CN115077425B - Product detection equipment and method based on structured light three-dimensional vision - Google Patents
Product detection equipment and method based on structured light three-dimensional vision Download PDFInfo
- Publication number
- CN115077425B CN115077425B CN202211003889.XA CN202211003889A CN115077425B CN 115077425 B CN115077425 B CN 115077425B CN 202211003889 A CN202211003889 A CN 202211003889A CN 115077425 B CN115077425 B CN 115077425B
- Authority
- CN
- China
- Prior art keywords
- dimensional model
- standard
- dimensional
- coordinate
- acquisition device
- 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.)
- Active
Links
Images
Classifications
-
- 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
- G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
- G01B11/25—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. one or more lines, moiré fringes on the object
- G01B11/2518—Projection by scanning of the object
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
- G06T7/001—Industrial image inspection using an image reference approach
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/50—Depth or shape recovery
- G06T7/521—Depth or shape recovery from laser ranging, e.g. using interferometry; from the projection of structured light
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Quality & Reliability (AREA)
- Optics & Photonics (AREA)
- Length Measuring Devices By Optical Means (AREA)
Abstract
The invention provides a product detection device and method based on structured light three-dimensional vision, which comprises the steps of respectively constructing three-dimensional models of a detection object and an image acquisition device; respectively constructing a plurality of standard working models of the image acquisition device corresponding to a plurality of detection objects according to the three-dimensional model and historical working data of the image acquisition device; determining a first standard working model corresponding to the image acquisition device from a plurality of standard working models according to the three-dimensional model of the object to be detected; determining the working configuration parameters of the image acquisition device according to the first standard working model; acquiring a structured light image by using an image acquisition device; reconstructing a detection three-dimensional model of the object to be detected according to the structured light image; and judging whether the object to be detected is qualified or not according to the detection three-dimensional model and the standard three-dimensional model of the object to be detected. The scheme is simple and intelligent by presetting the standard working model corresponding to the image acquisition device and the detection object, complex debugging is not needed, and the detection efficiency is greatly improved.
Description
Technical Field
The invention relates to the technical field of product detection, in particular to product detection equipment and method based on structured light three-dimensional vision.
Background
With the development of the modern manufacturing level, a large number of three-dimensional measurements are taken during the production of the product to detect and verify the product. For example, for industrial component products, intelligent analysis such as component surface detection and dimension measurement is an important link in the production process and quality inspection process of the products. The three-dimensional data information of the product surface contour is a necessary condition in intelligent analysis of the product, and how to accurately acquire the three-dimensional data information of the product surface contour is an important subject worth researching.
The three-dimensional measurement technology can obtain three-dimensional data information of a target object, and then the obtained data information is taken as a condition to complete the specific measurement requirement of the object to be measured. The traditional contact type measuring tool has many defects, is difficult to adapt to the increasingly developed requirements, and needs an efficient and convenient detection method.
Disclosure of Invention
The invention is based on the problems, provides a product detection device and a product detection method based on structured light three-dimensional vision, and the detection efficiency is greatly improved by presetting a corresponding standard working model between an image acquisition device and a detection object, so that the product detection device is simple and intelligent, and complex debugging is not needed.
In view of the above, an aspect of the present invention provides a product inspection apparatus based on structured light three-dimensional vision, including: the system comprises a three-dimensional model building module, a standard working model building module, an acquisition module, a control processing module and an image acquisition device;
the three-dimensional model building module is used for building a first three-dimensional model of various detection objects and a second three-dimensional model of the image acquisition device;
the standard working model building module is used for respectively building a plurality of standard working models corresponding to the image acquisition device and a plurality of detection objects according to the first three-dimensional model, the second three-dimensional model and historical working data of the image acquisition device;
the acquisition module is used for acquiring a third three-dimensional model of the object to be detected;
the control processing module is used for:
determining a first standard working model corresponding to the image acquisition device from a plurality of standard working models according to the third three-dimensional model;
determining the working configuration parameters of the image acquisition device according to the first standard working model;
projecting structured light stripes to the object to be detected by using the image acquisition device, and acquiring a structured light image;
reconstructing a detection three-dimensional model of the object to be detected according to the structured light image;
and judging whether the object to be detected is qualified or not according to the detection three-dimensional model and the standard three-dimensional model of the object to be detected.
Optionally, the three-dimensional model building module is configured to build a first three-dimensional model of a plurality of detection objects and a second three-dimensional model of the image acquisition apparatus, and includes:
respectively acquiring a plurality of first three-dimensional image data of a plurality of detection objects and a plurality of second three-dimensional image data of the image acquisition device in each state;
respectively constructing a first three-dimensional model of each detection object according to the first three-dimensional image data;
and respectively constructing a plurality of second three-dimensional models of the image acquisition device in each state according to the second three-dimensional image data.
Optionally, the standard working model constructing module is configured to respectively construct a plurality of standard working models of the image acquisition apparatus corresponding to a plurality of types of detection objects according to the first three-dimensional model, the second three-dimensional model, and historical working data of the image acquisition apparatus, and includes:
extracting spatial position relation data of the image acquisition device and a corresponding first detection object when the image acquisition device works, working parameters of the image acquisition device and environment data of the image acquisition device when the image acquisition device works from the historical working data;
constructing a standard working model between the image acquisition device and the corresponding first detection object according to the first three-dimensional model, the second three-dimensional model, the spatial position relation data, the working parameters and the environment data;
and repeating the steps until a standard working model is established between the image acquisition device and all the detection objects.
Optionally, the controlling and processing module is configured to determine whether the object to be detected is qualified according to the detected three-dimensional model and the standard three-dimensional model of the object to be detected, and includes:
adjusting the detected three-dimensional model and the standard three-dimensional model into the same spatial posture;
acquiring first size data of the standard three-dimensional model;
adjusting the second size data of the detected three-dimensional model to be consistent with the first size data to obtain a modified detected three-dimensional model;
comparing and analyzing the modified detection three-dimensional model and the standard three-dimensional model, and judging whether the difference value is within a preset range;
when the difference value is within a preset range, determining that the object to be detected is qualified;
and when the difference value exceeds a preset range, determining that the object to be detected is unqualified.
Optionally, in the step of comparing and analyzing the modified detected three-dimensional model and the standard three-dimensional model and determining whether the difference value is within a preset range, the control processing module is specifically configured to:
establishing a standard three-dimensional coordinate system by taking any point in the standard three-dimensional model as a standard coordinate origin, and generating corresponding coordinate values for all other points of the standard three-dimensional model;
establishing a first three-dimensional coordinate system by taking any point in the modified detection three-dimensional model as a first coordinate origin, and generating corresponding coordinate values of all other points of the modified detection three-dimensional model;
forming a first coordinate value sequence by using the coordinate values of all points of the modified detection three-dimensional model by taking the first coordinate origin as a starting point;
forming a standard coordinate value sequence by using the coordinates of all points of the standard three-dimensional model by taking the standard coordinate origin as a starting point, and recording the number of coordinate values in the sequence as n;
carrying out coordinate pair distance calculation on one coordinate value in the first coordinate value sequence and each coordinate value in the standard coordinate value sequence from the first coordinate origin in sequence each time to obtain all distance values;
counting the number of the same distance values, and taking the distance value with the number closest to n as a first distance value;
selecting all coordinate pairs with the distance values as first distance values;
taking a coordinate point corresponding to the coordinate value with the distance from the standard coordinate origin as the first distance value as a second coordinate origin, establishing a second three-dimensional coordinate system, and generating corresponding coordinate values for all other points of the modified detection three-dimensional model;
converting the second three-dimensional coordinate system into the standard three-dimensional coordinate system, and calculating difference values between coordinate values of all points of the modified detection three-dimensional model and corresponding points of the standard three-dimensional model;
and judging whether the number of the coordinate points with the difference value exceeding a preset difference value threshold value is within a preset range.
Another aspect of the present invention provides a product inspection method based on structured light three-dimensional vision, including:
constructing a first three-dimensional model of a plurality of detection objects and a second three-dimensional model of an image acquisition device;
respectively constructing a plurality of standard working models corresponding to the image acquisition device and a plurality of detection objects according to the first three-dimensional model, the second three-dimensional model and historical working data of the image acquisition device;
acquiring a third three-dimensional model of the object to be detected;
determining a first standard working model corresponding to the image acquisition device from a plurality of standard working models according to the third three-dimensional model;
determining the working configuration parameters of the image acquisition device according to the first standard working model;
projecting structured light stripes to the object to be detected by using the image acquisition device, and acquiring a structured light image;
reconstructing a detection three-dimensional model of the object to be detected according to the structured light image;
and judging whether the object to be detected is qualified or not according to the detection three-dimensional model and the standard three-dimensional model of the object to be detected.
Optionally, the step of constructing a first three-dimensional model of a plurality of detection objects and a second three-dimensional model of an image acquisition device includes:
respectively acquiring a plurality of first three-dimensional image data of the plurality of detection objects and a plurality of second three-dimensional image data of the image acquisition device in each state;
respectively constructing a first three-dimensional model of each detection object according to the first three-dimensional image data;
and respectively constructing a plurality of second three-dimensional models of the image acquisition device in each state according to the second three-dimensional image data.
Optionally, the step of respectively constructing standard working models of the image acquisition device corresponding to the plurality of detection objects according to the first three-dimensional model, the second three-dimensional model and historical working data of the image acquisition device includes:
extracting spatial position relation data of the image acquisition device and a corresponding first detection object when the image acquisition device works, working parameters of the image acquisition device and environment data of the image acquisition device when the image acquisition device works from the historical working data;
constructing a standard working model between the image acquisition device and the corresponding first detection object according to the first three-dimensional model, the second three-dimensional model, the spatial position relation data, the working parameters and the environment data;
and repeating the steps until a standard working model is established between the image acquisition device and all the detection objects.
Optionally, the step of determining whether the object to be detected is qualified according to the detection three-dimensional model and the standard three-dimensional model of the object to be detected includes:
adjusting the detected three-dimensional model and the standard three-dimensional model into the same spatial posture;
acquiring first size data of the standard three-dimensional model;
adjusting the second size data of the detected three-dimensional model to be consistent with the first size data to obtain a modified detected three-dimensional model;
comparing and analyzing the modified detection three-dimensional model and the standard three-dimensional model, and judging whether the difference value is within a preset range;
when the difference value is within a preset range, determining that the object to be detected is qualified;
and when the difference value exceeds a preset range, determining that the object to be detected is unqualified.
Optionally, the step of comparing and analyzing the modified detected three-dimensional model and the standard three-dimensional model to determine whether the difference value is within a preset range includes:
establishing a standard three-dimensional coordinate system by taking any point in the standard three-dimensional model as a standard coordinate origin, and generating corresponding coordinate values of all other points of the standard three-dimensional model;
establishing a first three-dimensional coordinate system by taking any point in the modified detection three-dimensional model as a first coordinate origin, and generating corresponding coordinate values of all other points of the modified detection three-dimensional model;
forming a first coordinate value sequence by using the coordinate values of all points of the modified detection three-dimensional model by taking the first coordinate origin as a starting point;
forming a standard coordinate value sequence by using the coordinates of all points of the standard three-dimensional model by taking the standard coordinate origin as a starting point, and recording the number of coordinate values in the sequence as n;
carrying out coordinate pair distance calculation on one coordinate value in the first coordinate value sequence and each coordinate value in the standard coordinate value sequence from the first coordinate origin in sequence each time to obtain all distance values;
counting the number of the same distance values, and taking the distance value with the number closest to n as a first distance value;
selecting all coordinate pairs with the distance values as first distance values;
establishing a second three-dimensional coordinate system by taking a coordinate point corresponding to the coordinate value with the distance from the standard coordinate origin as the first distance value as a second coordinate origin, and generating corresponding coordinate values for all other points of the modified detection three-dimensional model;
converting the second three-dimensional coordinate system into the standard three-dimensional coordinate system, and calculating difference values between coordinate values of all points of the modified detection three-dimensional model and corresponding points of the standard three-dimensional model;
and judging whether the number of the coordinate points with the difference value exceeding a preset difference value threshold value is within a preset range.
By adopting the technical scheme, the product detection equipment is provided with a three-dimensional model building module, a standard working model building module, an acquisition module, a control processing module and an image acquisition device; the three-dimensional model building module is used for building a first three-dimensional model of various detection objects and a second three-dimensional model of the image acquisition device; the standard working model building module is used for respectively building a plurality of standard working models corresponding to the image acquisition device and a plurality of detection objects according to the first three-dimensional model, the second three-dimensional model and historical working data of the image acquisition device; the acquisition module is used for acquiring a third three-dimensional model of the object to be detected; the control processing module is used for: determining a first standard working model corresponding to the image acquisition device from a plurality of standard working models according to the third three-dimensional model; determining the working configuration parameters of the image acquisition device according to the first standard working model; projecting structured light stripes to the object to be detected by using the image acquisition device, and acquiring a structured light image; reconstructing a detection three-dimensional model of the object to be detected according to the structured light image; and judging whether the object to be detected is qualified or not according to the detection three-dimensional model and the standard three-dimensional model of the object to be detected. The scheme is simple and intelligent by presetting the standard working model corresponding to the image acquisition device and the detection object, complex debugging is not needed, and the detection efficiency is greatly improved.
Drawings
FIG. 1 is a schematic block diagram of a product inspection apparatus provided in one embodiment of the present invention;
fig. 2 is a flowchart of a product inspection method according to another embodiment of the present invention.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention, taken in conjunction with the accompanying drawings and detailed description, is set forth below. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced otherwise than as specifically described herein and, therefore, the scope of the present invention is not limited by the specific embodiments disclosed below.
The terms "first," "second," and the like in the description and claims of the present application and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
A product inspection apparatus and method based on structured light three-dimensional vision according to some embodiments of the present invention is described below with reference to fig. 1 to 2.
As shown in fig. 1, an embodiment of the present invention provides a product inspection apparatus based on structured light three-dimensional vision, including: the system comprises a three-dimensional model building module, a standard working model building module, an acquisition module, a control processing module and an image acquisition device;
the three-dimensional model building module is used for building a first three-dimensional model of various detection objects and a second three-dimensional model of the image acquisition device;
the standard working model building module is used for respectively building a plurality of standard working models corresponding to the image acquisition device and a plurality of detection objects according to the first three-dimensional model, the second three-dimensional model and historical working data of the image acquisition device;
the acquisition module is used for acquiring a third three-dimensional model of the object to be detected;
the control processing module is used for:
determining a first standard working model corresponding to the image acquisition device from a plurality of standard working models according to the third three-dimensional model;
determining the working configuration parameters of the image acquisition device according to the first standard working model;
projecting structured light stripes to the object to be detected by using the image acquisition device, and acquiring a structured light image;
reconstructing a detection three-dimensional model of the object to be detected according to the structured light image;
and judging whether the object to be detected is qualified or not according to the detection three-dimensional model and the standard three-dimensional model of the object to be detected.
It can be understood that, in the embodiment of the present invention, various detection objects, three-dimensional models (i.e., a first three-dimensional model and a second three-dimensional model) of an image acquisition device for detection are pre-established by using a three-dimensional modeling technique, then, in combination with historical working data of the image acquisition device (e.g., spatial position relationship data between the image acquisition device and the corresponding detection object when working, working parameters of the image acquisition device, environmental data when the image acquisition device is working, etc.), a plurality of standard working models corresponding to the image acquisition device and a plurality of detection objects are respectively established, that is, for each product, in combination with a virtual three-dimensional image, a standard spatial position relationship between a detection tool (the image acquisition device) and a product when detection is performed (i.e., how the detection tool "swings"), standard working parameters (which are determined in combination with factors such as environmental data, etc.) are determined, a standard working model is established, when a certain product needs to be detected subsequently, a third standard working model of the object is obtained, the first standard working model is used for determining the image acquisition device from the plurality of the standard working models, and the intelligent working model configuration efficiency is greatly improved.
After the image acquisition device adjusts the space position and the working configuration logarithm according to a first standard working model, projecting structured light stripes to the object to be detected, acquiring a structured light image, and reconstructing a detection three-dimensional model of the object to be detected according to the structured light image. The structured light vision measurement is non-contact measurement combining laser scanning and vision processing technology, and has the advantages of high measurement precision, strong stability, real-time performance and universality. Three-dimensional reconstruction by structured light vision technology is a mature technology, and the embodiment of the invention is not described herein again.
And finally, comparing and analyzing the detection three-dimensional model and a standard three-dimensional model (such as a product standard model established in advance) of the object to be detected, and judging whether the object to be detected is qualified.
With the technical solution of this embodiment, the product detection apparatus includes: the system comprises a three-dimensional model building module, a standard working model building module, an acquisition module, a control processing module and an image acquisition device; the three-dimensional model building module is used for building a first three-dimensional model of various detection objects and a second three-dimensional model of the image acquisition device; the standard working model building module is used for respectively building a plurality of standard working models corresponding to the image acquisition device and a plurality of detection objects according to the first three-dimensional model, the second three-dimensional model and historical working data of the image acquisition device; the acquisition module is used for acquiring a third three-dimensional model of the object to be detected; the control processing module is used for: determining a first standard working model corresponding to the image acquisition device from a plurality of standard working models according to the third three-dimensional model; determining the working configuration parameters of the image acquisition device according to the first standard working model; projecting structured light stripes to the object to be detected by using the image acquisition device, and acquiring a structured light image; reconstructing a detection three-dimensional model of the object to be detected according to the structured light image; and judging whether the object to be detected is qualified or not according to the detection three-dimensional model and the standard three-dimensional model of the object to be detected. The scheme is simple and intelligent by presetting the standard working model corresponding to the image acquisition device and the detection object, complex debugging is not needed, and the detection efficiency is greatly improved.
It should be understood that the block diagram of the product inspection apparatus shown in fig. 1 is merely schematic, and the number of the modules shown is not intended to limit the scope of the present invention.
In some possible embodiments of the present invention, the three-dimensional model constructing module is configured to construct a first three-dimensional model of a plurality of detection objects and a second three-dimensional model of the image capturing apparatus, and includes:
respectively acquiring a plurality of first three-dimensional image data of the plurality of detection objects and a plurality of second three-dimensional image data of the image acquisition device in each state;
respectively constructing a first three-dimensional model of each detection object according to the first three-dimensional image data;
and respectively constructing a plurality of second three-dimensional models of the image acquisition device in each state according to the second three-dimensional image data.
It is understood that, in order to ensure that the standard working model has a wider application range and more accurate measurement, in an embodiment of the present invention, a plurality of second three-dimensional image data in each state of the image capturing apparatus (for example, different capturing postures, different extending lengths of the retractable member, and the like) are obtained to respectively construct a plurality of second three-dimensional models in each state of the image capturing apparatus.
In some possible embodiments of the present invention, the standard working model constructing module is configured to respectively construct a plurality of standard working models of the image capturing device corresponding to a plurality of types of the detection objects according to the first three-dimensional model, the second three-dimensional model and historical working data of the image capturing device, and includes:
extracting spatial position relation data of the image acquisition device and a corresponding first detection object when the image acquisition device works, working parameters of the image acquisition device and environment data of the image acquisition device when the image acquisition device works from the historical working data;
according to the first three-dimensional model, the second three-dimensional model, the spatial position relation data, the working parameters and the environment data, a standard working model between the image acquisition device and the corresponding first detection object is constructed;
and repeating the steps until a standard working model is established between the image acquisition device and all the detection objects.
It can be understood that, in this embodiment, according to spatial position relationship data between the image acquisition device and a corresponding detection object when the image acquisition device works, working parameters of the image acquisition device, environmental data of the image acquisition device when the image acquisition device works, and the like, a plurality of standard working models corresponding to the image acquisition device and a plurality of detection objects are respectively constructed, that is, for each product, a virtual three-dimensional image is combined to determine a standard spatial position relationship between a detection tool (the image acquisition device) and the product when the detection is performed (i.e., how the detection tool "swings"), standard working parameters (comprehensively determined by combining factors such as environmental data), and the like, so as to establish the standard working models. By the embodiment, an accurate standard working model can be effectively established, and a measuring working procedure is simplified.
In some possible embodiments of the present invention, the determining, by the control processing module, whether the object to be detected is qualified according to the detection three-dimensional model and a standard three-dimensional model of the object to be detected includes:
adjusting the detected three-dimensional model and the standard three-dimensional model into the same spatial posture;
acquiring first size data of the standard three-dimensional model;
adjusting the second size data of the detected three-dimensional model to be consistent with the first size data to obtain a modified detected three-dimensional model;
comparing and analyzing the modified detection three-dimensional model and the standard three-dimensional model, and judging whether the difference value is within a preset range;
when the difference value is within a preset range, determining that the object to be detected is qualified;
and when the difference value exceeds a preset range, determining that the object to be detected is unqualified.
It can be understood that, in order to better perform a comparison analysis on the detected three-dimensional model and the standard three-dimensional model of the object to be detected, in this embodiment, the detected three-dimensional model and the standard three-dimensional model are adjusted to the same spatial posture, the detected three-dimensional model is adjusted according to the size of the standard three-dimensional model to obtain a modified detected three-dimensional model, and then the modified detected three-dimensional model and the standard three-dimensional model are compared and analyzed to determine whether the difference value is within a preset range; when the difference value is within a preset range, determining that the object to be detected is qualified; and when the difference value exceeds a preset range, determining that the object to be detected is unqualified.
In some possible embodiments of the present invention, in the step of comparing and analyzing the modified detected three-dimensional model and the standard three-dimensional model, and determining whether the difference value is within a preset range, the control processing module is specifically configured to:
establishing a standard three-dimensional coordinate system by taking any point in the standard three-dimensional model as a standard coordinate origin, and generating corresponding coordinate values of all other points of the standard three-dimensional model;
establishing a first three-dimensional coordinate system by taking any point in the modified detection three-dimensional model as a first coordinate origin, and generating corresponding coordinate values of all other points of the modified detection three-dimensional model;
forming a first coordinate value sequence by using the coordinate values of all points of the modified detection three-dimensional model by taking the first coordinate origin as a starting point;
forming a standard coordinate value sequence by using the coordinates of all points of the standard three-dimensional model by taking the standard coordinate origin as a starting point, and recording the number of coordinate values in the sequence as n, wherein n is a positive integer;
carrying out coordinate pair distance calculation on one coordinate value in the first coordinate value sequence and each coordinate value in the standard coordinate value sequence in sequence from the first coordinate origin to obtain all distance values;
counting the number of the same distance values, and taking the distance value with the number closest to n as a first distance value;
selecting all coordinate pairs with the distance values as first distance values;
establishing a second three-dimensional coordinate system by taking a coordinate point corresponding to the coordinate value with the distance from the standard coordinate origin as the first distance value as a second coordinate origin, and generating corresponding coordinate values for all other points of the modified detection three-dimensional model;
converting the second three-dimensional coordinate system into the standard three-dimensional coordinate system, and calculating difference values between coordinate values of all points of the modified detection three-dimensional model and corresponding points of the standard three-dimensional model;
and judging whether the number of the coordinate points with the difference value exceeding a preset difference value threshold value is within a preset range.
In this embodiment, different three-dimensional coordinate systems, that is, a standard three-dimensional coordinate system and a first three-dimensional coordinate system, are respectively constructed with points of the standard three-dimensional model and the modified detection three-dimensional model, and distance values from all points in one model to all points in the other model are calculated through coordinate values of all points on the two models in different three-dimensional coordinate systems (two points calculated each time are marked as a coordinate pair, and coordinate values of both are recorded), it should be noted that all calculated distance values form a distance value set, a statistical analysis is performed on the set, the number of the same distance values is counted, the distance value with the number closest to n is taken as a first distance value, all coordinate pairs with the distance value as the first distance value are selected, an origin point corresponding to a coordinate value with the origin of the standard coordinate as the first distance value is taken as a second coordinate, a second three-dimensional coordinate system is established, and all other points of the modified detection three-dimensional model generate corresponding coordinate values; converting the second three-dimensional coordinate system into the standard three-dimensional coordinate system, and calculating difference values between coordinate values of all points of the modified detection three-dimensional model and corresponding points of the standard three-dimensional model; and judging whether the number of the coordinate points with the difference value exceeding a preset difference value threshold value is within a preset range.
Referring to fig. 2, another embodiment of the present invention provides a product inspection method based on structured light three-dimensional vision, including:
constructing a first three-dimensional model of a plurality of detection objects and a second three-dimensional model of an image acquisition device;
respectively constructing a plurality of standard working models corresponding to the image acquisition device and a plurality of detection objects according to the first three-dimensional model, the second three-dimensional model and historical working data of the image acquisition device;
acquiring a third three-dimensional model of the object to be detected;
determining a first standard working model corresponding to the image acquisition device from a plurality of standard working models according to the third three-dimensional model;
determining the working configuration parameters of the image acquisition device according to the first standard working model;
projecting structured light stripes to the object to be detected by using the image acquisition device, and acquiring a structured light image;
reconstructing a detection three-dimensional model of the object to be detected according to the structured light image;
and judging whether the object to be detected is qualified or not according to the detection three-dimensional model and the standard three-dimensional model of the object to be detected.
It can be understood that, in the embodiment of the present invention, various detection objects, three-dimensional models (i.e., a first three-dimensional model and a second three-dimensional model) of an image acquisition device for detection are pre-established by using a three-dimensional modeling technique, then, in combination with historical working data of the image acquisition device (e.g., spatial position relationship data between the image acquisition device and the corresponding detection object when working, working parameters of the image acquisition device, environmental data when the image acquisition device is working, etc.), a plurality of standard working models corresponding to the image acquisition device and a plurality of detection objects are respectively established, that is, for each product, in combination with a virtual three-dimensional image, a standard spatial position relationship between a detection tool (the image acquisition device) and a product when detection is performed (i.e., how the detection tool "swings"), standard working parameters (which are determined in combination with factors such as environmental data, etc.) are determined, a standard working model is established, when a certain product needs to be detected subsequently, a third standard working model of the object is obtained, the first standard working model is used for determining the image acquisition device from the plurality of the standard working models, and the intelligent working model configuration efficiency is greatly improved.
After the image acquisition device adjusts the space position and the working configuration logarithm according to a first standard working model, projecting structured light stripes to the object to be detected, acquiring a structured light image, and reconstructing a detection three-dimensional model of the object to be detected according to the structured light image. The structured light vision measurement is non-contact measurement combining laser scanning and vision processing technologies, and has the advantages of high measurement precision, high stability, real-time performance and universality. Three-dimensional reconstruction by structured light vision technology is a mature technology, and the embodiment of the invention is not described herein again.
And finally, comparing and analyzing the detection three-dimensional model and the standard three-dimensional model of the object to be detected, and judging whether the object to be detected is qualified.
By adopting the technical scheme of the embodiment, the product detection method comprises the following steps: constructing a first three-dimensional model of a plurality of detection objects and a second three-dimensional model of an image acquisition device; respectively constructing a plurality of standard working models corresponding to the image acquisition device and a plurality of detection objects according to the first three-dimensional model, the second three-dimensional model and historical working data of the image acquisition device; acquiring a third three-dimensional model of the object to be detected; determining a first standard working model corresponding to the image acquisition device from a plurality of standard working models according to the third three-dimensional model; determining the working configuration parameters of the image acquisition device according to the first standard working model; projecting structured light stripes to the object to be detected by using the image acquisition device, and acquiring a structured light image; reconstructing a detection three-dimensional model of the object to be detected according to the structured light image; and judging whether the object to be detected is qualified or not according to the detection three-dimensional model and the standard three-dimensional model of the object to be detected. According to the scheme, the standard working model corresponding to the image acquisition device and the detection object is set in advance, so that the method is simple and intelligent, complex debugging is not needed, and the detection efficiency is greatly improved.
In some possible embodiments of the present invention, the step of constructing the first three-dimensional model of the plurality of inspection objects and the second three-dimensional model of the image capturing device includes:
respectively acquiring a plurality of first three-dimensional image data of a plurality of detection objects and a plurality of second three-dimensional image data of the image acquisition device in each state;
respectively constructing a first three-dimensional model of each detection object according to the first three-dimensional image data;
and respectively constructing a plurality of second three-dimensional models of the image acquisition device in each state according to the second three-dimensional image data.
It is understood that, in order to ensure that the standard working model has a wider application range and more accurate measurement, in an embodiment of the present invention, a plurality of second three-dimensional image data in each state of the image capturing apparatus (for example, different capturing postures, different extending lengths of the retractable member, and the like) are obtained to respectively construct a plurality of second three-dimensional models in each state of the image capturing apparatus.
In some possible embodiments of the present invention, the step of respectively constructing a standard working model of the image capturing device corresponding to a plurality of types of the detection objects according to the first three-dimensional model, the second three-dimensional model and historical working data of the image capturing device includes:
extracting spatial position relation data of the image acquisition device and a corresponding first detection object when the image acquisition device works, working parameters of the image acquisition device and environment data of the image acquisition device when the image acquisition device works from the historical working data;
constructing a standard working model between the image acquisition device and the corresponding first detection object according to the first three-dimensional model, the second three-dimensional model, the spatial position relation data, the working parameters and the environment data;
and repeating the steps until a standard working model is established between the image acquisition device and all the detection objects.
It can be understood that, in this embodiment, according to the spatial position relationship data between the image acquisition device and the corresponding detection object when the image acquisition device operates, the operating parameters of the image acquisition device, the environmental data of the image acquisition device when the image acquisition device operates, and the like, a plurality of standard operating models corresponding to the image acquisition device and a plurality of detection objects are respectively constructed, that is, for each product, the virtual three-dimensional image is combined to determine the standard spatial position relationship between the detection tool (the image acquisition device) and the product when the detection is performed (i.e., how the detection tool "swings"), the standard operating parameters (which are comprehensively determined by combining factors such as the environmental data, and the like), and the standard operating models are established. By the embodiment, an accurate standard working model can be effectively established, and a measuring work program is simplified.
In some possible embodiments of the present invention, the step of determining whether the object to be detected is qualified according to the detection three-dimensional model and the standard three-dimensional model of the object to be detected includes:
adjusting the detected three-dimensional model and the standard three-dimensional model into the same spatial posture;
acquiring first size data of the standard three-dimensional model;
adjusting the second size data of the detected three-dimensional model to be consistent with the first size data to obtain a modified detected three-dimensional model;
comparing and analyzing the modified detection three-dimensional model and the standard three-dimensional model, and judging whether the difference value is in a preset range;
when the difference value is within a preset range, determining that the object to be detected is qualified;
and when the difference value exceeds a preset range, determining that the object to be detected is unqualified.
It can be understood that, in order to better perform comparison analysis on the detected three-dimensional model and the standard three-dimensional model of the object to be detected, in this embodiment, the detected three-dimensional model and the standard three-dimensional model are adjusted to be in the same spatial posture, the detected three-dimensional model is adjusted according to the size of the standard three-dimensional model to obtain a modified detected three-dimensional model, and then the modified detected three-dimensional model and the standard three-dimensional model are compared and analyzed to determine whether the difference value is within a preset range; when the difference value is within a preset range, determining that the object to be detected is qualified; and when the difference value exceeds a preset range, determining that the object to be detected is unqualified.
In some possible embodiments of the present invention, the step of comparing and analyzing the modified detection three-dimensional model and the standard three-dimensional model to determine whether the difference value is within a preset range includes:
establishing a standard three-dimensional coordinate system by taking any point in the standard three-dimensional model as a standard coordinate origin, and generating corresponding coordinate values for all other points of the standard three-dimensional model;
establishing a first three-dimensional coordinate system by taking any point in the modified detection three-dimensional model as a first coordinate origin, and generating corresponding coordinate values for all other points of the modified detection three-dimensional model;
forming a first coordinate value sequence by using the coordinate values of all points of the modified detection three-dimensional model by taking the first coordinate origin as a starting point;
forming a standard coordinate value sequence by using the coordinates of all points of the standard three-dimensional model by taking the standard coordinate origin as a starting point, and recording the number of coordinate values in the sequence as n, wherein n is a positive integer;
carrying out coordinate pair distance calculation on one coordinate value in the first coordinate value sequence and each coordinate value in the standard coordinate value sequence in sequence from the first coordinate origin to obtain all distance values;
counting the number of the same distance values, and taking the distance value with the number closest to n as a first distance value;
selecting all coordinate pairs with the distance values as first distance values;
taking a coordinate point corresponding to the coordinate value with the distance from the standard coordinate origin as the first distance value as a second coordinate origin, establishing a second three-dimensional coordinate system, and generating corresponding coordinate values for all other points of the modified detection three-dimensional model;
converting the second three-dimensional coordinate system into the standard three-dimensional coordinate system, and calculating difference values between coordinate values of all points of the modified detection three-dimensional model and corresponding points of the standard three-dimensional model;
and judging whether the number of the coordinate points with the difference value exceeding a preset difference value threshold value is within a preset range.
In this embodiment, different three-dimensional coordinate systems, that is, a standard three-dimensional coordinate system and a first three-dimensional coordinate system, are respectively constructed with points of the standard three-dimensional model and the modified detection three-dimensional model, and distance values from all points in one model to all points in the other model are calculated through coordinate values of all points on the two models in the different three-dimensional coordinate systems (two points calculated each time are recorded as a coordinate pair, and coordinate values of both are recorded), it should be noted that all the calculated distance values are combined into a distance value set, a statistical analysis is performed on the set, the number of the same distance values is counted, the distance value closest to n is taken as a first distance value, all the coordinate pairs with the distance value as the first distance value are selected, an origin point corresponding to a coordinate value with the origin of the standard coordinate as the first distance value is taken as a second coordinate, a second three-dimensional coordinate system is established, and all other points of the modified detection three-dimensional model are generated into corresponding coordinate values; converting the second three-dimensional coordinate system into the standard three-dimensional coordinate system, and calculating difference values between coordinate values of all points of the modified detection three-dimensional model and corresponding points of the standard three-dimensional model; and judging whether the number of the coordinate points with the difference value exceeding a preset difference value threshold value is within a preset range.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the above-described units is only one type of logical functional division, and other divisions may be realized in practice, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed coupling or direct coupling or communication connection between each other may be through some interfaces, indirect coupling or communication connection between devices or units, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit may be implemented in the form of hardware, or may also be implemented in the form of a software functional unit.
The integrated unit may be stored in a computer readable memory if it is implemented in the form of a software functional unit and sold or used as a separate product. Based on such understanding, the technical solution of the present application may be substantially implemented or a part of or all or part of the technical solution contributing to the prior art may be embodied in the form of a software product stored in a memory, and including several instructions for causing a computer device (which may be a personal computer, a control processing module or a network device, etc.) to execute all or part of the steps of the above methods of the embodiments of the present application. And the aforementioned memory comprises: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable memory, which may include: flash Memory disks, read-Only memories (ROMs), random Access Memories (RAMs), magnetic or optical disks, and the like.
The foregoing detailed description of the embodiments of the present application has been presented to illustrate the principles and implementations of the present application, and the above description of the embodiments is only provided to help understand the method and the core concept of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Although the present invention is disclosed above, the present invention is not limited thereto. Various changes and modifications can be easily made by those skilled in the art without departing from the spirit and scope of the present invention, and it is within the scope of the present invention to include different functions, combination of implementation steps, software and hardware implementations.
Claims (10)
1. A structured light three-dimensional vision based product inspection device, comprising: the system comprises a three-dimensional model building module, a standard working model building module, an acquisition module, a control processing module and an image acquisition device;
the three-dimensional model building module is used for building a first three-dimensional model of various detection objects and a second three-dimensional model of the image acquisition device;
the standard working model building module is used for respectively building a plurality of standard working models corresponding to the image acquisition device and a plurality of detection objects according to the first three-dimensional model, the second three-dimensional model and historical working data of the image acquisition device;
the acquisition module is used for acquiring a third three-dimensional model of the object to be detected;
the control processing module is used for:
determining a first standard working model corresponding to the image acquisition device from a plurality of standard working models according to the third three-dimensional model;
determining the working configuration parameters of the image acquisition device according to the first standard working model;
projecting structured light stripes to the object to be detected by using the image acquisition device, and acquiring a structured light image;
reconstructing a detection three-dimensional model of the object to be detected according to the structured light image;
and judging whether the object to be detected is qualified or not according to the detection three-dimensional model and the standard three-dimensional model of the object to be detected.
2. The product inspection apparatus of claim 1, wherein the three-dimensional model building module is configured to build a first three-dimensional model of a plurality of inspection objects and a second three-dimensional model of the image capturing device, and comprises:
respectively acquiring a plurality of first three-dimensional image data of the plurality of detection objects and a plurality of second three-dimensional image data of the image acquisition device in each state;
respectively constructing a first three-dimensional model of each detection object according to the first three-dimensional image data;
and respectively constructing a plurality of second three-dimensional models of the image acquisition device in each state according to the second three-dimensional image data.
3. The product inspection apparatus according to claim 2, wherein the standard working model building module is configured to respectively build a plurality of standard working models of the image capturing device corresponding to a plurality of types of inspection objects according to the first three-dimensional model, the second three-dimensional model and historical working data of the image capturing device, and includes:
extracting spatial position relation data of the image acquisition device and a corresponding first detection object when the image acquisition device works, working parameters of the image acquisition device and environment data of the image acquisition device when the image acquisition device works from the historical working data;
constructing a standard working model between the image acquisition device and the corresponding first detection object according to the first three-dimensional model, the second three-dimensional model, the spatial position relation data, the working parameters and the environment data;
and repeating the steps until a standard working model is established between the image acquisition device and all the detection objects.
4. The product inspection apparatus of claim 3, wherein the control processing module is configured to determine whether the object under test is qualified according to the inspection three-dimensional model and a standard three-dimensional model of the object under test, and includes:
adjusting the detection three-dimensional model and the standard three-dimensional model to be in the same spatial posture;
acquiring first size data of the standard three-dimensional model;
adjusting the second size data of the detected three-dimensional model to be consistent with the first size data to obtain a modified detected three-dimensional model;
comparing and analyzing the modified detection three-dimensional model and the standard three-dimensional model, and judging whether the difference value is within a preset range;
when the difference value is within a preset range, determining that the object to be detected is qualified;
and when the difference value exceeds a preset range, determining that the object to be detected is unqualified.
5. The product inspection apparatus according to claim 4, wherein in the step of comparing and analyzing the modified inspection three-dimensional model and the standard three-dimensional model to determine whether the difference is within a preset range, the control processing module is specifically configured to:
establishing a standard three-dimensional coordinate system by taking any point in the standard three-dimensional model as a standard coordinate origin, and generating corresponding coordinate values for all other points of the standard three-dimensional model;
establishing a first three-dimensional coordinate system by taking any point in the modified detection three-dimensional model as a first coordinate origin, and generating corresponding coordinate values of all other points of the modified detection three-dimensional model;
forming a first coordinate value sequence by using the coordinate values of all points of the modified detection three-dimensional model by taking the first coordinate origin as a starting point;
forming a standard coordinate value sequence by using the coordinates of all points of the standard three-dimensional model by taking the standard coordinate origin as a starting point, and recording the number of coordinate values in the sequence as n;
carrying out coordinate pair distance calculation on one coordinate value in the first coordinate value sequence and each coordinate value in the standard coordinate value sequence in sequence from the first coordinate origin to obtain all distance values;
counting the number of the same distance values, and taking the distance value with the number closest to n as a first distance value;
selecting all coordinate pairs with the distance values as first distance values;
establishing a second three-dimensional coordinate system by taking a coordinate point corresponding to the coordinate value with the distance from the standard coordinate origin as the first distance value as a second coordinate origin, and generating corresponding coordinate values for all other points of the modified detection three-dimensional model;
converting the second three-dimensional coordinate system into the standard three-dimensional coordinate system, and calculating difference values between coordinate values of all points of the modified detection three-dimensional model and corresponding points of the standard three-dimensional model;
and judging whether the number of the coordinate points with the difference value exceeding a preset difference value threshold value is in a preset range or not.
6. A product detection method based on structured light three-dimensional vision is characterized by comprising the following steps:
constructing a first three-dimensional model of a plurality of detection objects and a second three-dimensional model of an image acquisition device;
respectively constructing a plurality of standard working models corresponding to the image acquisition device and a plurality of detection objects according to the first three-dimensional model, the second three-dimensional model and historical working data of the image acquisition device;
acquiring a third three-dimensional model of the object to be detected;
determining a first standard working model corresponding to the image acquisition device from a plurality of standard working models according to the third three-dimensional model;
determining the working configuration parameters of the image acquisition device according to the first standard working model;
projecting structured light stripes to the object to be detected by using the image acquisition device, and acquiring a structured light image;
reconstructing a detection three-dimensional model of the object to be detected according to the structured light image;
and judging whether the object to be detected is qualified or not according to the detection three-dimensional model and the standard three-dimensional model of the object to be detected.
7. The product inspection method according to claim 6, wherein the step of constructing a first three-dimensional model of a plurality of inspection objects and a second three-dimensional model of an image capture device comprises:
respectively acquiring a plurality of first three-dimensional image data of the plurality of detection objects and a plurality of second three-dimensional image data of the image acquisition device in each state;
respectively constructing a first three-dimensional model of each detection object according to the first three-dimensional image data;
and respectively constructing a plurality of second three-dimensional models of the image acquisition device in each state according to the second three-dimensional image data.
8. The product inspection method according to claim 7, wherein the step of constructing a standard working model of the image capturing device corresponding to a plurality of types of the inspection objects based on the first three-dimensional model, the second three-dimensional model, and historical working data of the image capturing device, respectively, comprises:
extracting spatial position relation data of the image acquisition device and a corresponding first detection object when the image acquisition device works, working parameters of the image acquisition device and environment data of the image acquisition device when the image acquisition device works from the historical working data;
according to the first three-dimensional model, the second three-dimensional model, the spatial position relation data, the working parameters and the environment data, a standard working model between the image acquisition device and the corresponding first detection object is constructed;
and repeating the steps until a standard working model is established between the image acquisition device and all the detection objects.
9. The product inspection method according to claim 8, wherein the step of determining whether the object to be inspected is qualified according to the inspection three-dimensional model and a standard three-dimensional model of the object to be inspected comprises:
adjusting the detected three-dimensional model and the standard three-dimensional model into the same spatial posture;
acquiring first size data of the standard three-dimensional model;
adjusting the second size data of the detected three-dimensional model to be consistent with the first size data to obtain a modified detected three-dimensional model;
comparing and analyzing the modified detection three-dimensional model and the standard three-dimensional model, and judging whether the difference value is within a preset range;
when the difference value is within a preset range, determining that the object to be detected is qualified;
and when the difference value exceeds a preset range, determining that the object to be detected is unqualified.
10. The product inspection method according to claim 9, wherein the step of comparing the modified inspection three-dimensional model with the standard three-dimensional model for analysis to determine whether the difference is within a predetermined range includes:
establishing a standard three-dimensional coordinate system by taking any point in the standard three-dimensional model as a standard coordinate origin, and generating corresponding coordinate values for all other points of the standard three-dimensional model;
establishing a first three-dimensional coordinate system by taking any point in the modified detection three-dimensional model as a first coordinate origin, and generating corresponding coordinate values for all other points of the modified detection three-dimensional model;
forming a first coordinate value sequence by using the coordinate values of all points of the modified detection three-dimensional model by taking the first coordinate origin as a starting point;
forming a standard coordinate value sequence by using the coordinates of all points of the standard three-dimensional model by taking the standard coordinate origin as a starting point, and recording the number of coordinate values in the sequence as n;
carrying out coordinate pair distance calculation on one coordinate value in the first coordinate value sequence and each coordinate value in the standard coordinate value sequence in sequence from the first coordinate origin to obtain all distance values;
counting the number of the same distance values, and taking the distance value with the number closest to n as a first distance value;
selecting all coordinate pairs with the distance values as first distance values;
taking a coordinate point corresponding to the coordinate value with the distance from the standard coordinate origin as the first distance value as a second coordinate origin, establishing a second three-dimensional coordinate system, and generating corresponding coordinate values for all other points of the modified detection three-dimensional model;
converting the second three-dimensional coordinate system into the standard three-dimensional coordinate system, and calculating difference values between coordinate values of all points of the modified detection three-dimensional model and corresponding points of the standard three-dimensional model;
and judging whether the number of the coordinate points with the difference value exceeding a preset difference value threshold value is in a preset range or not.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211003889.XA CN115077425B (en) | 2022-08-22 | 2022-08-22 | Product detection equipment and method based on structured light three-dimensional vision |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211003889.XA CN115077425B (en) | 2022-08-22 | 2022-08-22 | Product detection equipment and method based on structured light three-dimensional vision |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115077425A CN115077425A (en) | 2022-09-20 |
| CN115077425B true CN115077425B (en) | 2022-11-11 |
Family
ID=83245218
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211003889.XA Active CN115077425B (en) | 2022-08-22 | 2022-08-22 | Product detection equipment and method based on structured light three-dimensional vision |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115077425B (en) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116342602A (en) * | 2023-05-30 | 2023-06-27 | 四川都得利管业有限公司 | Fine detection method and system for production quality of plastic pipe |
| CN116664520A (en) * | 2023-05-31 | 2023-08-29 | 深圳市莱创云信息技术有限公司 | Intelligent detection system of electronic product |
| CN117152098A (en) * | 2023-09-04 | 2023-12-01 | 深圳崎点数据有限公司 | Deep learning-based battery defect detection method and system |
| CN117237345B (en) * | 2023-11-13 | 2024-02-02 | 珠宝玉石首饰国检集团深圳研究所有限公司 | Noble metal detection method and system based on pulse eddy current |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2010121999A (en) * | 2008-11-18 | 2010-06-03 | Omron Corp | Creation method of three-dimensional model, and object recognition device |
| JP2015219679A (en) * | 2014-05-16 | 2015-12-07 | 株式会社リコー | Image processing system, information processing device, and program |
| CN108955520A (en) * | 2018-04-17 | 2018-12-07 | 武汉工程大学 | A kind of structural light three-dimensional scanning analysis method of reachability and analysis system |
| CN109000560A (en) * | 2018-06-11 | 2018-12-14 | 广东工业大学 | Method, apparatus and equipment based on three-dimensional camera detection package dimensions |
| WO2021099883A1 (en) * | 2019-11-20 | 2021-05-27 | Ricoh Company, Ltd. | Shape measuring device, system with fabricating unit and shape measuring device, and method |
| CN114909999A (en) * | 2022-07-18 | 2022-08-16 | 深圳市超准视觉科技有限公司 | Three-dimensional measurement system and method based on structured light |
-
2022
- 2022-08-22 CN CN202211003889.XA patent/CN115077425B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2010121999A (en) * | 2008-11-18 | 2010-06-03 | Omron Corp | Creation method of three-dimensional model, and object recognition device |
| JP2015219679A (en) * | 2014-05-16 | 2015-12-07 | 株式会社リコー | Image processing system, information processing device, and program |
| CN108955520A (en) * | 2018-04-17 | 2018-12-07 | 武汉工程大学 | A kind of structural light three-dimensional scanning analysis method of reachability and analysis system |
| CN109000560A (en) * | 2018-06-11 | 2018-12-14 | 广东工业大学 | Method, apparatus and equipment based on three-dimensional camera detection package dimensions |
| WO2021099883A1 (en) * | 2019-11-20 | 2021-05-27 | Ricoh Company, Ltd. | Shape measuring device, system with fabricating unit and shape measuring device, and method |
| CN114909999A (en) * | 2022-07-18 | 2022-08-16 | 深圳市超准视觉科技有限公司 | Three-dimensional measurement system and method based on structured light |
Non-Patent Citations (1)
| Title |
|---|
| 逆向工程在义齿修复中的应用;韩静芸等;《北京工业大学学报》;20021230;第28卷(第4期);第413-417页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115077425A (en) | 2022-09-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN115077425B (en) | Product detection equipment and method based on structured light three-dimensional vision | |
| US9046353B2 (en) | System and method for remote full field three-dimensional displacement and strain measurements | |
| Di Leo et al. | Covariance propagation for the uncertainty estimation in stereo vision | |
| CN111156923A (en) | Workpiece detection method, workpiece detection device, computer equipment and storage medium | |
| CN104713885A (en) | Structured light-assisted binocular measuring method for on-line detection of PCB | |
| CN109579718B (en) | Method and device for detecting welding seam parameters, computer equipment and storage medium | |
| CN104634242A (en) | Point adding system and method of probe | |
| CN108955901B (en) | Infrared temperature measurement method and system and terminal equipment | |
| CN115731165B (en) | Detection system and method for on-line size spot inspection of lithium battery | |
| CN112258507B (en) | Target object detection method and device of internet data center and electronic equipment | |
| CN112001880B (en) | Method and device for detecting characteristic parameters of planar member | |
| CN114240854A (en) | Product detection method and detection device | |
| CN115902931A (en) | Device and method for detecting by using laser signal | |
| CN115770731A (en) | Method and system for eliminating bad workpieces based on laser vision | |
| CN114638795A (en) | Multi-structure light measurement unit online measurement method and system | |
| CN114549453A (en) | Contact line pull-out lead height value detection method and system | |
| CN113393450B (en) | Data quality inspection method and system for digital line drawing and readable storage medium | |
| CN112785135A (en) | Engineering quality inspection method, device, computer equipment and storage medium | |
| CN113744194B (en) | Steel plate defect detection method and computer readable storage medium | |
| US11698252B2 (en) | Error determination apparatus, error determination method, and storage medium | |
| Svalina et al. | Possibilities of evaluating the dimensional acceptability of workpieces using computer vision | |
| CN112881999B (en) | Semi-automatic calibration method for multi-line laser radar and vision sensor | |
| CN108195289A (en) | A kind of method measured using line laser to workpiece specific position parameter | |
| Shin et al. | Point to point calibration method of structured light for facial data reconstruction | |
| CN109449096B (en) | Method for identifying and detecting wafer chip |
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 |