CN210664378U - Customized light source roughness detection device based on red-green chromatic aberration - Google Patents
Customized light source roughness detection device based on red-green chromatic aberration Download PDFInfo
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Abstract
The utility model provides a customization light source roughness measurement device based on red green colour difference belongs to roughness measurement technical field. The detection device comprises a detection platform, a customized color light source, an image acquisition unit and an intelligent terminal; the customized color light source comprises a lamp holder, a lamp bead and a square lampshade, and the square lampshade is arranged on the surface of the lamp holder; the image acquisition unit is a camera, the customized color light source and the image acquisition unit are arranged above the detection platform through a support, the light emitted by the customized color light source and the image acquisition unit face the surface of an object to be detected on the detection platform, and the included angle between the plane center normal of the square lampshade and the normal of the upper surface of the object to be detected is theta1Method of obtaining optical axis of image obtaining unit and upper surface of object to be measuredAngle of line theta2Theta of1、θ2Are all less than 90 DEG, and theta1＝θ2(ii) a The device directly designs the color blocks into light sources, can reduce the reflection process of primary light, simplifies the light path design and improves the feasibility for realizing online detection of roughness detection.
Description
[ technical field ] A method for producing a semiconductor device
The utility model relates to a work piece surface roughness detects technical field, concretely relates to customization light source roughness detection device based on red green colour difference.
[ background of the invention ]
The machine vision detection method of surface roughness generally performs objective quantization on image gray value information by analyzing gray level images, and then obtains the relationship between the surface roughness and machine vision indexes by applying image texture analysis technology (the image texture analysis technology is generally summarized into three categories of frequency spectrum, structure and statistics). Because the gray level image is a degraded image, the sensitivity of the image characteristics to the surface roughness is reduced to a certain extent, and the gray level image cannot be subjectively judged visually; moreover, the application of more gray level co-occurrence matrix methods needs to be combined with a microscopic device, so that the test view field is small, the operation is inconvenient, and the working efficiency is low. In addition, the frequency spectrum characteristics of Fourier transform have better robustness to the texture characteristics with periodic regularity, but for the grinding workpiece with larger randomness of the texture characteristics, the sensitivity is not strong when the surface roughness is judged by the frequency spectrum characteristics, the prediction accuracy of the artificial neural network is greatly influenced by the factors such as the number of training samples, training parameters, network structures and the like, and the prediction accuracy cannot be ensured in the case of small samples. Literature indicates that color is a sensitive delineation factor that often simplifies the extraction and recognition of objects from a scene, and few quantitatively predict surface roughness by studying color image quality. Since the ground sample itself does not have a distinct color feature, it is difficult to obtain significant color difference information by directly shooting the sample. Ancient people used copper as a mirror, observed appearances by utilizing virtual images very early, whether the appearances are clear or not is related to the smoothness of the surface of the copper mirror, and most metal surfaces are easy to generate the virtual images. The color block is used as a reference object, and the surface roughness of the sample is judged according to the definition change of a virtual image on the surface of the sample. Meanwhile, the objective index of definition is combined with subjective evaluation of a Human Visual System (HVS), so that the surface roughness of the workpiece can be detected quickly and accurately.
The chinese utility model patent publication No. CN104848808B discloses a surface roughness detection method, which comprises: acquiring a corresponding relation between definition and the surface roughness of the object, wherein the definition is the definition of a virtual image formed on the surface of the object by a reference object; acquiring an image corresponding to a virtual image formed on the surface of an object to be detected by a reference object; calculating the definition value of the image; and calculating the surface roughness corresponding to the definition of the image according to the corresponding relation, and taking the surface roughness as the surface roughness of the object to be measured. Although the proposal also adopts the color block as a reference object to establish the corresponding relation between the acquired definition and the surface roughness of the object, the proposal has the following defects: the reference object adopted by the scheme is a color block, and the imaging principle is that light irradiates on the color block, is reflected to the surface of the object to be measured through the color block, and is reflected to a camera for imaging through the surface light of the object to be measured. The light emitted from the light source can reach the camera for imaging only through at least secondary reflection, which undoubtedly adds difficulty to the design of the light path for engineering practice.
[ Utility model ] content
The utility model discloses a utility model aim at: aiming at the existing problems, the customized light source roughness detection device based on the red-green chromatic aberration is provided, and the device directly designs the color block into the light source, so that the reflection process of primary light can be reduced, the light path design is simplified, and the feasibility for realizing online detection of roughness detection is improved.
In order to realize the purpose, the utility model discloses a technical scheme as follows:
the utility model also provides a customized light source roughness detection device based on red-green chromatic aberration, which comprises a detection platform, a customized color light source, an image acquisition unit and an intelligent terminal;
the detection platform is used for bearing an object to be detected;
the customized color light source comprises a lamp holder, a lamp bead and a square lampshade, and the square lampshade is arranged on the surface of the lamp holder; the image acquisition unit is a camera, the customized color light source and the image acquisition unit are both arranged above the detection platform through a support, and the light emitted by the customized color light source and the image acquisition unit are arrangedThe lenses face the surface of the object to be detected on the detection platform, and the included angle between the plane center normal of the square lampshade and the normal of the upper surface of the object to be detected is theta1The included angle between the optical axis of the image acquisition unit and the normal of the upper surface of the object to be measured is theta2The plane center normal of the square lampshade and the optical axis of the image acquisition unit are positioned on two sides of the normal of the upper surface of the object to be detected, and theta1、θ2Are all less than 90 DEG, and theta1＝θ2；
The image acquisition unit is connected with the intelligent terminal and is used for acquiring an image corresponding to a virtual image formed by the customized color light source on the surface of the object to be measured and sending the image to the intelligent terminal;
the intelligent terminal comprises a storage module and a roughness calculation module; and the intelligent terminal is in communication connection with the image acquisition unit.
Preferably, the customized color light source comprises 2 or 4 lamp beads, and each lamp bead is independently covered by the same square lampshade; half of the red light beads are red light beads, and the other half of the green light beads are green light beads; when the number of the lamp beads is 2, arranging one row; when the number of the lamp beads is 4, two rows of 2 lamp beads are arranged, and the colors of the adjacent lamp beads are different.
Preferably, the device also comprises a multi-channel digital display light source controller, each channel of the light source controller controls one of the lamp beads, and the light source controller can control the brightness of the lamp beads.
Preferably, the image acquisition unit is a CCD camera.
To sum up, owing to adopted above-mentioned technical scheme, the beneficial effects of the utility model are that:
1. the utility model discloses customization light source roughness measurement method based on red green colour difference obtains the image that customization light source reference object is waiting to detect the virtual image that the thing surface formed and corresponds, and this image is the color image, and non-grey level image therefore does not have the process of image degradation for image processing's accuracy improves, thereby makes roughness measurement result's accuracy higher.
2. The utility model discloses customization light source roughness detection device based on red green colour difference to the customization light source compares in adopting color lump and LED light source complex mode for reference matter, directly designs into the light source with the color lump, can reduce the reflection process of primary light, makes the light path design obtain simplifying, realizes on-line measuring for average colour difference index and has improved the feasibility.
[ description of the drawings ]
Fig. 1 is the utility model discloses customization light source roughness measurement device's structural schematic diagram based on red green colour difference.
Fig. 2 is a schematic plan view of the customized color light source of the present invention.
Fig. 3 is a flow chart of the detection method for roughness detection according to the present invention.
The system comprises a support 1, a customized color light source 2, a camera 3, an intelligent terminal 4, an object to be detected 5, a detection platform 6, a virtual image 7 and a light source controller 8.
[ detailed description ] embodiments
In order to express the present invention more clearly, the present invention will be further described below by way of specific examples.
When the color block is used as a reference object, the virtual image of the color block on the surface of the workpiece is obtained, and the imaging principle is that light irradiates on the color block, is reflected to the surface of the workpiece through the color block and is reflected to a camera for imaging through the surface of the workpiece. The light emitted from the light source can reach the camera for imaging only by at least secondary reflection, which undoubtedly increases the difficulty of light path design for engineering practice, and if the color block is directly designed into the light source, the primary light reflection process can be reduced, and the feasibility for realizing online detection of the surface roughness is improved.
Fig. 1 shows the customized light source roughness detection device based on red-green color difference of the present invention, which comprises a detection platform 6, a customized color light source 2, an image acquisition unit 3 and an intelligent terminal 4;
the detection platform 6 is used for bearing an object 5 to be detected, and preferably adopts a precise optical test bench;
the customized color light source 2 comprises a lamp holder, a lamp bead and a square lampshade, and the surface of the lamp holder is provided withA square lampshade is arranged; the image acquisition unit 3 is a camera, preferably a CCD camera. The customized color light source 2 and the image acquisition unit 3 are both arranged above the detection platform 6 through the support 1, the light emitted by the customized color light source 2 and the lens of the image acquisition unit all face the surface of an object to be detected 5 on the detection platform, and the included angle between the plane center normal of the square lampshade and the normal of the upper surface of the object to be detected is theta1The included angle between the optical axis of the image acquisition unit and the normal of the upper surface of the object to be measured is theta2The plane center normal of the square lampshade and the optical axis of the image acquisition unit are positioned on two sides of the normal of the upper surface of the object to be detected, and theta1、θ2Are all less than 90 DEG, and theta1＝θ2；
The image acquisition unit 3 is connected with the intelligent terminal 4, and the image acquisition unit 3 is used for acquiring an image corresponding to a virtual image formed by the customized color light source 1 on the surface of the object 5 to be measured and sending the image to the intelligent terminal 4 through the wireless communication module;
the intelligent terminal 4 comprises a storage module and a roughness calculation module, and preferably adopts a computer; the intelligent terminal 4 is in communication connection with the image acquisition unit 3. The roughness calculating module is used for calculating the average color difference index of the virtual image according to the virtual image sent by the image acquiring unit 3, and then calculating the surface roughness of the object to be measured according to the corresponding relation stored in the storage module; the calculation principle of the correspondence between the average color difference index of the virtual image and the surface roughness of the object is the prior art, and is not described in detail herein.
In the embodiment, the customized color light source 1 comprises 2 or 4 lamp beads, and each lamp bead is independently covered by the same square lampshade; half of the red light beads are red light beads, and the other half of the green light beads are green light beads; when the number of the lamp beads is 2, arranging one row; when the number of the lamp beads is 4, two rows of 2 lamp beads are arranged, and the colors of the adjacent lamp beads are different. Fig. 3 shows a structure provided with four lamp beads, in this embodiment, the lamp shade is a plastic lamp shade with a side length of 40mm, and the distance between the lamp shades is set to be 2 mm. The voltage of a customized red and green light source is 24V, the power of a red light is 0.9W, the power of a green light is 1.8W, the brightness interval is 85-120, and a lampshade is made of transparent plastic.
In other embodiments, the device further comprises a multi-channel digital display light source controller, each channel of the light source controller controls one of the lamp beads, and the light source controller can control the brightness of the lamp beads.
The utility model discloses when implementing, utilize above-mentioned device to carry out the roughness, can adopt following detection method to carry out the roughness detection, figure 3 shows the flow chart of this detection method, including following step:
(1) the method comprises the steps that a red-green customized light source is used as a reference object, so that the reference object forms virtual images on the surfaces of a group of standard test blocks with different roughness, the average chromatic aberration index of each virtual image is calculated, and the corresponding relation between the average chromatic aberration index of the virtual images and the surface roughness of an object is established according to the surface roughness of each standard test block and the calculated average chromatic aberration index value;
in this step, the standard test block is a group of test blocks with different surface roughness, each standard test block and the block to be tested should be made of the same material, and the surface texture direction should be the same. The customized light source is a red-green customized light source, and the two colors are beneficial to the simple judgment of a human visual system; the customized light source adopts the power controller to control the brightness of the customized light source, so that the proper brightness can be conveniently selected as the standard brightness for testing according to different materials.
In the above steps, the average color difference index is calculated by the following formula:
wherein M and N are the number of pixels in length and the number of pixels in width of the virtual image, R(i,j)-G(i,j)Representing the red-green colour difference, R, of each point on the virtual image(i,j)Representing the value of the red component at point (i, j) in the image, G(i,j)A value representing the green component at point (i, j) in the image;
and after the average color difference index is calculated, establishing the relation between the average color difference index and the surface roughness value by adopting a least square method.
(2) Acquiring an image corresponding to a virtual image formed on the surface of an object to be detected by a reference object; in this step, the setting conditions of the reference object and other test conditions are the same as those in the test of the standard test block, so as to maintain the test identity.
(3) And (3) calculating the average color difference index of the image in the step (2), and calculating the surface roughness corresponding to the average color difference index of the image according to the corresponding relation in the step (1) to be used as the surface roughness of the object to be measured.
The above description is for the detailed description of the preferred possible embodiments of the present invention, but the embodiments are not intended to limit the scope of the present invention, and all equivalent changes or modifications accomplished under the technical spirit suggested by the present invention should fall within the scope of the present invention.
Claims (4)
1. Customization light source roughness detection device based on red green colour difference, its characterized in that: the system comprises a detection platform (6), a customized color light source (2), an image acquisition unit (3) and an intelligent terminal (4);
the detection platform (6) is used for bearing an object to be detected (5);
the customized color light source (2) comprises a lamp holder, a lamp bead and a square lampshade, and the square lampshade is arranged on the surface of the lamp holder; image acquisition unit (3) are the camera, customization colored light source (2) and image acquisition unit (3) all set up in the top of testing platform (6) through support (1), and the light sum image acquisition unit's of customization colored light source (2) transmission camera lens all faces the last surface of awaiting measuring article (5) of testing platform, the contained angle of the plane center normal of square lampshade and the normal of the article upper surface that awaits measuring is theta1The included angle between the optical axis of the image acquisition unit and the normal of the upper surface of the object to be measured is theta2The plane center normal of the square lampshade and the optical axis of the image acquisition unit are positioned on two sides of the normal of the upper surface of the object to be detected, and theta1、θ2Are all less than 90 DEG, and theta1＝θ2；
The image acquisition unit (3) is connected with the intelligent terminal (4), and the image acquisition unit (3) is used for acquiring an image corresponding to a virtual image formed by the customized color light source (2) on the surface of the object to be measured (5) and sending the image to the intelligent terminal (4);
the intelligent terminal (4) comprises a storage module and a roughness calculation module; and the intelligent terminal (4) is in communication connection with the image acquisition unit (3).
2. The device for detecting the roughness of the customized light source based on the red-green chromatic aberration as claimed in claim 1, wherein: the customized color light source (2) comprises 2 or 4 lamp beads, and each lamp bead is independently covered by the same square lampshade; half of the red light beads are red light beads, and the other half of the green light beads are green light beads; when the number of the lamp beads is 2, arranging one row; when the number of the lamp beads is 4, two rows of 2 lamp beads are arranged, and the colors of the adjacent lamp beads are different.
3. The device for detecting the roughness of the customized light source based on the red-green chromatic aberration as claimed in claim 1, wherein: the device also comprises a multi-channel digital display light source controller (8), wherein each channel of the light source controller (8) controls one of the lamp beads, and the light source controller (8) can control the brightness of the lamp beads.
4. The device for detecting the roughness of the customized light source based on the red-green chromatic aberration as claimed in claim 1, wherein: the image acquisition unit (3) is a CCD camera.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112098333A (en) * | 2020-11-17 | 2020-12-18 | 北京领邦智能装备股份公司 | High-precision imaging system and method, image acquisition device and detection equipment |
| CN113418476A (en) * | 2021-07-09 | 2021-09-21 | 扬州大学 | Device and method for measuring roughness of tooth surface of grinding tooth based on machine vision |
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2019
- 2019-07-31 CN CN201921219416.7U patent/CN210664378U/en active Active
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112098333A (en) * | 2020-11-17 | 2020-12-18 | 北京领邦智能装备股份公司 | High-precision imaging system and method, image acquisition device and detection equipment |
| CN112098333B (en) * | 2020-11-17 | 2021-04-02 | 北京领邦智能装备股份公司 | High-precision imaging system and method, image acquisition device and detection equipment |
| CN113418476A (en) * | 2021-07-09 | 2021-09-21 | 扬州大学 | Device and method for measuring roughness of tooth surface of grinding tooth based on machine vision |
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