CN117664986A - Detection method and detection system suitable for diffuse reflection sample surface - Google Patents
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Abstract
The invention discloses a detection method and a detection system suitable for a diffuse reflection sample surface, wherein the detection method comprises the following steps: s1, setting three stripe patterns with different frequencies; s2, debugging imaging parameters of the light source by using the stripe patterns to obtain working parameters of a detection system; s3, the controller controls the debugged light source to project a stripe pattern to the surface of the sample to be detected; s4, obtaining a stripe image of the stripe pattern on the surface of the sample to be detected through an acquisition camera and sending the stripe image to a controller; s5, the controller processes the image data of the stripe image and outputs a surface defect detection result and a surface type detection result of the sample to be detected. The invention can detect the defect and the surface shape of the diffuse reflection surface and has high detection efficiency.
Description
Technical Field
The invention relates to the technical field of detection equipment, in particular to a detection method and a detection system suitable for a diffuse reflection sample surface.
Background
With the development of society, people have increasingly high requirements on the appearance of consumer goods. In the production process of the product, various defects can be generated on the surface of the product due to complex process flow, so that adverse effects are brought to the aesthetic degree, comfort degree, usability and the like of the product, and if the product is not found and controlled in time, great cost can be wasted.
At present, the mainstream method of defect detection is based on 2D optical imaging and machine vision technology, and the method can overcome the defects of low sampling rate, low accuracy, poor real-time performance, low efficiency, high labor intensity and the like of manual detection to a great extent. However, there are a variety of surface types and surface characteristics in the market where samples need to be inspected, resulting in conventional machine vision requiring extensive non-standard manufacturing effort, time consuming, labor consuming and cost prohibitive. In addition, besides the defect detection requirement, there are many requirements for judging the depth information of the defects, and only the defects with certain depth belong to the true defects, so that the technology based on 2D optical imaging and machine vision only has 2D information, and the requirements of customers are hardly met.
In order to improve the defects of the detection methods of 2D optical imaging and machine vision, non-contact three-dimensional (3D) optical imaging and vision technologies are generated. Currently, the industry is mature and industrial 3D detection technology mainly comprises time-of-flight method, binocular stereo vision, laser scanner, confocal and laser interferometer, etc. The time flight is a point scanning technology, the precision is not high, and the requirements of high precision and high CT of industrial detection cannot be met. The spectrum confocal and laser interferometer can image clearly with high precision, but has low speed, small measuring range and weak anti-interference performance. The laser scanner extracts the central coordinates of the laser lines based on the triangle ranging principle, outputs the reconstructed surface type of the sample to be measured according to the system calibration, has no defect detection function, and has larger repeated error when the surface type of the sample is slightly complex. The binocular stereoscopic vision technology relies on the reconstruction of sample surface characteristic points, has lower reconstruction accuracy for samples without obvious surface characteristics and has no defect detection function. Therefore, the invention aims to provide a detection method which can detect defects and surface types, has high test efficiency and accurate test results.
Disclosure of Invention
The present invention aims to solve at least one of the technical problems of the prior art.
Therefore, the invention provides the detection method and the detection system suitable for the diffuse reflection sample surface, which can detect the defect and the surface type of the diffuse reflection surface and have high detection efficiency.
The technical scheme adopted for solving the technical problems is as follows: a method of detecting a surface of a sample suitable for diffuse reflection, comprising the steps of:
s1, setting three stripe patterns with different frequencies;
s2, debugging imaging parameters of the light source by utilizing the stripe pattern to obtain working parameters of a detection system;
s3, the controller controls the debugged light source to project the stripe pattern to the surface of the sample to be detected;
s4, acquiring a stripe image of the stripe pattern on the surface of the sample to be detected through an acquisition camera and sending the stripe image to the controller;
s5, the controller processes the image data of the stripe image and outputs a surface defect detection result and a surface type detection result of the sample to be detected.
Further, in step S5, outputting a surface defect detection result of the sample to be detected, including:
substituting the image data into a formula of the stripe pattern, and solving background intensity, modulation amplitude and phase information; wherein,
the background intensity and the modulation amplitude can represent three-damage defects, pit defects and protrusion defects on the surface of the sample.
Further, in step S5, outputting the surface type detection result of the sample to be detected includes:
absolute phase extraction is carried out according to the phase information;
carrying out three-dimensional matching according to the absolute phase information to obtain homonymous points of the to-be-measured point under different visual angles;
according to the homonymy points, calculating three-dimensional coordinates of the points to be measured;
the three-dimensional coordinates of all the points to be measured form point cloud data of the sample to be measured;
obtaining a reconstruction surface type of the sample to be detected according to the point cloud data;
and matching the reconstructed surface type with the standard surface type to obtain a surface type detection result of the sample to be detected.
Further, the three-dimensional coordinates (x i ,y i ,z i ) The calculation formula of (2) is as follows:
where f denotes a lens focal length, b denotes a camera base line, (x) il ,y il ) And (x) ir ,y ir ) And represents homonymous points at left and right viewing angles.
Further, the outputting the surface defect detection result of the sample to be detected further includes:
and comparing the point cloud data of the sample to be detected with the point cloud data of the standard sample, and outputting a surface defect detection result.
Further, the acquisition camera is a binocular camera, and the acquisition camera comprises two cameras which are symmetrically arranged left and right.
Furthermore, before the surface type detection, the acquisition camera is calibrated, so that an internal reference matrix and an external reference matrix of the acquisition camera suitable for detection are obtained.
Further, the formula of the stripe pattern is:
wherein,I n light intensity expressed by (x, y), A (x, y) is background light intensity, B (x, y) is modulation amplitude,>representing phase information.
Further, an optical filter is arranged in front of the lens of the acquisition camera.
The invention also provides a detection system suitable for diffusely reflecting the surface of a sample, and the detection method is adopted, and the system comprises the following steps: the light source and the acquisition camera are integrated in one shell, and the light source and the acquisition camera are connected with the controller.
The detection method and the detection system have the beneficial effects that the surface defect detection and the surface type detection of the diffuse reflection sample can be simultaneously completed through one set of system, the image data of one-time imaging operation can be used for the detection in two aspects, the detection efficiency is high, and the precision is high.
Drawings
The invention will be further described with reference to the drawings and examples.
FIG. 1 is a flow chart of the detection method of the present invention.
FIG. 2 is a schematic diagram of the detection system of the present invention.
In the figure: 1. a controller; 2. a light source; 3. and (5) collecting a camera.
Detailed Description
The invention will now be described in further detail with reference to the accompanying drawings. The drawings are simplified schematic representations which merely illustrate the basic structure of the invention and therefore show only the structures which are relevant to the invention.
In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", "axial", "radial", "circumferential", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the device or element being referred to must have a specific orientation, be configured and operated in a specific orientation, and therefore should not be construed as limiting the present invention. Furthermore, features defining "first", "second" may include one or more such features, either explicitly or implicitly. In the description of the present invention, unless otherwise indicated, the meaning of "a plurality" is two or more.
In the description of the present invention, it should be noted that, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention will be understood in specific cases by those of ordinary skill in the art.
As shown in fig. 1, the detection method suitable for diffuse reflection of the surface of a sample of the present invention comprises the following steps: s1, setting three stripe patterns with different frequencies; s2, debugging imaging parameters of the light source by using the stripe patterns to obtain working parameters of a detection system; s3, the controller controls the debugged light source to project a stripe pattern to the surface of the sample to be detected; s4, obtaining a stripe image of the stripe pattern on the surface of the sample to be detected through an acquisition camera and sending the stripe image to a controller; s5, the controller processes the image data of the stripe image and outputs a surface defect detection result and a surface type detection result of the sample to be detected.
It should be noted that, after the stripe pattern is projected onto the surface of the sample to be detected, some parts may deform, the acquisition camera may capture an image of the stripe pattern projected onto the surface of the sample in real time, and the controller may obtain whether or not the surface of the sample has defects and what kind of defects by calculating and processing the image data of the stripe pattern, and may also obtain the surface type information of the sample, so as to analyze whether or not the surface type size of the sample has deviation. That is, the method can realize surface defect detection and surface type detection of the diffuse reflection sample by combining one-time imaging with data processing, is convenient and quick, and is beneficial to improving detection efficiency.
The stripe pattern was obtained by a four-step phase shift method. The formula of the fringe pattern is:
wherein,I n light intensity expressed by (x, y), A (x, y) is background light intensity, B (x, y) is modulation amplitude,>representing phase information, (x, y) representing pixel coordinates. For example, the four stripe patterns at frequency one are:
the four stripe patterns of frequency two are:
the four stripe patterns at frequency three are:
the controller can sequentially send the set stripe patterns to the light source for projection, and the light source adopts a large-aperture low-distortion lens, so that the light source intensity and the contrast and sine of the projected stripe patterns can be ensured. The acquisition camera adopts a high-speed high-resolution CCD, and the camera lens adopts a large-aperture low-distortion lens so as to ensure the intensity, contrast and sine of the acquired fringe image. In addition, the camera is provided with the optical filter in front of the head, so that the influence of ambient light on an imaging result can be reduced to the greatest extent.
It should be noted that the whole test process can be mainly divided into several steps: imaging, collecting and calculating. The defect detection and the surface type detection are obtained by calculating and analyzing the image processing by a controller. I.e. one imaging and acquisition, can be used for both defect detection and area detection.
Before formal detection, the imaging parameters of the light source need to be debugged to obtain the optimal working parameters of the detection system. The debugging process comprises the following steps: selecting a standard ceramic plate as a test sample, then projecting a stripe pattern onto the surface of the test sample to obtain a group of optimal working parameters (including a light source parameter and a camera parameter) on the standard ceramic plate, using the group of optimal working parameters as debugging initial parameters of the sample to be tested, projecting the stripe pattern onto the surface of the sample to be tested, collecting the stripe image on the sample to be tested by a camera, sending the collected stripe image to a controller, judging whether the contrast and the sine of the stripe image are proper by the controller, if not, adjusting the continuous adjustment parameters on the basis of the initial parameters until the contrast reaches 200, enabling the fitting degree of the sine to be higher than 0.95, and taking the group of image parameters which finally meet the requirements as subsequent working parameters. The subsequent imaging effect can be improved by debugging the imaging parameters of the light source, so that the detection precision is improved.
After the imaging parameters of the light source are adjusted, the stripe patterns can be projected to the surface of the sample to be detected in sequence, and the stripe patterns are collected through the collecting camera and sent to the controller. For example, the acquisition camera is a binocular camera, and the acquisition camera includes two cameras arranged in bilateral symmetry. The two cameras are respectively positioned at the left side and the right side of the light source.
For example, outputting the surface defect detection result of the sample to be detected includes: substituting the image data into a formula of the stripe pattern, and solving background intensity, modulation amplitude and phase information; wherein, the background intensity and the modulation amplitude can represent three damage defects, pit defects and protrusion defects of the surface of the sample. That is, the controller substitutes the acquired image data (twelve stripe patterns including three frequencies) into the above-mentioned corresponding stripe pattern formula to solve A (x, y), B (x, y),And->A (x, y) represents background light intensity, has good characterization capability mainly for different colors, and has good characterization effect on defects such as three wounds, pits, bulges and the likeSome characterization capability is trapped, but background information can affect defect detection. B (x, y) represents modulation amplitude, has good characterization capability on defects such as three wounds, pits, bulges and the like, and can avoid the influence of the background on defect detection. Thus, by analysis of a (x, y) and/or B (x, y), it is possible to find whether and which defects are present on the surface of the sample to be measured. For example, after the background light intensity and the modulation amplitude are extracted, a picture is generated for display, and the defect morphology can be distinguished by observing the morphology of the defect position in the picture.
Before the controller analyzes the surface shape of the sample to be detected, the acquisition camera needs to be calibrated to obtain the conversion relation between the world coordinate system and the pixel coordinate system of the point to be detected on the surface of the sample to be detected, and the distortion coefficient and the external reference matrix of the acquisition camera suitable for detection are obtained. The world coordinate system of the point to be measured is transformed into the camera coordinate system by rigid transformation, the camera coordinate system is transformed into the image coordinate system by projection, and the image coordinate system is transformed into the pixel coordinate system by translation. By calibration, the internal parameters of the camera (i.e. the focal length f, distortion coefficient s, center point coordinates (x) 0 ,y 0 ) Aspect ratio parameter a) and world coordinate system rigid transformation to an extrinsic matrix [ R|t ] of a camera coordinate system]. The conversion relationship between the pixel coordinates (X, Y) and the world coordinates (X, Y, Z) is:
wherein R represents a rotation matrix from world coordinates to a camera coordinate system, and t represents a translation vector from world coordinates to the camera coordinate system, so that the known pixel coordinates can quickly obtain the corresponding world coordinates, thereby facilitating subsequent data processing of the controller.
For example, the controller outputs a surface type detection result of the sample to be detected, including: absolute phase extraction is carried out according to the phase information; carrying out three-dimensional matching according to the absolute phase information to obtain homonymous points of the to-be-measured point under different visual angles; calculating the three-dimensional coordinates of the to-be-measured point according to the homonymy points; the three-dimensional coordinates of all the points to be measured form point cloud data of the sample to be measured; obtaining a reconstruction surface type of the sample to be detected according to the point cloud data; and matching the reconstructed surface type with the standard surface type to obtain a surface type detection result of the sample to be detected.
The phase obtained by the above-described solutionAnd->The relative phases may be the same phase for different pixels. Therefore, absolute phase extraction is required so that each pixel has a unique corresponding phase value. For example, by projecting fringe images of three frequencies, the phase is shifted using heterodyne principlesAdding to obtain->Phase->Superposition to obtainThen, the phase +.>And->Superposing to obtain a phase of only one cycle in the whole range>The absolute phase calculation may then be performed. Each frequency can extract a corresponding absolute phase. For example, taking frequency one as an example, absolute phase φ 1 The calculation formula of (x, y):wherein (1)>R 1 Representing the ratio between frequency one and frequency two.
After absolute phase extraction, each pixel point has a unique phase value. Then, stereo correction is performed on the acquisition camera. The purpose of the stereo correction is to keep the optical axes of the two cameras of the binocular camera parallel so that the image points are of uniform height on the left and right images. Therefore, when stereo matching is carried out, only the same row is needed to be searched, and the working efficiency can be improved. The stereo matching is used to find the matching corresponding points from different viewpoint images. Since the acquisition cameras are binocular cameras, both cameras can shoot images (i.e. can obtain a left image and a right image), and the objects shot by the two cameras are identical, i.e. a target point appears on the left image and the right image at the same time. The purpose of stereo matching is to find the homonymous point of this target point in the left image and in the right image. Thus, a plurality of characteristic points of the sample to be measured can be obtained, and the characteristic of the sample is not needed to be relied on.
After stereo matching, according to the found homonymous points, the three-dimensional coordinates (x i ,y i ,z i ). The calculation formula is as follows:wherein, represents lens focal length, b represents camera baseline, (x) il ,y il ) And (x) ir ,y ir ) And represents homonymous points at left and right viewing angles. And forming point cloud data of the sample to be measured by the three-dimensional coordinates of all the points to be measured. The point cloud data has two uses, namely, the point cloud data can be used for surface type detection; and secondly, the method can be used for defect detection. Obtaining a reconstruction surface shape of the sample to be detected according to the point cloud data, matching the reconstruction surface shape with a standard surface shape, and obtaining a surface shape detection result of the sample to be detected, namely whether the surface shape size has deviation and how much the deviation existsA location where the deviation is, etc. Although a surface defect detection scheme (by background light intensity and modulation amplitude) has been provided in the foregoing, these two parameters do not detect all types of defects. The point cloud data has obvious change on the rendering map due to the stress effect in the defect area. Therefore, by analyzing the point cloud data, a defect detection result of the sample surface can be obtained, for example, the obtained point cloud data is subjected to elevation rendering, and for a defective place, the color is obviously different from that of a surrounding normal area. According to the characteristics, defects are identified and classified by combining the existing defect morphology identification algorithm, and defects such as scratches, pits, bulges and the like can be detected. In addition, the working parameter system in the test process can be automatically acquired, and a complex debugging process is avoided.
As shown in fig. 2, the present invention further provides a detection system suitable for diffusely reflecting a surface of a sample, and the detection method is adopted, and the system includes: the controller 1, the light source 2 and the acquisition camera 3 are integrated in a shell, the two cameras are respectively positioned at the left side and the right side of the light source 2, and the light source 2 and the acquisition camera 3 are both connected with the controller 1. The detection system provided by the invention has the advantages that the number of parts is small, and one set of detection system can be suitable for detecting defects and surface types of different detection scenes, such as die castings, spray-coated parts, automobile interior parts, electronic products and the like.
In summary, the detection method, the detection system and the bronze drum system can simultaneously finish surface defect detection and surface type detection of the diffuse reflection sample, and image data of one imaging operation can be used for detection in two aspects, so that the detection efficiency is high and the precision is high.
With the above-described preferred embodiments according to the present invention as an illustration, the above-described descriptions can be used by persons skilled in the relevant art to make various changes and modifications without departing from the scope of the technical idea of the present invention. The technical scope of the present invention is not limited to the description, but must be determined as the scope of the claims.
Claims (10)
1. A method for detecting a surface of a diffusely reflecting sample, comprising the steps of:
s1, setting three stripe patterns with different frequencies;
s2, debugging imaging parameters of the light source by utilizing the stripe pattern to obtain working parameters of a detection system;
s3, the controller controls the debugged light source to project the stripe pattern to the surface of the sample to be detected;
s4, acquiring a stripe image of the stripe pattern on the surface of the sample to be detected through an acquisition camera and sending the stripe image to the controller;
s5, the controller processes the image data of the stripe image and outputs a surface defect detection result and a surface type detection result of the sample to be detected.
2. The method for detecting a surface of a diffusely reflecting sample according to claim 1, wherein outputting the surface defect detection result of the sample to be detected in step S5 comprises:
substituting the image data into a formula of the stripe pattern, and solving background intensity, modulation amplitude and phase information; wherein,
the background intensity and the modulation amplitude can represent three-damage defects, pit defects and protrusion defects on the surface of the sample.
3. The method for detecting a surface of a diffusely reflecting sample according to claim 2, wherein outputting the surface type detection result of the sample to be detected in step S5 comprises:
absolute phase extraction is carried out according to the phase information;
carrying out three-dimensional matching according to the absolute phase information to obtain homonymous points of the to-be-measured point under different visual angles;
according to the homonymy points, calculating three-dimensional coordinates of the points to be measured;
the three-dimensional coordinates of all the points to be measured form point cloud data of the sample to be measured;
obtaining a reconstruction surface type of the sample to be detected according to the point cloud data;
and matching the reconstructed surface type with the standard surface type to obtain a surface type detection result of the sample to be detected.
4. A method for detecting a surface of a sample adapted for diffuse reflection according to claim 3, characterized in that the three-dimensional coordinates (x i ,y i ,z i ) The calculation formula of (2) is as follows:
where f denotes a lens focal length, b denotes a camera base line, (x) il ,y il ) And (x) ir ,y ir ) And represents homonymous points at left and right viewing angles.
5. The method for detecting a surface of a diffusely reflecting sample according to claim 3, wherein the outputting of the detection result of the surface defect of the sample to be detected further comprises:
and comparing the point cloud data of the sample to be detected with the point cloud data of the standard sample, and outputting a surface defect detection result.
6. A method for detecting a surface of a diffusely reflecting sample as claimed in claim 3, wherein the collection camera is a binocular camera comprising two cameras arranged symmetrically left and right.
7. The method of claim 6, wherein the acquisition camera is calibrated prior to performing the area-type detection to obtain an internal reference matrix and an external reference matrix of the acquisition camera suitable for detection.
8. The method for detecting a surface of a sample for diffuse reflection according to claim 2, wherein the formula of the fringe pattern is:
wherein,n∈[1,N]，N＝4，k＝1，2，3；I n light intensity expressed by (x, y), A (x, y) is background light intensity, B (x, y) is modulation amplitude,>representing phase information.
9. The method for detecting a surface of a diffusely reflecting sample according to claim 1, wherein a filter is provided in front of a lens of the collecting camera.
10. A detection system adapted to diffusely reflect a surface of a sample, wherein a detection method according to any one of claims 1 to 9 is employed, the system comprising: the light source and the acquisition camera are integrated in one shell, and the light source and the acquisition camera are connected with the controller.
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