Detection method, detection system and computer readable storage medium

Abstract

The invention discloses a detection method, a detection system and a computer readable storage medium. The detection method is used for the industrial camera and comprises the steps that the industrial camera is moved to a detection position facing a calibration plate, and the calibration plate is provided with a calibration pattern; acquiring an image of the calibration plate through an industrial camera; determining parameters of the calibration pattern in the image; and comparing the parameters with corresponding preset reference values, and detecting whether the parameters of the industrial camera are abnormal or not. According to the detection mechanism provided by the invention, the parameters of the industrial camera can be detected under the condition that a hardware structure is not disassembled, and the detection efficiency and the reliability of a detection result are improved.

Description

Technical Field

[0001] The present disclosure generally relates to the field of detection, and more particularly to a detection method, a detection system, and a computer-readable storage medium. Background Art

[0002] In modern industrial production, industrial imaging systems are often used as the eyes of automation equipment, and are widely used to guide actuators to grab materials, assemble materials, and check the status of products after the process is completed. Generally speaking, industrial imaging systems include cameras, lenses, and light sources. In order to give full play to the role of "eyes", industrial cameras need to collect clear and contrasty photos, which mainly depends on: the exposure time of the camera, the working position of the camera, the aperture size of the lens, the focal distance of the lens, and the brightness of the light source. In traditional industrial production processes, the working distance of industrial cameras, lens-related hardware parameters, and light source brightness generally rely on manual or mechanical adjustments. Once it is determined that they will no longer be adjusted within a certain time range, this method lacks detection feedback. Once the parameters affecting imaging change, it cannot be known in time, let alone timely detection and correction. If the image quality collected by industrial cameras is reduced, the actuators will not be accurately guided to perform tasks, thereby reducing the reliability of automation equipment. Therefore, it is necessary to propose a new solution to optimize the detection of industrial cameras.

[0003] The contents of the background technology section are merely the technologies known to the inventors and do not necessarily represent the prior art in the field. Summary of the invention

[0004] In response to one or more problems existing in the prior art, the present disclosure provides a detection method for an industrial camera, the detection method comprising: moving the industrial camera to a detection position facing a calibration plate, wherein the calibration plate has a calibration pattern; acquiring an image of the calibration plate by the industrial camera; determining parameters of the calibration pattern in the image; and comparing the parameters with corresponding preset reference values ​​to detect whether the parameters of the industrial camera are abnormal.

[0005] Optionally, the calibration pattern includes at least one of a positioning point or a grayscale detection area.

[0006] Optionally, determining the parameters of the calibration pattern in the image includes: acquiring the coordinates of the positioning point in the image, or the position of the grayscale detection area.

[0007] Optionally, determining the parameters of the calibration pattern in the image includes: adjusting the position of the grayscale detection area in the image according to the coordinates of the positioning point in the image.

[0008] Optionally, the step of detecting the parameters of the industrial camera includes: detecting whether a working position of the industrial camera is abnormal according to the coordinates of the positioning point in the image.

[0009] Optionally, determining the parameter of the calibration pattern in the image includes: detecting the grayscale of the grayscale detection area.

[0010] Optionally, the detecting the parameters of the industrial camera includes: judging whether the aperture and the brightness of the light source are abnormal according to the grayscale detection result.

[0011] Optionally, determining the parameter of the calibration pattern in the image includes: detecting a boundary of the grayscale detection area to obtain the sharpness of the grayscale detection area.

[0012] Optionally, the detecting the parameters of the industrial camera includes: judging whether the focal length is abnormal according to the sharpness detection result.

[0013] Optionally, the detection method further includes: when it is determined that the parameters of the industrial camera are abnormal, correcting the parameters of the industrial camera.

[0014] Optionally, the detection method further includes: moving the industrial camera to a detection position facing the calibration plate by controlling an actuator on which the industrial camera is installed.

[0015] Optionally, the detection method also includes: calibrating parameters of the industrial camera; moving the industrial camera to the detection position; acquiring an image of the calibration plate through the industrial camera; and determining parameters of the calibration pattern in the image as the preset reference value.

[0016] The present disclosure also provides a detection system, including: a calibration plate having at least one calibration pattern; an industrial camera installed on an actuator of an industrial robot; and a controller communicating with the industrial camera and configured to execute the detection method as described above.

[0017] The present disclosure also provides a computer-readable storage medium, including computer-executable instructions stored thereon, and when the executable instructions are executed by a processor, the detection method as described above is implemented.

[0018] The detection method and detection system disclosed in the present invention can realize the detection of industrial cameras without interrupting the production process. Specifically, it can detect whether one or more parameters of the working position, aperture, light source brightness and focal length are abnormal. In particular, without disassembling the hardware structure, the detection of lens-related hardware parameters can be realized, which improves the detection efficiency and the reliability of the detection results. When a parameter abnormality is detected, the corresponding parameters can be corrected in time, which improves the reliability of the industrial camera, helps the industrial camera to capture clear images with good contrast, and ensures image quality. When it is applied to automated equipment, it helps to more accurately guide the actuator to grab materials, assemble materials, and check the product status after the process is completed, thereby improving the reliability of the automated equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The accompanying drawings are used to provide a further understanding of the present disclosure and constitute a part of the specification. Together with the embodiments of the present disclosure, they are used to explain the present disclosure and do not constitute a limitation of the present disclosure. In the accompanying drawings: Figure 1 A schematic diagram of a detection method according to some embodiments of the present disclosure is shown.

[0020] Figure 2 A schematic diagram of a detection system according to some embodiments of the present disclosure is shown.

[0021] Figure 3 Schematic diagrams of calibration plates according to other embodiments of the present disclosure are shown.

[0022] Figure 4 Schematic diagrams of calibration plates according to further embodiments of the present disclosure are shown. DETAILED DESCRIPTION

[0023] In the following, only some exemplary embodiments are briefly described. As those skilled in the art will appreciate, the described embodiments may be modified in various ways without departing from the spirit or scope of the present disclosure. Therefore, the drawings and descriptions are considered to be exemplary and non-restrictive in nature.

[0024] In the description of the present disclosure, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, which are only for the convenience of describing the present disclosure and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present disclosure. In addition, the terms "first" and "second" are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present disclosure, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0025] In the description of the present disclosure, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", and "coupled" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection, an electrical connection, or can communicate with each other; it can be a direct connection, or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present disclosure can be understood according to specific circumstances.

[0026] In the present disclosure, unless otherwise clearly specified and limited, a first feature being "above" or "below" a second feature may include that the first and second features are in direct contact, or may include that the first and second features are not in direct contact but are in contact through another feature between them. Moreover, a first feature being "above", "above" and "above" a second feature includes that the first feature is directly above and obliquely above the second feature, or simply means that the first feature is higher in level than the second feature. A first feature being "below", "below" and "below" a second feature includes that the first feature is directly below and obliquely below the second feature, or simply means that the first feature is lower in level than the second feature.

[0027] Many different embodiments or examples are provided below to implement different structures of the present disclosure. In order to simplify the present disclosure, the components and settings of specific examples are described below. Of course, they are only examples, and the purpose is not to limit the present disclosure. In addition, the present disclosure may repeat reference numbers and / or reference letters in different examples, and this repetition is for the purpose of simplicity and clarity, and does not itself indicate the relationship between the various embodiments and / or settings discussed. In addition, the present disclosure provides various specific examples of processes and materials, but those of ordinary skill in the art may be aware of the application of other processes and / or the use of other materials.

[0028] Some embodiments of the present disclosure are described below in conjunction with the accompanying drawings. It should be understood that some embodiments described herein are only used to illustrate and explain the present disclosure, and are not used to limit the present disclosure.

[0029] The present disclosure provides a detection method for an industrial camera. The detection method comprises: moving the industrial camera to a detection position facing a calibration plate, wherein the calibration plate has a calibration pattern; collecting an image of the calibration plate by the industrial camera; determining a parameter of the calibration pattern in the image; comparing the parameter with a corresponding preset reference value to detect whether the parameter of the industrial camera is abnormal.

[0030] The present disclosure also provides a detection system. The detection system includes a calibration plate, an industrial camera and a controller. The calibration plate has at least one calibration pattern. The industrial camera is installed on an actuator of an industrial robot. The controller communicates with the industrial camera and can execute the detection method.

[0031] The detection method and detection system disclosed in the present invention can detect whether the parameters of the industrial camera are abnormal, which is conducive to timely correction and improves the reliability of the industrial camera. When it is applied to automation equipment, the industrial camera, as the eyes of the automation equipment, can more accurately guide the actuator to grab materials, assemble materials, and check the status of the product after the process is completed. The detection method and detection system disclosed in the present invention are introduced in detail below.

[0032] Figure 1 FIG. 1 is a schematic diagram of a detection method 10 according to some embodiments of the present disclosure. Figure 1 As shown, the detection method 10 includes steps S11 to S14. Step S11, moving the industrial camera to a detection position facing a calibration plate, on which a calibration pattern is provided. Step S12, capturing an image of the calibration plate through the industrial camera. Step S13, determining the parameters of the calibration pattern in the image. Step S14, comparing the parameters with corresponding preset reference values ​​to detect whether the parameters of the industrial camera are abnormal. Before introducing each step in detail, the detection system of the present invention is first introduced.

[0033] Figure 2FIG. 2 shows a schematic diagram of a detection system 20 according to some embodiments of the present disclosure. Figure 2 As shown, the detection system 20 includes a calibration plate 21, an industrial camera 22 and a controller 23. The calibration plate 21 has a calibration pattern 211. The industrial camera 22 can be installed on an actuator (not shown) of an industrial robot (not shown). The controller 23 communicates with the industrial camera 22 and can execute the detection method 10 and its various steps.

[0034] like Figure 2 As shown, the calibration pattern 211 may include at least one of the first area R1 and the second area R2. For example, the calibration pattern 211 may include a positioning point M. The positioning point M is located in the first area R1, for example, it can be a circular cross intersection, but is not limited thereto. For another example, the calibration pattern 211 also includes a grayscale detection area Ag. The grayscale detection area Ag is located in the second area R2. The grayscale detection area Ag includes a grayscale detection point N. The position of the grayscale detection point N can be used as the position of the grayscale detection area Ag. The grayscale detection point N and the positioning point M have a preset relative position relationship. According to the position of the positioning point M, and the relative position relationship between the grayscale detection point N and the positioning point M, the position of the grayscale detection point N can be determined.

[0035] It should be noted that Figure 2 One grayscale detection point N is shown, but the present disclosure is not limited thereto, and in practical applications, multiple grayscale detection points N may be set. The average value of the positions of the multiple grayscale detection points N may be used as the position of the grayscale detection area Ag. Figure 2 The illustrated calibration pattern 211 is only shown as an example and does not constitute a limitation to the present disclosure. In practical applications, it can be adjusted according to needs. Figure 2 In the embodiment of the present invention, the positioning point M and the grayscale detection area Ag are respectively located in two different areas of the same calibration plate. Although not shown in the figure, it can be understood that the positioning point M and the grayscale detection area Ag can also be located in the same area of ​​the same calibration plate, or respectively located on two calibration plates, which are all within the protection scope of the present disclosure.

[0036] In some embodiments, the industrial camera 22 can be installed on the actuator of the industrial robot. The actuator can be, for example, a robotic arm. When the actuator of the industrial robot moves, the industrial camera can be driven to move.

[0037] The present disclosure does not limit the type of industrial camera 22. The industrial camera 22 can be various types of industrial cameras, including but not limited to CCD cameras, CMOS cameras, line array cameras, area array cameras, interlaced scan cameras, progressive scan cameras, normal resolution cameras, high resolution cameras, analog cameras, digital cameras, monochrome (black and white) cameras, color cameras, normal speed cameras, high-speed cameras, visible light (normal) cameras, infrared cameras, ultraviolet cameras, 2D cameras, 3D cameras, etc.

[0038] Although not shown in the figure, the industrial camera 22 includes a lens, a light source, a controller, a memory, etc. The light source is installed on the industrial camera. The light source can be various types of light sources, for example, a ring light source, a bar light source, a coaxial light source, a dome light source, a surface light source, a point light source, a plane shadowless light source, a line scanning light source, etc., and can be an LED light source, or can also be a laser light source, but is not limited thereto.

[0039] In some embodiments, Figure 2 As shown, the controller 23 is external to the industrial camera 22. In other embodiments, although not shown in the figure, the controller 23 may also be built into the industrial camera 22 or the industrial robot, which are all within the protection scope of the present disclosure.

[0040] In some embodiments, the controller 23 may include a control circuit, a central processing unit (CPU), a microprocessing unit (MCU), a digital signal processor (DSP), other general-purpose processors, an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a complex programmable logic device (CPLD) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components and other components and circuits.

[0041] In some embodiments, the detection system 20 may further include a memory (not shown). The memory may be used to store images captured by the industrial camera 22, etc. The memory may be built into the industrial camera, or built into the industrial robot, or built into the controller 23, or be a cloud storage, etc.

[0042] In some embodiments, the memory may include random access memory (RAM) or non-volatile memory (NVM). Further, the memory may include at least one of phase-change random access memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), read-only memory (ROM), and electrically erasable programmable read only memory (EEPROM).

[0043] The detection system 20 of the present disclosure is introduced above. Figure 1 and Figure 2 The various steps of detection method 10 are introduced.

[0044] In some embodiments, in step S11, the controller 23 moves the industrial camera 22 to a detection position facing the calibration plate 21. For example, the industrial camera 22 is installed on an actuator of an industrial robot, and the actuator is, for example, a mechanical arm of the industrial robot. The controller 23 moves the industrial camera 22 to the detection position by controlling the actuator. Specifically, the actuator and the industrial camera have a preset relative position relationship. The controller 23 controls the movement of the actuator to drive the industrial camera to move, and controls the actuator to move to a preset position to move the industrial camera 22 to the detection position. At the detection position, the industrial camera 22 faces the calibration plate 21, and the calibration plate 21 is within the field of view of the industrial camera 22. The industrial camera 22 can theoretically capture a clear image of the calibration plate.

[0045] In some embodiments, in step S12 , the controller 23 controls the industrial camera 22 to capture an image of the calibration plate 21 .

[0046] In some embodiments, in step S13, the controller 23 further analyzes the acquired image to determine the parameters of the calibration pattern 211 in the acquired image. The parameters of the calibration pattern include one or more of the coordinates of the positioning point M in the image, the position of the grayscale detection area Ag in the image, the grayscale of the grayscale detection area Ag, and the acuteness of the grayscale detection area Ag.

[0047] Correspondingly, determining the parameters of the calibration pattern 211 in the captured image includes: determining the coordinates of the positioning point M in the calibration plate image, obtaining the position of the grayscale detection area Ag in the image, detecting the grayscale of the grayscale detection area Ag, and obtaining one or more of the sharpness of the grayscale detection area Ag.

[0048] For example, the controller 23 may identify the coordinates P1 of the positioning point M in the acquired calibration plate image through a visual recognition algorithm, and the specific recognition algorithm is not limited.

[0049] The positioning point M and the grayscale detection point N may have a preset positional relationship. The controller 23 may obtain or adjust the position P2 of the grayscale detection area Ag in the image according to the coordinates P1 of the positioning point M in the image, for example, obtain or adjust the coordinates of the grayscale detection point N in the image, and use the coordinates of the grayscale detection point N as the position P2 of the grayscale detection area Ag.

[0050] The controller 23 can detect the grayscale of the grayscale detection area Ag, for example, detect the grayscale of the grayscale detection point N, and use the grayscale of the grayscale detection point N as the grayscale of the grayscale detection area Ag. The controller 23 can detect the grayscale of one grayscale detection point N, or can detect the grayscale of multiple grayscale detection points N. If multiple grayscale detection points N are involved, the controller 23 can determine the average value of the multiple grayscale detection points N, and the average value can be used as the grayscale of the grayscale detection area Ag.

[0051] The controller 23 can detect the boundary B of the grayscale detection area Ag to obtain the sharpness of the grayscale detection area Ag. The specific implementation method of detecting the boundary is not limited. The controller 23 can detect the sharpness of one boundary or multiple boundaries. If multiple boundaries are involved, the controller 23 can determine the average value of the sharpness of the multiple boundaries, and the average value can be used as the sharpness of the grayscale detection area Ag.

[0052] In these ways, the controller 23 can determine one or more parameters of the calibration pattern 211 in the image.

[0053] In some embodiments, in step S14, the controller 23 detects the parameters of the industrial camera 22 according to the parameters of the calibration pattern 211 in the image, and detects whether the parameters of the industrial camera 22 are abnormal. The parameters of the industrial camera 22 include one or more of the working position, aperture, light source brightness, and focal length of the industrial camera 22. The controller 23 can detect whether one or more of the working position, aperture, light source brightness, and focal length of the industrial camera are abnormal according to one or more of the coordinates P1 of the positioning point M in the image, the position P2 of the grayscale detection area Ag in the image, the grayscale G of the grayscale detection area Ag, and the sharpness A of the grayscale detection area Ag.

[0054] Specifically, the controller 23 compares one or more parameters of the calibration pattern in the image with corresponding preset reference values; when the difference between the parameter and the preset reference value is greater than the corresponding threshold, it is determined that the parameter of the industrial camera is abnormal; when the difference between the parameter and the preset reference value is less than the corresponding threshold, it is determined that the parameter of the industrial camera is normal. For ease of understanding, the following example is given.

[0055] For example, the controller 23 detects whether the working position of the industrial camera is abnormal based on the coordinates of the positioning point M. Specifically, the controller 23 compares the coordinates P1 of the positioning point M in the image with the preset reference coordinates P0; when the difference ΔP between the coordinates P1 and the preset reference coordinates P0 is greater than the position threshold THP, it is determined that the working position of the industrial camera 22 is abnormal. On the contrary, when the difference ΔP between the coordinates P1 and the preset reference coordinates P0 is less than or equal to the position threshold THP, it is determined that the working position of the industrial camera 22 is normal.

[0056] For another example, the controller 23 determines whether the aperture and light source brightness of the industrial camera are abnormal based on the grayscale detection result of the grayscale detection area Ag. Specifically, the controller 23 compares the grayscale G1 of the grayscale detection point N in the image with the preset reference grayscale G0; when the difference ΔG between the grayscale G1 and the preset reference grayscale G0 is greater than the grayscale threshold THG, it is determined that the aperture and light source brightness of the industrial camera 22 are abnormal. On the contrary, when the difference ΔG between the grayscale G1 and the preset reference grayscale G0 is less than or equal to the grayscale threshold THG, it is determined that the aperture and light source brightness of the industrial camera 22 are normal.

[0057] For another example, the controller 23 determines whether the focus of the industrial camera is abnormal based on the detection result of the sharpness of the grayscale detection area Ag. Specifically, the controller 23 compares the sharpness A1 of the boundary B of the grayscale detection area Ag in the image with the preset reference sharpness A0; when the difference ΔA between the sharpness A1 and the preset reference sharpness A0 is greater than the sharpness threshold THA, it is determined that the focus of the industrial camera 22 is abnormal. On the contrary, when the difference ΔA between the detected sharpness A1 and the preset reference sharpness A0 is less than or equal to the sharpness threshold THA, it is determined that the focus of the industrial camera 22 is normal.

[0058] In the present disclosure, the parameters of the industrial camera 22 (working position, aperture, light source brightness and focal length) can be detected individually, or one or more of them can be detected simultaneously, all of which are within the protection scope of the present disclosure.

[0059] In some embodiments, the detection method 10 further includes: when it is determined that the parameters of the industrial camera are abnormal, correcting the parameters of the industrial camera.

[0060] For example, when it is determined that the working position of the industrial camera is abnormal, the controller 23 can drive the industrial camera 22 to move by controlling the movement of the actuator (such as a robotic arm). During the movement, the controller 23 can control the industrial camera 22 to capture the image of the calibration plate 21 once or multiple times. Each time the calibration plate image is captured, the coordinates P1 of the positioning point M in the calibration plate image are determined, and the coordinates P1 of the positioning point M in the image are compared with the preset reference coordinates P0 until the difference ΔP between the two is less than or equal to the position threshold THP. It is determined that the working position of the industrial camera 22 is normal, thereby correcting the working position of the industrial camera 22.

[0061] For another example, when it is determined that the aperture and light source brightness of the industrial camera are abnormal, the controller 23 can adjust at least one of the aperture and light source brightness. For example, when the detected grayscale G1 is greater than the preset reference grayscale G0, the controller 23 determines that the image is darker, and at least one of the aperture and light source brightness can be increased. Conversely, when the grayscale G1 is less than the preset reference grayscale G0, the controller 23 determines that the image is brighter, and at least one of the aperture and light source brightness can be reduced. During the adjustment process, the controller 23 can control the industrial camera 22 to capture the image of the calibration plate 21 once or more, and each time the calibration plate image is captured, the grayscale G1 of the grayscale detection area Ag is detected, and the grayscale G1 is compared with the preset reference grayscale G0 until the difference ΔG between the two is less than or equal to the grayscale threshold THG, and it is determined that the aperture and light source brightness of the industrial camera 22 are normal, so as to correct the aperture and light source brightness of the industrial camera 22.

[0062] The long service life of the light source will cause the brightness to decay. In some embodiments, the controller 23 can increase the current provided to the light source, thereby increasing the brightness value. For example, it can be adjusted according to a preset current-brightness curve to indirectly correct the aperture and light source brightness of the industrial camera 22. In other embodiments, the controller 23 can use the difference ΔG between the detected grayscale G1 and the preset reference grayscale G0 as the grayscale compensation amount to compensate for the image brightness, thereby indirectly correcting the aperture and light source brightness of the industrial camera 22. In some other embodiments, the controller 23 can also indirectly correct the aperture and light source brightness of the industrial camera 22 by adjusting the exposure time of the industrial camera 22. These are all within the scope of protection of the present disclosure.

[0063] For another example, when it is determined that the focal length of the industrial camera is abnormal, the controller 23 can adjust the focal length. For example, when the detected sharpness A1 is greater than the preset reference sharpness A0, the controller 23 determines that the image is severely sharpened and the focal length is small, and the focal length can be increased. Conversely, when the sharpness A1 is less than the preset reference sharpness A0, the controller 23 determines that the image is not sharp enough and the focal length is large, and the focal length can be reduced. During the adjustment process, the controller 23 can control the industrial camera 22 to capture the image of the calibration plate 21 once or more. Each time the calibration plate image is captured, the sharpness A1 of the grayscale detection area Ag is detected, and the sharpness A1 is compared with the preset reference sharpness A0 until the difference ΔA between the two is less than or equal to the sharpness threshold THA, and it is determined that the focal length of the industrial camera 22 is normal, so as to correct the focal length of the industrial camera 22.

[0064] In some embodiments, the detection method 10 further includes: determining a preset reference value of a parameter. Specifically, calibrating the parameters of the industrial camera; moving the industrial camera to the detection position; acquiring an image of the calibration plate through the industrial camera; and determining the parameters of the calibration pattern in the image as a preset reference value. For example, the controller 23 can calibrate one or more of the working position, aperture, light source brightness, and focal length of the industrial camera 22, control the actuator of the industrial robot, move the industrial camera 22 to the detection position, and control the industrial camera 22 to acquire an image of the calibration plate 21, and after one or more calibrations, until a clear image of the calibration plate is acquired. At this time, the controller 23 determines the coordinates of the positioning point M in the calibration plate image, determines the coordinates of the grayscale detection point N in the calibration plate image, determines the grayscale of the grayscale detection point N in the calibration plate image, and determines the sharpness of the boundary B in the calibration plate image. The coordinates of the positioning point M in the calibration plate image can be used as the preset reference coordinates P0, the coordinates of the grayscale detection point N in the calibration plate image can be used as the preset reference grayscale detection position, the grayscale of the grayscale detection point N in the calibration plate image can be used as the preset reference grayscale G0, and the sharpness of the boundary B in the calibration plate image can be used as the preset reference sharpness A0. In this way, the preset reference values ​​of the parameters of the calibration pattern in the image can be determined.

[0065] according to Figure 2 The calibration plate 21 shown in the figure, the controller 23 can detect one or more parameters of the working position, aperture, light source brightness and focal length of the industrial camera 22. It is understandable that the calibration plate and its calibration pattern can be determined according to the parameters of the industrial camera that need to be detected. For example, if the working position of the industrial camera needs to be detected, the calibration plate 21 may only need to retain the first area R1 and the calibration pattern thereon. If one or more parameters of the aperture, light source brightness and focal length need to be detected, the calibration plate 21 may retain the second area R2 and the calibration pattern thereon. In addition, Figure 2 The illustrated calibration pattern 211 is only shown for example and does not constitute a limitation to the present disclosure. In practical applications, a corresponding calibration pattern can be designed according to the parameters of the industrial camera to be detected.

[0066] Figure 3 Schematic diagrams of calibration plates 21 according to other embodiments of the present disclosure are shown. Figure 3 As shown, the calibration plate 21 includes a calibration pattern 211, which is roughly triangular and includes a positioning point M. The controller 23 collects an image of the calibration plate 21 through the industrial camera 22, and can determine the coordinates of the positioning point M in the calibration plate image. According to the coordinates of the positioning point M, the working position of the industrial camera 22 can be detected. It should be noted that Figure 3 The calibration pattern shown is only shown as an example, and the present disclosure is not limited thereto. The calibration pattern may also be other regular shapes such as a five-pointed star or irregular shapes, depending on the actual situation.

[0067] Figure 4 FIG. 2 shows a schematic diagram of a calibration plate 21 according to some other embodiments of the present disclosure. Figure 4 As shown, the calibration plate 21 includes a calibration pattern 211, which is roughly circular and includes a grayscale detection area Ag. The controller 23 collects an image of the calibration plate 21 through the industrial camera 22, and can determine the grayscale and / or sharpness of the grayscale detection area Ag. According to the grayscale of the grayscale detection area Ag, the controller 23 can detect the aperture and light source brightness of the industrial camera 22. According to the sharpness of the grayscale detection area Ag, the controller 23 can detect the focal length of the industrial camera 22. It should be noted that Figure 4 The calibration pattern shown is only shown as an example, and the present disclosure is not limited thereto. The calibration pattern may also be other regular shapes such as a five-pointed star or irregular shapes, depending on the actual situation.

[0068] The above has introduced the detection method and detection system of the present invention. The detection method and detection system of the present invention can realize the detection of industrial cameras without interrupting the production process. Specifically, it can detect whether one or more parameters of the working position, aperture, light source brightness and focal length are abnormal. In particular, without disassembling the hardware structure, the detection of lens-related hardware parameters can be realized, which improves the detection efficiency and the reliability of the detection results. When a parameter abnormality is detected, the corresponding parameters can be corrected in time, which improves the reliability of the industrial camera, helps the industrial camera to capture clear images with good contrast, and ensures image quality. When it is applied to automated equipment, it helps to more accurately guide the actuator to grab materials, assemble materials, and check the product status after the process is completed, thereby improving the reliability of the automated equipment.

[0069] The present disclosure also provides a computer-readable storage medium, including computer-executable instructions stored thereon, and when the executable instructions are executed by a processor, the detection method 10 as described above is implemented.

[0070] In some embodiments, the processor may include components or circuits such as processing circuits, CPUs, MCUs, DSPs, other general-purpose processors, ASICs, FPGAs, CPLDs or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0071] The present disclosure may take the form of a computer program product implemented on one or more storage media containing program code. Computer-usable storage media include permanent and non-permanent, removable and non-removable media, and information storage may be implemented by any method or technology. Information may be computer-readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to: PRAM, SRAM, DRAM, other types of RAM, ROM, EEPROM, flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device.

[0072] It should be noted that the present disclosure may only include Figure 1-4 In other words, not all of the features shown need to be implemented simultaneously in the detection method and detection system of the present disclosure.

[0073] It should be noted that this specification provides method operation steps such as embodiments or schematic diagrams, but more or fewer operation steps may be included based on conventional or non-creative labor. The order of steps listed in the embodiments is only one way of executing the order of many steps and does not represent the only execution order. When the actual system or device product is executed, it can be executed in the order of the method shown in the embodiment or flowchart or in parallel.

[0074] It should be noted that although several modules of the detection system are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules described above can be implemented in one module. Conversely, the features and functions of one module described above can be further divided into multiple modules to be embodied.

[0075] Finally, it should be noted that the above are only some embodiments of the present disclosure and are not intended to limit the present disclosure. Although the present disclosure is described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A detection method for an industrial camera, characterized in that: The detection method comprises: Moving the industrial camera to a detection position facing a calibration plate, wherein the calibration plate has a calibration pattern; Acquire the image of the calibration plate by the industrial camera; Determining a parameter of the calibration pattern in the image; The parameters are compared with corresponding preset reference values ​​to detect whether the parameters of the industrial camera are abnormal.

2. The detection method according to claim 1, characterized in that: The calibration pattern includes at least one of a positioning point or a grayscale detection area.

3. The detection method according to claim 2, characterized in that: The determining of the parameters of the calibration pattern in the image includes: obtaining the coordinates of the positioning point in the image, or the position of the grayscale detection area.

4. The detection method according to claim 3, characterized in that: The determining of the parameters of the calibration pattern in the image includes: adjusting the position of the grayscale detection area in the image according to the coordinates of the positioning point in the image.

5. The detection method according to claim 3, characterized in that: The step of detecting the parameters of the industrial camera includes: detecting whether the working position of the industrial camera is abnormal according to the coordinates of the positioning point in the image.

6. The detection method according to claim 2, characterized in that: The determining of the parameter of the calibration pattern in the image includes: detecting the grayscale of the grayscale detection area.

7. The detection method according to claim 6, characterized in that: The detecting of the parameters of the industrial camera includes: judging whether the aperture and the brightness of the light source are abnormal according to the grayscale detection result.

8. The detection method according to claim 2, characterized in that: The determining of the parameter of the calibration pattern in the image includes: detecting the boundary of the grayscale detection area to obtain the sharpness of the grayscale detection area.

9. The detection method according to claim 8, characterized in that: The detecting of the parameters of the industrial camera includes: judging whether the focal length is abnormal according to the sharpness detection result.

10. The detection method according to claim 1 or 2, characterized in that: Also includes: When the parameters of the industrial camera are abnormal, the parameters of the industrial camera are corrected.

11. The detection method according to claim 1 or 2, characterized in that: Further including: By controlling the actuator on which the industrial camera is installed, the industrial camera is moved to a detection position facing the calibration plate.

12. The detection method according to claim 11, characterized in that: The detection method further comprises: Calibrate parameters of the industrial camera; Moving the industrial camera to the detection position; Acquiring an image of the calibration plate by means of the industrial camera; and A parameter of the calibration pattern in the image is determined as the preset reference value.

13. A detection system, characterized in that: include: A calibration plate, wherein the calibration plate has at least one calibration pattern; Industrial cameras, installed on the actuators of industrial robots; and A controller communicates with the industrial camera and is configured to execute the detection method according to any one of claims 1 to 12.

14. A computer-readable storage medium, characterized in that: The invention comprises computer executable instructions stored thereon, and when the executable instructions are executed by a processor, the detection method according to any one of claims 1 to 12 is implemented.

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