CN110458772B - Point cloud filtering method and device based on image processing and storage medium - Google Patents
Point cloud filtering method and device based on image processing and storage medium Download PDFInfo
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Abstract
The invention discloses a point cloud filtering method, a point cloud filtering device and a storage medium based on image processing, wherein scattered points of an obtained initial point cloud are filtered, so that the influence of the scattered points on subsequent processing is avoided; after uniquely numbering the initial point cloud coordinates corresponding to the filtered initial point cloud, because the point cloud coordinates are mapped into an image coordinate system, and the values of the initial point cloud coordinates are usually floating point type, the data types of the initial point cloud coordinates are converted into integer type, so that the mapping is more accurate; meanwhile, after the connected components are extracted from the mapping image, the connected domain with the most integer point cloud coordinates corresponding to the image coordinates in the connected domain is reserved, namely the unique number of the initial point cloud coordinates corresponding to the image coordinates in the connected domain is reserved, the filtered data corresponding to other connected domains is noise data, the point cloud recovered through the unique number is the filtered target point cloud, coordinate-by-coordinate comparison is not needed, the calculated amount is small, and point cloud noise is quickly filtered.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a point cloud filtering method and device based on image processing and a storage medium.
Background
In the fields of ancient building reconstruction, reverse engineering or measurement engineering of workpieces and the like, non-contact three-dimensional measurement equipment can acquire the shape information of an object under the condition of not contacting the object, the application is very wide, although the scanning precision is stably improved, the problems of lens distortion, inaccurate camera parameter estimation and the like are inevitably caused, the acquired shape information contains more noise, the shape information is usually presented in a point cloud form, therefore, the point cloud needs to be denoised, and the accuracy of subsequent work is ensured. The existing scheme usually processes point clouds based on a three-dimensional space, and removes noise by calculating the relationship between the initial point clouds, but the initial point clouds obtained by a three-dimensional measuring device are often huge in data volume, and the defects of large calculation amount, low efficiency and high complexity exist when the initial point clouds are directly processed.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention aims to provide a point cloud filtering method, a point cloud filtering device and a storage medium based on image processing, which can reduce the calculated amount of point cloud denoising and quickly and efficiently complete point cloud filtering.
The technical scheme adopted by the invention for solving the problems is as follows: in a first aspect, the invention provides a point cloud filtering method based on image processing, which comprises the following steps:
the method comprises the steps that a client side obtains an initial point cloud, and scattered points of the initial point cloud are filtered;
the client acquires an initial point cloud coordinate corresponding to the initial point cloud in a point cloud coordinate system, and numbers the initial point cloud coordinate to obtain a unique corresponding coordinate number of the initial point cloud coordinate;
the client converts the initial point cloud coordinate into an integer point cloud coordinate with an integer data type, establishes an image coordinate system and maps the integer point cloud coordinate into the image coordinate system;
the client acquires a mapping image formed by data in the image coordinate system, sets a connected domain with the most image coordinates corresponding to the integer point cloud coordinates as a target connected domain after extracting connected components from the mapping image, and filters other connected domains;
and acquiring a coordinate number included in the target connected domain, restoring the integer point cloud coordinate into a corresponding initial point cloud coordinate according to the coordinate number, and mapping the initial point cloud coordinate into the point cloud coordinate system to finish point cloud filtering.
Further, scattered points in the initial point cloud are filtered by a k-nearest neighbor algorithm.
Further, the image coordinate system is established according to the origin, the x axis and the y axis of the point cloud coordinate system.
Further, the coordinate value in the integer point cloud coordinate is a value obtained by rounding and rounding the coordinate value of the initial point cloud coordinate.
Further, before extracting the connected component from the mapping image, the method further includes: and performing a closing operation on the mapping image to close the fractured region.
In a second aspect, the invention provides an apparatus for performing an image processing based point cloud filtering method, comprising a CPU unit for performing the steps of:
the method comprises the steps that a client side obtains an initial point cloud, and scattered points of the initial point cloud are filtered;
the client acquires an initial point cloud coordinate corresponding to the initial point cloud in a point cloud coordinate system, and numbers the initial point cloud coordinate to obtain a unique corresponding coordinate number of the initial point cloud coordinate;
the client converts the initial point cloud coordinate into an integer point cloud coordinate with an integer data type, establishes an image coordinate system and maps the integer point cloud coordinate into the image coordinate system;
the client acquires a mapping image formed by data in the image coordinate system, sets a connected domain with the most image coordinates corresponding to the integer point cloud coordinates as a target connected domain after extracting connected components from the mapping image, and filters other connected domains;
and acquiring a coordinate number included in the target connected domain, restoring the integer point cloud coordinate into a corresponding initial point cloud coordinate according to the coordinate number, and mapping the initial point cloud coordinate into the point cloud coordinate system to finish point cloud filtering.
Further, the CPU unit is further configured to perform the steps of: and performing a closing operation on the mapping image to close the fractured region.
In a third aspect, the present invention provides an apparatus for performing an image processing-based point cloud filtering method, comprising at least one control processor and a memory for communicative connection with the at least one control processor; the memory stores instructions executable by the at least one control processor to enable the at least one control processor to perform the image processing based point cloud filtering method as described above.
In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions for causing a computer to perform the image processing-based point cloud filtering method as described above.
In a fifth aspect, the present invention also provides a computer program product comprising a computer program stored on a computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, cause the computer to perform the method for image processing based point cloud filtering as described above.
One or more technical schemes provided in the embodiment of the invention have at least the following beneficial effects: the invention provides a point cloud filtering method, a point cloud filtering device and a storage medium based on image processing, which are used for filtering scattered points of an acquired initial point cloud to avoid the influence of the scattered points on subsequent processing; after uniquely numbering the initial point cloud coordinates corresponding to the filtered initial point cloud, because the point cloud coordinates are mapped into an image coordinate system, and the value of the initial point cloud coordinates is usually a floating point type, the data type of the initial point cloud coordinates is converted into an integer type, so that the mapping is more accurate; meanwhile, after the connected components are extracted from the mapping image, the connected domain with the most integer point cloud coordinates corresponding to the image coordinates in the connected domain is reserved, namely the unique number of the initial point cloud coordinates corresponding to the image coordinates in the connected domain is reserved, the filtered data corresponding to other connected domains is noise data, the point cloud recovered through the unique number is the filtered target point cloud, coordinate-by-coordinate comparison is not needed, the calculated amount is small, and point cloud noise is filtered quickly.
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The invention is further illustrated with reference to the following figures and examples.
FIG. 1 is a flow chart of a method of an embodiment of the present invention;
FIG. 2 is an exemplary diagram of an initial point cloud according to an embodiment of the invention;
FIG. 3 is a diagram illustrating an effect of the initial point cloud after filtering scattered points according to an embodiment of the present invention;
FIG. 4 is a diagram illustrating an effect of mapping an image according to an embodiment of the present invention;
FIG. 5 is a diagram illustrating an effect of the embodiment of the present invention after performing a close operation on the mapping image;
FIG. 6 is a diagram illustrating an effect of obtaining a target connected domain according to an embodiment of the present invention;
FIG. 7 is an exemplary diagram of the effect of completing point cloud filtering according to an embodiment of the present invention;
FIG. 8 is a schematic diagram of an apparatus for performing an image processing-based point cloud filtering method according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
It should be noted that, if not conflicting, various features of the embodiments of the present invention may be combined with each other within the scope of the present invention. Additionally, while functional block divisions are performed in apparatus schematics, with logical sequences shown in flowcharts, in some cases, steps shown or described may be performed in sequences other than block divisions in apparatus or flowcharts.
It should be noted that the data of the present invention can be acquired by a conventional acquisition device in the market, and the present invention does not relate to the improvement of the acquisition device, and only processes the data acquired by the acquisition device.
Referring to fig. 1 to 7, a first embodiment of the present invention provides a point cloud filtering method based on image processing, including the following steps:
step S100, a client acquires an initial point cloud and filters scattered points of the initial point cloud;
step S200, the client acquires an initial point cloud coordinate corresponding to an initial point cloud in a point cloud coordinate system, and numbers the initial point cloud coordinate to obtain a coordinate number uniquely corresponding to the initial point cloud coordinate;
step S300, the client converts the initial point cloud coordinate into an integer point cloud coordinate with an integer data type, establishes an image coordinate system and maps the integer point cloud coordinate into the image coordinate system;
step S400, the client acquires a mapping image formed by data in the image coordinate system, extracts connected components from the mapping image, sets a connected domain with the largest image coordinate corresponding to the integer point cloud coordinate as a target connected domain, and filters other connected domains;
and S500, acquiring a coordinate number included in the target connected domain, restoring the integer point cloud coordinate into a corresponding initial point cloud coordinate according to the coordinate number, and mapping the initial point cloud coordinate into the point cloud coordinate system to finish point cloud filtering.
It should be noted that the point cloud obtained by the three-dimensional device has many scattered points, for example, the point objects shown in fig. 2 cause many scattered points, and if the point cloud is not filtered, the target point cloud is likely to cause large interference, so in this embodiment, it is preferable to preferentially perform the scattered point filtering after obtaining the initial point cloud, and the interference of the scattered points can be eliminated, and an exemplary diagram obtained after filtering is shown in fig. 3.
It should be noted that the initial point cloud coordinates are three-dimensional coordinates, that is, the initial point cloud coordinates include an x axis, a y axis and a z axis, so the initial point cloud coordinates in this embodiment can be expressed as (x, y, z), and the initial point cloud coordinates after numbering the initial point cloud coordinates in step S200 are (x, y, z), and then the initial point cloud coordinates are numbered in step S200 i ,y i ,z i ) The unique coordinate number is i, the value of the specific i is determined by the sequence of the initial point cloud coordinates, for example, when the values are arranged according to the sequence of the values of the x axis, the coordinate with the minimum value of the x axis is x 1 And so on, and will not be described herein again.
In this embodiment, the data type of the initial point cloud obtained by the acquisition device is usually a floating point type due to the requirement of precision, and if mapping is to be performed, the floating point type data needs to be converted into integer data.
It should be noted that, after the mapping is completed in step S300, after the floating point cloud coordinates are converted into integer coordinates, there is a case that one or more floating point coordinates correspond to one integer coordinate, that is, when the integer point cloud coordinates are mapped to the image coordinates, there is a case that one or more integer point cloud coordinates correspond to one image coordinate, and an effect diagram thereof is shown in fig. 4. However, the coordinate number corresponding to the integer point cloud coordinate is unique, and the image coordinate also corresponds to the integer point cloud coordinate and the coordinate number corresponding to the integer point cloud coordinate, so that the points corresponding to the integer point cloud coordinate can be distinguished.
It should be noted that, in this embodiment, preferably, in step S400, the number of integer point cloud coordinates corresponding to the image coordinates in each connected domain is counted, the connected domain with the largest number of integer point cloud coordinates corresponding to the image coordinates in the connected domain is reserved, that is, the coordinate number corresponding to the integer point cloud coordinates corresponding to the image coordinates in the connected domain is reserved, and other connected domains are filtered, that is, the coordinate numbers corresponding to the integer point cloud coordinates corresponding to the image coordinates in other connected domains are filtered, and an exemplary diagram of the effect is shown in fig. 6.
It should be noted that, the numbers corresponding to the integer point cloud coordinates retained in step S400 are restored to the corresponding initial point cloud coordinates, that is, the integer point cloud coordinates with inconsistent coordinate numbers in the connected domain are filtered out, so that noise point clouds are filtered out, and only the target point cloud is retained. Because each initial point cloud coordinate is numbered, the initial point cloud coordinate corresponding to the initial point cloud is found in the initial point cloud according to the number retained in step S400, so that point cloud filtering is realized, and an exemplary effect of the point cloud filtering is shown in fig. 7.
Further, in another embodiment of the present invention, the scattered points in the initial point cloud are filtered by a k-nearest neighbor algorithm.
It should be noted that the filtering of the scattered points can be completed through any algorithm, and the effect of filtering the scattered points can be achieved.
Further, in another embodiment of the present invention, the image coordinate system is established according to the origin, the x-axis and the y-axis of the point cloud coordinate system.
It should be noted that, in this embodiment, it is further preferable that the length H and the width W of the image coordinate system respectively satisfy the following formulas:
H＝max(y k )-min(y k )；k＝1,2,3…,n；
W＝max(x k )-min(x k )；k＝1,2,3…,n。
wherein x is k Subtracting the minimum value of the coordinate from the initial point cloud coordinate with the coordinate number of k to convert into an abscissa value, y, of the integer point cloud coordinate k The vertical coordinate of the integer point cloud coordinate is converted by subtracting the minimum value of the coordinate from the initial point cloud coordinate with the coordinate number of kAnd (5) carrying out value marking.
Further, in another embodiment of the present invention, the coordinate value in the integer point cloud coordinate is a value obtained by rounding the coordinate value of the initial point cloud coordinate.
It should be noted that rounding is preferable in this embodiment, and methods such as rounding up or rounding down may also be adopted, and the integer data may be obtained, and the specific manner may be adjusted according to actual requirements.
Referring to fig. 5, further, in another embodiment of the present invention, before extracting connected components from the mapping image, the method further includes: and performing a closing operation on the mapping image to close the fractured region.
Since the number of the fractured regions included in the mapped image is large, in this embodiment, it is preferable to perform closure operation on the fractured regions to improve the accuracy of the image, an effect schematic diagram of the method is shown in fig. 5, it should be noted that the closure operation is an algorithm in the prior art, and this embodiment does not involve algorithm improvement of the closure operation, and details are not described here.
Referring to fig. 8, a second embodiment of the present invention further provides an apparatus for performing a point cloud filtering method based on image processing, where the apparatus is a smart device, such as a smart phone, a computer, a tablet computer, and the like, and the embodiment is described by taking the computer as an example.
In this computer 8000 for performing an image processing based point cloud filtering method, a CPU unit 8100 is included, the CPU unit 8100 being configured to perform the following steps:
the method comprises the steps that a client side obtains an initial point cloud, and scattered points of the initial point cloud are filtered;
the client acquires an initial point cloud coordinate corresponding to the initial point cloud in a point cloud coordinate system, and numbers the initial point cloud coordinate to obtain a unique corresponding coordinate number of the initial point cloud coordinate;
the client converts the initial point cloud coordinate into an integer point cloud coordinate with an integer data type, establishes an image coordinate system and maps the integer point cloud coordinate into the image coordinate system;
the client acquires a mapping image formed by data in the image coordinate system, sets a connected domain with the most image coordinates corresponding to the integer point cloud coordinates as a target connected domain after extracting connected components from the mapping image, and filters other connected domains;
and acquiring a coordinate number included in the target connected domain, restoring the integer point cloud coordinate into a corresponding initial point cloud coordinate according to the coordinate number, and mapping the initial point cloud coordinate into the point cloud coordinate system to finish point cloud filtering.
Further, in another embodiment of the present invention, the CPU unit 8100 is further configured to perform the following steps: and performing a closing operation on the mapping image to close the fractured region.
The computer 8000 and the CPU unit 8100 may be connected by a bus or other means, and the computer 8000 further includes a memory, which is a non-transitory computer-readable storage medium and may be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as program instructions/modules corresponding to the apparatus for performing the point cloud filtering method based on image processing according to the embodiment of the present invention. The computer 8000 controls the CPU unit 8100 to execute various functional applications for executing the image processing-based point cloud filtering method and data processing, i.e., to implement the image processing-based point cloud filtering method of the above-described method embodiment, by running non-transitory software programs, instructions, and modules stored in the memory.
The memory may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created from use of the CPU unit 8100, and the like. Further, the memory may include high speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory optionally includes memory located remotely from CPU unit 8100, which may be connected to computer 8000 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The one or more modules are stored in the memory, and when executed by the CPU unit 8100, perform the point cloud filtering method based on image processing in the above-described method embodiment.
An embodiment of the present invention further provides a computer-readable storage medium, where computer-executable instructions are stored, and the computer-executable instructions are executed by the CPU unit 8100, so as to implement the above-mentioned point cloud filtering method based on image processing.
The above-described embodiments of the apparatus are merely illustrative, and the apparatuses described as separate components may or may not be physically separate, may be located in one place, or may be distributed over a plurality of network apparatuses. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
It should be noted that, since the apparatus for executing the point cloud filtering method based on image processing in the present embodiment is based on the same inventive concept as the above-mentioned point cloud filtering method based on image processing, the corresponding contents in the method embodiment are also applicable to the present apparatus embodiment, and are not described in detail here.
Through the above description of the embodiments, those skilled in the art will clearly understand that the embodiments may be implemented by software plus a general hardware platform. Those skilled in the art will appreciate that all or part of the processes in the methods of the above embodiments may be implemented by hardware related to instructions of a computer program, which may be stored in a computer-readable storage medium, and when executed, may include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read Only Memory (ROM), a Random Access Memory (RAM), or the like.
While the preferred embodiments of the present invention have been described, the present invention is not limited to the above embodiments, and those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention, and such equivalent modifications or substitutions are to be included within the scope of the present invention defined by the claims.
Claims (8)
1. A point cloud filtering method based on image processing is characterized by comprising the following steps: the method comprises the steps that a client side obtains an initial point cloud, and scattered points of the initial point cloud are filtered;
the client acquires an initial point cloud coordinate corresponding to an initial point cloud in a point cloud coordinate system, and numbers the initial point cloud coordinate to obtain a coordinate number uniquely corresponding to the initial point cloud coordinate;
the client converts the initial point cloud coordinate into an integer point cloud coordinate with an integer data type, establishes an image coordinate system and maps the integer point cloud coordinate into the image coordinate system;
the client acquires a mapping image formed by data in the image coordinate system, sets a connected domain with the maximum image coordinate corresponding to the integer point cloud coordinate as a target connected domain after extracting connected components from the mapping image, and filters other connected domains;
and acquiring a coordinate number included in the target connected domain, restoring the integer point cloud coordinate into a corresponding initial point cloud coordinate according to the coordinate number, and mapping the initial point cloud coordinate into the point cloud coordinate system to finish point cloud filtering.
2. The method of claim 1, wherein the filtering comprises: and filtering scattered points in the initial point cloud by a k nearest neighbor algorithm.
3. The point cloud filtering method based on image processing according to claim 1, wherein: the image coordinate system is established according to the original point, the x axis and the y axis of the point cloud coordinate system.
4. The method of claim 1, wherein the filtering comprises: and the coordinate value in the integer point cloud coordinate is a value obtained by rounding and rounding the coordinate value of the initial point cloud coordinate.
5. The method of claim 1, wherein before extracting the connected components from the mapping image, the method further comprises: and performing a closing operation on the mapping image to close the fractured region.
6. An apparatus for performing an image processing based point cloud filtering method, comprising a CPU unit for performing the steps of:
the method comprises the steps that a client side obtains an initial point cloud, and scattered points of the initial point cloud are filtered;
the client acquires an initial point cloud coordinate corresponding to an initial point cloud in a point cloud coordinate system, and numbers the initial point cloud coordinate to obtain a coordinate number uniquely corresponding to the initial point cloud coordinate;
the client converts the initial point cloud coordinate into an integer point cloud coordinate with an integer data type, establishes an image coordinate system and maps the integer point cloud coordinate into the image coordinate system;
the client acquires a mapping image formed by data in the image coordinate system, sets a connected domain with the most image coordinates corresponding to the integer point cloud coordinates as a target connected domain after extracting connected components from the mapping image, and filters other connected domains;
and acquiring a coordinate number included in the target connected domain, restoring the integer point cloud coordinate into a corresponding initial point cloud coordinate according to the coordinate number, and mapping the initial point cloud coordinate into the point cloud coordinate system to finish point cloud filtering.
7. The apparatus of claim 6, wherein the CPU unit is further configured to perform the following steps: and performing a closing operation on the mapping image to close the fractured region.
8. A computer-readable storage medium characterized by: the computer-readable storage medium stores computer-executable instructions for causing a computer to perform a method of image processing based point cloud filtering as claimed in any one of claims 1 to 5.
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| CN110458772B (en) * | 2019-07-30 | 2022-11-15 | 五邑大学 | Point cloud filtering method and device based on image processing and storage medium |
| CN112907164A (en) * | 2019-12-03 | 2021-06-04 | 北京京东乾石科技有限公司 | Object positioning method and device |
| CN111275633B (en) * | 2020-01-13 | 2023-06-13 | 五邑大学 | Point cloud denoising method, system, device and storage medium based on image segmentation |
| CN111275810B (en) * | 2020-01-17 | 2022-06-24 | 五邑大学 | K nearest neighbor point cloud filtering method and device based on image processing and storage medium |
| CN111340728B (en) * | 2020-02-26 | 2023-03-21 | 五邑大学 | Point cloud denoising method and device based on 3D point cloud segmentation and storage medium |
| CN117223031A (en) * | 2021-05-06 | 2023-12-12 | Oppo广东移动通信有限公司 | Point cloud encoding and decoding method, encoder, decoder and computer storage medium |
| CN117408913B (en) * | 2023-12-11 | 2024-02-23 | 浙江托普云农科技股份有限公司 | Method, system and device for denoising point cloud of object to be measured |
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