Preferably, with one in P2, P4, P6Position is 1,3 × 3 convolution kernel and neighborhood territory pixel template that remaining position is 0
Image convolution operation is carried out, judges whether pixel meets condition 3)；With one in P2, P4, P8Position is 1, remaining position is 0
3 × 3 convolution kernel and neighborhood territory pixel template carry out image convolution operation, judge whether pixel meets condition 4)；With one
In P4, P6, P8Position is 1, and 3 × 3 convolution kernel and neighborhood territory pixel template that remaining position is 0 carry out image convolution operation, judgement
Whether pixel meets condition 5)；With one in P2, P6, P8Position is 1,3 × 3 convolution kernel and neighborhood picture that remaining position is 0
Plain template carries out image convolution operation, judges whether pixel meets condition 6).
Compared with prior art, the beneficial effect of technical solution of the present invention is:
The method for having used concurrent operation differentiates the edge picture of interference fringe in 3 × 3 convolution kernel as concurrent operation
Element.Meanwhile reduce the criterion of redundancy, only use neighborhood territory pixel point and etc. direct condition to stripes edge pixels point
Differentiated.So can be quickly and accurately fitted to the center line of interference fringe.Using method of the invention, it is possible to
The operational efficiency of interference fringe fitting algorithm is improved significantly, while reducing the burr of image after fitting, overcomes fitting not
Complete problem.
Detailed description of the invention
Fig. 1 is a kind of interference fringe center line approximating method process signal extracted based on Zhang-Suen image framework
Figure.
Fig. 2 is 3 × 3 neighborhood territory pixel template schematic diagrames.
Fig. 3 is original interference striped 1.
Fig. 4 is the interference fringe 1 after the method for the present invention is fitted.
Fig. 5 is original interference striped 2.
Fig. 6 is the interference fringe 2 after the method for the present invention is fitted.
Specific embodiment
The attached figures are only used for illustrative purposes and cannot be understood as limitating the patent；
In order to better illustrate this embodiment, the certain components of attached drawing have omission, zoom in or out, and do not represent actual product
Size；
To those skilled in the art, it is to be understood that certain known features and its explanation, which may be omitted, in attached drawing
's.
The following further describes the technical solution of the present invention with reference to the accompanying drawings and examples.
Embodiment 1
The present embodiment provides a kind of interference fringe center line approximating methods extracted based on Zhang-Suen image framework, such as
Fig. 1, comprising the following steps:
S1: the image comprising interference fringe is converted into grayscale image；
S2: pre-processing grayscale image, obtains bianry image；
S3: scanning all pixels of bianry image, the pixel structure neighborhood territory pixel template scan to each；
S4: using the condition distinguishing method of Zhang-Suen image framework extraction method and neighborhood territory pixel to the neighbour scanned
Domain template pixel carries out condition judgement, under the premise of retaining the framework information of interference fringe, deletes the superfluous of interference fringe edge
Afterimage vegetarian refreshments after iterating, obtains the center line of interference fringe.
Grayscale image is pre-processed in step S2 the following steps are included:
S2.1: noise reduction is carried out to grayscale image using the median filtering that kernel is n × n；
S2.2: the binarization operation that threshold value is λ is carried out to filtered picture.
The neighborhood territory pixel template of step S3 includes 9 pixels, is 3 × 3 neighborhood territory pixel templates, wherein such as Fig. 2, Cong Zuozhi
The right side, from top to bottom, respectively P9 pixel, P2 pixel, P3 pixel, P8 pixel, P1 pixel, P4 pixel, P7 picture
Vegetarian refreshments, P6 pixel, P5 pixel.
Using the condition distinguishing method of Zhang-Suen image framework extraction method and neighborhood territory pixel to scanning in step S3
The neighborhood territory pixel template arrived carries out condition judgement, sentences wherein carrying out condition to the neighborhood territory pixel template centered on P1 pixel
Certainly, including the following conditions:
1)2≤N(P1)≤6, wherein N (P1) be P1 neighborhood of pixels P2, P3 ..., in P9 all non-zero pixels pixel
Number summation；
2)S(P1)=1, wherein S (P1) be in P1 neighborhood of pixels, using P2, P3 ..., P9 as the value of the pixel of sequence from
0 to 1 change frequency summation；
3)P2*P4*P6=0；
4)P2*P4*P8=0；
5)P4*P6*P8=0；
6)P2*P6*P8=0；
If P1 pixel meets above six conditions simultaneously, P1 pixel is deleted；If P1 pixel do not meet simultaneously with
Upper six conditions then retain P1 pixel and complete an iteration after each pixel completes primary judgement.
With one in P2, P4, P6Position is 1, and 3 × 3 convolution kernel and neighborhood territory pixel template that remaining position is 0 carry out figure
As convolution algorithm, judge whether pixel meets condition 3)；With one in P2, P4, P8Position is 1, remaining position is the 3 × 3 of 0
Convolution kernel and neighborhood territory pixel template carry out image convolution operation, judge whether pixel meets condition 4)；With one in P4, P6,
P8Position is 1, and 3 × 3 convolution kernel and neighborhood territory pixel template that remaining position is 0 carry out image convolution operation, judges pixel
Whether condition 5 is met)；With one in P2, P6, P8Position is 1,3 × 3 convolution kernel and neighborhood territory pixel template that remaining position is 0
Image convolution operation is carried out, judges whether pixel meets condition 6).
In the specific implementation process, threshold value λ=60 are enabled, the picture of original interference striped 1, such as Fig. 3, through this implementation will be had
After the method processing that example provides, the interference fringe 1 after being fitted, such as Fig. 4；The picture of original interference striped 2 will be had, is such as schemed
5, after method provided in this embodiment processing, interference fringe 2 after being fitted, such as Fig. 6；Through detecting, Zhang-Suen figure
As framework extraction method has preferable effect when being fitted interference fringe center line.By carrying out a small amount of calculating, effectively intend
The center line of interference fringe has been closed, and has removed most of noise.
The same or similar label correspond to the same or similar components；
The terms describing the positional relationship in the drawings are only for illustration, should not be understood as the limitation to this patent；
Obviously, the above embodiment of the present invention be only to clearly illustrate example of the present invention, and not be pair
The restriction of embodiments of the present invention.For those of ordinary skill in the art, may be used also on the basis of the above description
To make other variations or changes in different ways.There is no necessity and possibility to exhaust all the enbodiments.It is all this
Made any modifications, equivalent replacements, and improvements etc., should be included in the claims in the present invention within the spirit and principle of invention
Protection scope within.
Claims (5)
1. a kind of interference fringe center line approximating method extracted based on Zhang-Suen image framework, which is characterized in that including
Following steps:
S1: the image comprising interference fringe is converted into grayscale image；
S2: pre-processing grayscale image, obtains bianry image；
S3: scanning all pixels of bianry image, the pixel structure neighborhood territory pixel template scan to each；
S4: using the condition distinguishing method of Zhang-Suen image framework extraction method and neighborhood territory pixel to the neighborhood picture scanned
Plain template carries out condition judgement, under the premise of retaining the framework information of interference fringe, deletes the redundancy picture at interference fringe edge
Vegetarian refreshments after iterating, obtains the center line of interference fringe.
2. the interference fringe center line approximating method according to claim 1 extracted based on Zhang-Suen image framework,
It is characterized in that, grayscale image is pre-processed in the step S2 the following steps are included:
S2.1: noise reduction is carried out to grayscale image using the median filtering that kernel is n × n；
S2.2: the binarization operation that threshold value is λ is carried out to filtered picture, obtains bianry image.
3. the interference fringe center line approximating method according to claim 2 extracted based on Zhang-Suen image framework,
It is characterized in that, the neighborhood territory pixel template of the step S3 includes 9 pixels, it is 3 × 3 neighborhood territory pixel templates, wherein Cong Zuozhi
The right side, from top to bottom, respectively P9 pixel, P2 pixel, P3 pixel, P8 pixel, P1 pixel, P4 pixel, P7 picture
Vegetarian refreshments, P6 pixel, P5 pixel.
4. the interference fringe center line approximating method according to claim 3 extracted based on Zhang-Suen image framework,
It is characterized in that, utilizing the condition distinguishing method of Zhang-Suen image framework extraction method and neighborhood territory pixel in the step S3
Condition judgement is carried out to the neighborhood territory pixel template scanned, wherein carrying out item to the neighborhood territory pixel template centered on P1 pixel
Part judgement, including the following conditions:
1)2≤N(P1)≤6, wherein N (P1) be P1 neighborhood of pixels P2, P3 ..., in P9 all non-zero pixels number of pixels
Summation；
2)S(P1)=1, wherein S (P1) be in P1 neighborhood of pixels, using P2, P3 ..., P9 be the value of the pixel of sequence from 0 to 1
Change frequency summation；
3)P2*P4*P6=0；
4)P2*P4*P8=0；
5)P4*P6*P8=0；
6)P2*P6*P8=0；
If P1 pixel meets above six conditions simultaneously, P1 pixel is deleted；If P1 pixel does not meet above six simultaneously
A condition then retains P1 pixel and completes an iteration after each pixel completes primary judgement.
5. the interference fringe center line approximating method according to claim 4 extracted based on Zhang-Suen image framework,
It is characterized in that, with one in P2, P4, P6Position is 1, and 3 × 3 convolution kernel and neighborhood territory pixel template that remaining position is 0 carry out
Image convolution operation, judges whether pixel meets condition 3)；With one in P2, P4, P8Position is 1, remaining position be 03 ×
3 convolution kernel and neighborhood territory pixel template carries out image convolution operation, judges whether pixel meets condition 4)；With one in P4,
P6, P8Position is 1, and 3 × 3 convolution kernel and neighborhood territory pixel template that remaining position is 0 carry out image convolution operation, judges pixel
Whether point meets condition 5)；With one in P2, P6, P8Position is 1,3 × 3 convolution kernel and neighborhood territory pixel mould that remaining position is 0
Plate carries out image convolution operation, judges whether pixel meets condition 6).
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| CN111738936A (en) * | 2020-05-18 | 2020-10-02 | 浙江托普云农科技股份有限公司 | Image processing-based multi-plant rice spike length measuring method |
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| CN112308826A (en) * | 2020-10-23 | 2021-02-02 | 南京航空航天大学 | Bridge structure surface defect detection method based on convolutional neural network |
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