CN111461230A - Dental model classification and identification method based on dental stl model and two-dimensional image registration - Google Patents
Dental model classification and identification method based on dental stl model and two-dimensional image registration Download PDFInfo
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Abstract
The invention discloses a dental model classification and identification method based on dental stl model and two-dimensional image registration, which comprises the following steps: s1: shooting a target dental model on a transmission line by using an industrial camera to obtain a shot two-dimensional image, and preprocessing the shot two-dimensional image; s2: carrying out perspective projection transformation on a three-dimensional model of a dental model three-dimensional stl file for printing a target dental model to obtain a transformation two-dimensional image; s3: and matching the shot two-dimensional image with the converted two-dimensional image, and identifying the dental model three-dimensional stl file corresponding to each target dental model, thereby realizing accurate sorting. The method can quickly and accurately sort a plurality of dental casts produced in batch to match with corresponding dental cast three-dimensional files.
Description
Technical Field
The invention relates to a dental model classification and identification method based on dental stl model and two-dimensional image registration, and belongs to the technical field of dentistry.
Background
With the wide application of digital technology, 3D printing and the like in the field of oral repair, oral medical treatment enters the digital era. In the digital preparation process of the denture, a digital dental model needs to be prepared. Due to the highly personalized characteristics of the dental cast, the 3D printing technology is the best choice for manufacturing the dental cast, and the popularization of the 3D printing technology shows great commercial potential in dental cast preparation.
When the 3D printer prints the dental cast, in order to improve efficiency, a plurality of dental casts are generally printed in batches. However, since there are often only slight differences between the dental casts, after mass production, how to quickly and accurately sort the dental casts of different users is a problem to be solved.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a dental model classification and identification method based on dental stl model and two-dimensional image registration, which can rapidly and accurately sort a plurality of dental models produced in batch and match corresponding dental model three-dimensional files.
In order to achieve the above object, the present invention provides a dental model classification recognition method based on dental stl model and two-dimensional image registration, comprising the following steps:
s1: shooting a target dental model on a transmission line by using an industrial camera to obtain a shot two-dimensional image, and preprocessing the shot two-dimensional image;
s2: carrying out perspective projection transformation on a three-dimensional model of a dental model three-dimensional stl file for printing a target dental model to obtain a transformation two-dimensional image;
s3: and matching the shot two-dimensional image with the converted two-dimensional image, and identifying the dental model three-dimensional stl file corresponding to each target dental model, thereby realizing accurate sorting.
Further, in step S1, an industrial camera is used to collect and store an image of the transfer line without the dental model as a background image, then the industrial camera is used to photograph the target dental model on the transfer line to obtain a target image, a background difference is made between the two images to segment a target dental model image area, an edge contour of the target dental model is extracted through a Canny edge detection operator, and a minimum circumscribed rectangle of the target dental model is obtained as a contour of the target dental model through a minimum circumscribed rectangle method.
Further, in step S1, the two-dimensional coordinates of the center point of the target dental model are determined according to the contour of the target dental model, and the placement angle of the target dental model in the captured two-dimensional image is obtained, and the captured two-dimensional image is corrected by an image rotation algorithm, so that the obtained captured two-dimensional image has the same direction as the target dental model.
Further, in step S1, a pixel difference between the background image and the target image is calculated by the following formula, a pixel having a pixel difference greater than a threshold is set to 0, a pixel having a pixel difference less than or equal to the threshold is set to 1, and a binarized image only including the target dental model region is obtained:
wherein f isk(x, y) represents an object image, bk(x, y) represents a background image, ThIs an image gray threshold, Rk(x, y) is a binarized image of the target dental model area.
Further, in step S2, the three-dimensional model in the dental model three-dimensional stl file is read in, and a transformed two-dimensional image of the three-dimensional model is calculated by the following formula in a perspective projection algorithm:
wherein E is the perspective viewpoint position, RTIs the inverse matrix of the perspective viewpoint pose R, X being a point in the three-dimensional model and Y being a point on the two-dimensional image plane.
Further, in step S3, a template matching algorithm is used to calculate a matching result of the captured two-dimensional image and the transformed two-dimensional image, which is calculated by the following formula:
wherein S (m, n) is a shot two-dimensional image, T (m, n) is a transformed two-dimensional image, and R is a correlation coefficient between the shot two-dimensional image and the transformed two-dimensional image.
Further, in step S3, a maximum value is selected from the correlation coefficients of the matching between the current captured two-dimensional image and all the transformed two-dimensional images, and the calculated result is that the corresponding dental model three-dimensional stl file is searched for the target dental model.
The dental model classification and identification method based on dental stl model and two-dimensional image registration identifies the dental model three-dimensional stl file corresponding to each target dental model by matching the shot two-dimensional image obtained by shooting the target dental model with the transformed two-dimensional image obtained by perspective projection of the dental model three-dimensional stl file, thereby meeting the classification and identification requirements, and being capable of rapidly and accurately sorting a plurality of dental models produced in batch to match corresponding users.
Drawings
The present invention will be further described and illustrated with reference to the following drawings.
Fig. 1 is a flowchart of a dental model classification recognition method based on dental stl model and two-dimensional image registration according to a preferred embodiment of the present invention.
Detailed Description
The technical solution of the present invention will be more clearly and completely explained by the description of the preferred embodiments of the present invention with reference to the accompanying drawings.
As shown in fig. 1, a dental model classification recognition method based on registration of a dental stl model and a two-dimensional image according to a preferred embodiment of the present invention includes the following steps:
s1: and shooting the target dental model on the transmission line by using an industrial camera to obtain a shot two-dimensional image, and preprocessing the shot two-dimensional image.
Specifically, an industrial camera is adopted in advance to collect images without a dental model on a transmission line as background images and store the background images, then the industrial camera is used for photographing a target dental model on the transmission line to obtain a target image, background difference is carried out on the two images, and a target dental model image area is divided. Then, calculating a pixel difference value between the background image and the target image through the following formula to obtain a binary image only containing the target dental model area:
wherein f isk(x, y) represents an object image, bk(x, y) represents a background image, ThIs an image gray threshold, Rk(x, y) is a binarized image of the target dental model area. Setting the pixel point with the pixel difference value larger than the threshold value as 0, and setting the pixel point with the pixel difference value smaller than or equal to the threshold value as 1, wherein the obtained new image is the binary image of the dental model image.
Extracting the effective characteristic of the edge contour of the target dental model through a Canny edge detection operator, obtaining the minimum circumscribed rectangle of the target dental model as the contour of the target dental model through a minimum circumscribed rectangle method, and extracting an image of a reserved dental model area. And then, calculating the coordinate and the rotation angle of the central point of the minimum circumscribed rectangle through the outline of the target dental model, determining the two-dimensional coordinate of the central point of the target dental model, simultaneously knowing the placement angle of the target dental model in the shot two-dimensional image, correcting the shot two-dimensional image through an image rotation algorithm, ensuring that the direction of the obtained shot two-dimensional image is the same as that of the target dental model, and reducing the running time of a matching algorithm.
S2: and carrying out perspective projection transformation on the three-dimensional model of the dental model three-dimensional stl file for printing the target dental model to obtain a transformed two-dimensional image.
Specifically, firstly, reading in a three-dimensional model in a dental model three-dimensional stl file, and calculating a transformation two-dimensional image of the three-dimensional model by a perspective projection algorithm through the following formula:
wherein E is the perspective viewpoint position, RTIs the inverse matrix of the perspective viewpoint pose R, X being a point in the three-dimensional model and Y being a point on the two-dimensional image plane. The profile details of the surface of the dental cast can be kept, and the accuracy of the subsequent matching is improved.
S3: and matching the shot two-dimensional image with the converted two-dimensional image, and identifying the dental model three-dimensional stl file corresponding to each target dental model.
Specifically, firstly, ensuring that the direction of a dental model in a shot two-dimensional image is the same as that of a transformed two-dimensional image, reducing the running time of a matching algorithm, then calculating the matching result of the shot two-dimensional image and the transformed two-dimensional image by using a template matching algorithm, and calculating by using the following formula:
wherein S (m, n) is a shot two-dimensional image, T (m, n) is a transformed two-dimensional image, and R is a correlation coefficient between the shot two-dimensional image and the transformed two-dimensional image
In step S3, the maximum value is selected from the correlation coefficients of the matching between the current captured two-dimensional image and all the transformed two-dimensional images, and the calculated result is the corresponding dental model three-dimensional stl file searched for the target dental model.
And identifying the three-dimensional stl file corresponding to each dental model, namely selecting the maximum value from the correlation coefficients matched between the current shot two-dimensional image and all the converted two-dimensional images, and searching the corresponding dental model three-dimensional stl file for the target dental model according to the calculated result.
The dental model classification and identification method based on dental stl model and two-dimensional image registration identifies the dental model three-dimensional stl file corresponding to each target dental model by matching the shot two-dimensional image obtained by shooting the target dental model with the transformed two-dimensional image obtained by perspective projection of the dental model three-dimensional stl file, thereby meeting the classification and identification requirements, and being capable of rapidly and accurately sorting a plurality of dental models produced in batch to match corresponding users.
The above detailed description merely describes preferred embodiments of the present invention and does not limit the scope of the invention. Without departing from the spirit and scope of the present invention, it should be understood that various changes, substitutions and alterations can be made herein by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims and their equivalents. The scope of the invention is defined by the claims.
Claims (7)
1. A dental model classification identification method based on dental stl model and two-dimensional image registration is characterized by comprising the following steps:
s1: shooting a target dental model on a transmission line by using an industrial camera to obtain a shot two-dimensional image, and preprocessing the shot two-dimensional image;
s2: carrying out perspective projection transformation on a three-dimensional model of a dental model three-dimensional stl file for printing a target dental model to obtain a transformation two-dimensional image;
s3: and matching the shot two-dimensional image with the converted two-dimensional image, and identifying the dental model three-dimensional stl file corresponding to each target dental model, thereby realizing accurate sorting.
2. The dental cast classification and identification method based on dental stl model and two-dimensional image registration as claimed in claim 1, wherein in step S1, an industrial camera is used to collect and store an image without dental cast on a transmission line as a background image in advance, then the industrial camera is used to photograph the target dental cast on the transmission line to obtain a target image, the background difference is made between the two images to segment the target dental cast image area, the edge contour of the target dental cast is extracted by Canny edge detection operator, and the minimum circumscribed rectangle of the target dental cast is obtained by minimum circumscribed rectangle method as the contour of the target dental cast.
3. The dental cast classification and identification method based on dental stl model and two-dimensional image registration as claimed in claim 2, wherein in step S1, the two-dimensional coordinates of the center point of the target dental cast are determined by the contour of the target dental cast, and the angle of the target dental cast in the captured two-dimensional image is known, and the captured two-dimensional image is modified by image rotation algorithm to make the captured two-dimensional image and the target dental cast have the same direction.
4. The dental model classification and identification method based on dental stl model and two-dimensional image registration as claimed in claim 3, wherein in step S1, the pixel difference between the background image and the target image is calculated by the following formula, the pixel with pixel difference greater than the threshold is set to 0, the pixel with pixel difference less than or equal to the threshold is set to 1, and the binarized image only containing the target dental model region is obtained:
wherein f isk(x, y) represents an object image, bk(x, y) represents a background image, ThIs an image gray threshold, Rk(x, y) is a binarized image of the target dental model area.
5. The dental model classification recognition method based on dental stl model and two-dimensional image registration as claimed in claim 1, wherein in step S2, reading in the three-dimensional model in the dental model three-dimensional stl file, calculating the transformed two-dimensional image of the three-dimensional model by the following formula with perspective projection algorithm:
wherein E is the perspective viewpoint position, RTIs the inverse matrix of the perspective viewpoint pose R, X being a point in the three-dimensional model and Y being a point on the two-dimensional image plane.
6. The dental model classification recognition method based on dental stl model and two-dimensional image registration as claimed in claim 1, wherein in step S3, the matching result of the captured two-dimensional image and the transformed two-dimensional image is calculated by using a template matching algorithm, and calculated by the following formula:
wherein S (m, n) is a shot two-dimensional image, T (m, n) is a transformed two-dimensional image, and R is a correlation coefficient between the shot two-dimensional image and the transformed two-dimensional image.
7. The dental model classification and identification method based on dental stl model and two-dimensional image registration as claimed in claim 6, wherein in step S3, the maximum value is selected from the matching correlation coefficients of the current captured two-dimensional image and all transformed two-dimensional images, and the calculated result is the corresponding dental model three-dimensional stl file searched for by the target dental model.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114419437A (en) * | 2022-01-12 | 2022-04-29 | 湖南视比特机器人有限公司 | Workpiece sorting system based on 2D vision and control method and control device thereof |
| CN118135117A (en) * | 2024-04-30 | 2024-06-04 | 先临三维科技股份有限公司 | Method, device, equipment and medium for generating region of three-dimensional model |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN101271469A (en) * | 2008-05-10 | 2008-09-24 | 深圳先进技术研究院 | Two-dimension image recognition based on three-dimensional model warehouse and object reconstruction method |
| US20160239631A1 (en) * | 2015-02-13 | 2016-08-18 | Align Technology, Inc. | Three-dimensional tooth modeling using a two-dimensional x-ray image |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN101271469A (en) * | 2008-05-10 | 2008-09-24 | 深圳先进技术研究院 | Two-dimension image recognition based on three-dimensional model warehouse and object reconstruction method |
| US20160239631A1 (en) * | 2015-02-13 | 2016-08-18 | Align Technology, Inc. | Three-dimensional tooth modeling using a two-dimensional x-ray image |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114419437A (en) * | 2022-01-12 | 2022-04-29 | 湖南视比特机器人有限公司 | Workpiece sorting system based on 2D vision and control method and control device thereof |
| CN118135117A (en) * | 2024-04-30 | 2024-06-04 | 先临三维科技股份有限公司 | Method, device, equipment and medium for generating region of three-dimensional model |
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