Source: https://patents.google.com/patent/US8295552B2/en
Timestamp: 2018-06-21 11:22:47
Document Index: 390780278

Matched Legal Cases: ['Application No. 05763341', 'Application No. 05763341', 'Application No. 05763341', 'Application No. 2007', 'Application No. 2007', 'Application No. 05763341', 'Application No. 05763341', 'Application No. 05763341', 'Application No. 2007']

US8295552B2 - Method for setting parameters of a vision detector using production line information - Google Patents
Method for setting parameters of a vision detector using production line information Download PDF
US8295552B2
US8295552B2 US12432235 US43223509A US8295552B2 US 8295552 B2 US8295552 B2 US 8295552B2 US 12432235 US12432235 US 12432235 US 43223509 A US43223509 A US 43223509A US 8295552 B2 US8295552 B2 US 8295552B2
US12432235
US20090273668A1 (en )
Brian V. Mirtich
G03B7/097—Digital circuits for control of both exposure time and aperture
Disclosed are systems and methods for setting various operating parameters of a vision detector from production line information that can be supplied by a manufacturing technician who is not skilled in the art of the invention. These operating parameters include shutter time, video gain, idle time, frame count, and locator search range. The production line information includes line speed, field of view size, direction of motion, and object spacing.
This application claims the benefit of priority of U.S. patent application Ser. No. 10/979,535, filed Nov. 2, 2004, entitled “Method for Setting Parameters of a Vision Detector using Production Line Information” which is a continuation-in-part of co-pending patent application Ser. No. 10/865,155, entitled “Method and Apparatus for Visual Detection and Inspection of Objects”, By William M. Silver, filed Jun. 9, 2004, the teachings of which are expressly incorporated herein by reference, and referred to herein as the “Vision Detector Method and Apparatus”.
Machine vision systems have additional limitations arising from their use of a trigger signal. The need for a trigger signal makes the setup more complex—a photodetector must be mounted and adjusted, or software must be written for a PLC or computer to provide an appropriate message. When a photodetector is used, which is almost always the case when the objects are in continuous motion, a production line changeover may require it to be physically moved, which can offset some of the advantages of a vision system. Furthermore, photodetectors can only respond to a change in light intensity reflected from an object or transmitted along a path. In some cases, such a condition may not be sufficient to reliably detect when an object has entered the field of view.
The vision systems respond too slowly for self-triggering to work at common production speeds;
The methods provided to detect when an object is present are not sufficient in many cases; and
The vision systems do not provide useful output signals that are synchronized to a specific, repeatable position of the object along the production line, signals that are typically provided by the photodetector that acts as a trigger and needed by a PLC or handling mechanism to take action based on the vision system's decision.
Many of the limitations of machine vision systems arise in part because they operate too slowly to capture and analyze multiple perspectives of objects in motion, and too slowly to react to events happening in the field of view. Since most vision systems can capture a new image simultaneously with analysis of the current image, the maximum rate at which a vision system can operate is determined by the larger of the capture time and the analysis time. Overall, one of the most significant factors in determining this rate is the number of pixels comprising the imager.
When performing object detection, a test is made for each frame to decide whether the evidence is sufficient that an object is located in the field of view. If a simple yes/no value is used, the evidence may be considered sufficient if the value is “yes”. If a number is used, sufficiency may be determined by comparing the number to a threshold. Frames where the evidence is sufficient are called active frames. Note that what constitutes sufficient evidence is ultimately defined by a human user who configures the vision detector based on an understanding of the specific application at hand. The vision detector automatically applies that definition in making its decisions.
The method of dynamic image analysis involves capturing and analyzing multiple frames to inspect an object, where “inspect” means to determine some information about the status of the object. In one example of this method, the status of an object includes whether or not the object satisfies inspection criteria chosen as appropriate by a user.
the shutter time and video gain of the imager;
frame count parameters used to control the number of frames to be analyzed for visual event detection and dynamic image analysis;
idle time parameters use to avoid misdetection of objects and for other purposes; and
search range parameters used to help track objects as they move through the field of view.
The Vision Detector Method and Apparatus provides explanations of these parameters, as well as useful default values for illustrative embodiments, that in conjunction with general knowledge in the art guide a person of ordinary skill in setting them as appropriate for the conditions of his application. Note that doing so is at least in part a matter of human judgment—there is no formula or set of formulas that gives optimal results in all situations, partly because most situations cannot be foreseen and partly because setting the parameters involves engineering tradeoffs where there is no clear optimal solution.
In one aspect the invention provides methods and systems to set a shutter time parameter and a gain parameter of an imager that is configured to capture images of a field of view of a production line. The production line moves relative to the field of view at a nominal line speed, and the size of the field of view in the direction of motion is known. The line speed and size information can be provided by a manufacturing technician.
The desired shutter time is approximately equal to the motion shutter time. This means that a value for the desired video gain can be found within its allowable range that provides the highest fidelity while avoiding excessive blurring;
The desired shutter time is less than the motion shutter time and the desired gain is approximately equal to the minimum allowable gain value. This means that there is so much light that the shutter time has to be shorter to achieve suitable brightness; and
The desired shutter time is greater than the motion shutter time and the desired gain is approximately equal to the maximum allowable gain value. This means that there is so little light that longer shutter times are needed, and the increased blurring will have to be tolerated.
Once the desired shutter time and video gain are computed, the corresponding imager parameters are set to those values.
Using the nominal object speed, the apparent object speed is estimated. Apparent and nominal object speed are equivalent to apparent and nominal line speed as discussed above—as the present invention uses these values, it does not matter whether what is moving through the field of view is described as a production line, an object, or any other entity. Using the apparent object speed estimate and the motion parameter, the desired idle time is computed and the idle time parameter is set. In this illustrative embodiment, the desired idle time is simply the ratio of the motion parameter to the apparent object speed. Note that the actual object speed at any given time may differ from the nominal object speed, which may increase the risk of multiple detection or misdetection.
Basic Operation of the Vision Detector Method and Apparatus
FIG. 2 shows a timeline that illustrates a typical operating cycle for a vision detector in visual event detection mode. Boxes labeled “c”, such as box 520, represent image capture. Boxes labeled “a”, such as box 530, represent image analysis. It is desirable that capture “c” of the next image be overlapped with analysis “a” of the current image, so that (for example) analysis step 530 analyzes the image captured in capture step 520. In this timeline, analysis is shown as taking less time than capture, but in general analysis will be shorter or longer than capture depending on the application details.
If capture and analysis are overlapped, the rate at which a vision detector can capture and analyze images is determined by the longer of the capture time and the analysis time. This is the “frame rate”.
b fraction of the FOV occupied by the portion of the object that contains the visible features to be inspected, determined by choosing the optical magnification of the lens 950 so as to achieve good use of the available resolution of imager 960;
m ≤ 1 - b - e n ⁢ ⁢ and ( 1 ) r ≥ sp m ( 2 )
To achieve good use of the available resolution of the imager, it is desirable that b is at least 50%. For dynamic image analysis, n should be at least 2. Therefore it is further desirable that the object moves no more than about one-quarter of the field of view between successive frames.
f = min ⁡ ( max ⁡ ( x - t 0 t 1 - t 0 , 0 ) , 1 ) ( 3 )
Note that this function works just as well when t1<t0. Other functions can also be used for a fuzzy threshold, such as the sigmoid
f = 1 1 + ⅇ - ( x - t ) / σ ( 4 )
where t and σ are threshold parameters. In embodiments where simplicity is a goal, a conventional binary threshold can be used, resulting in binary logic values.
Fuzzy decision making is based on fuzzy versions of AND 1140, OR 1150, and NOT 1160. A fuzzy AND of two or more fuzzy logic values is the minimum value, and a fuzzy OR is the maximum value. Fuzzy NOT off is 1−f Fuzzy logic is identical to binary when the fuzzy logic values are restricted to 0 and 1.
1. Is an object, or a set of visible features of an object, located in the field of view?
2. If so, what is the status of the object?
Information comprising evidence that an object is located in the field of view is called an object detection weight. Information comprising evidence regarding the status of an object is called an object pass score. In various illustrative embodiments, the status of the object comprises whether or not the object satisfies inspection criteria chosen as appropriate by a user. In the following, an object that satisfies the inspection criteria is sometimes said to “pass inspection”.
In the illustrative embodiment of FIG. 7, frames where di≧0.5 are considered active (refer to the above description of FIG. 2 for an explanation of active frames). For reference, a line 1230 where di=0.5 is plotted. Object detection weights and pass scores for active frames are plotted as solid circles, for example points 1210 and 1212, and those for inactive frames are plotted as open circles, for example points 1214 and 1216. In some embodiments, the object pass weights are only computed for active frames; while in the embodiment of FIG. 7, they are computed for all frames, whether or not deemed “active”.
∑ i ⁢ ⁢ d i ⁢ p i ∑ i ⁢ ⁢ d i ≥ 0.5 ( 5 )
where the summation is over all active frames. The effect of this formula is to average the object pass scores, but to weight each score based on the confidence that the object really did appear in the corresponding frame.
Q ⁡ ( p ) = ∑ k ❘ p k ≥ p ⁢ ⁢ d k ∑ i ⁢ ⁢ d i ( 6 )
The object is judged to pass if Q(p) is at least some threshold t. In the illustrative embodiment of FIG. 8, p=0.5, which is plotted as line 1320. A reasonable threshold t for this case would be 10%.
1. has a name that can be chosen by the user;
2. has a logic output (a fuzzy logic value) that can be used as a logic input by other gadgets to make judgments and control output signals;
3. has a set of parameters than can be configured by a user to specify its operation;
4. has one such parameter that can be used to invert the logic output (i.e. fuzzy NOT); and
5. can be run, which causes its logic output to be updated based on its parameters, logic inputs if any, and for certain Gadgets the contents of the current frame, and which may also cause side-effects such as the setting of an output signal.
The act of analyzing a frame consists of running each Gadget once, in an order determined to guarantee that all logic inputs to a Gadget have been updated before the Gadget is run. In some embodiments, a Gadget is not run during a frame where its logic output is not needed.
The logic output of the ObjectDetect Judge provides a pulse that indicates when a judgment has been made. In one mode of operation, called “output when processing”, the leading edge of the pulse occurs when the inspection of an object begins, for example at the end of analysis step 540 in FIG. 2, and the trailing edge occurs when the inspection of an object is complete, for example at the end of analysis step 548. In another mode, called “output when done”, the leading edge of the pulse occurs when the inspection of an object is complete, for example at the end of analysis step 548 in FIG. 2, and the trailing edge occurs some time after that, for example at the end of idle step 580.
Referring still to the wiring diagram of FIG. 11, a Locator 1620 named “Top”, corresponding to Locator 1520 in the image view of FIG. 10, is connected to AND Gate 1610 by wire 1624. Similarly, “Side” Locator 1622, corresponding to Locator 1522, and “Box” Detector 1630, corresponding to Brightness Detector 1530, are also wired to AND Gate 1610. The logic output of “Box” detector 1630 is inverted, as shown by the small circle 1632 and as described above to detect the darker object against a lighter background.
In the wiring diagram, Contrast Detector “Hole” 1640, corresponding to Contrast Detector 1540, Brightness Detector “Label” 1650, corresponding to Brightness Detector 1550, and Edge Detector “LabelEdge” 1660, corresponding to Edge Detector 1560, are wired to AND Gate 1612. The logic output of AND Gate 1612 represents the level of confidence that all three image features have been detected, and is wired to ObjectPass Judge 1602 to provide the object pass score for each frame.
The logic output of ObjectDetect Judge 1600 is wired to AND Gate 1670. The logic output of ObjectPass Judge 1602 is inverted and also wired to AND Gate 1670. The ObjectDetect Judge is set to “output when done” mode, so a pulse appears on the logic output of ObjectDetect Judge 1600 after an object has been detected and inspection is complete. Since the logic output of ObjectPass 1602 has been inverted, this pulse will appear on the logic output of AND Gate 1670 only if the object has not passed inspection. The logic output of AND Gate 1670 is wired to an Output gadget 1680, named “Reject”, which controls an output signal from the vision detector than can be connected directly to a reject actuator 170. The Output Gadget 1680 is configured by a user to perform the appropriate delay 570 needed by the downstream reject actuator.
A logic view shows “Right” Brightness Detector 4440 corresponding to right Brightness Detector ROI 4432, and “Left” Brightness Detector 4442 corresponding to left Brightness Detector ROI 4430. “Right” Brightness Detector 4440 produces a true logic output when object 4400 is not covering right Brightness Detector ROI 4432, because the background in this example is brighter than object 4400. “Left” Brightness Detector 4442 produces a true logic output when object 4400 is covering left Brightness Detector ROI 4430, because its output is inverted. Therefore AND Gate 4460 produces a true logic output when the right edge of object 4400 is between left Brightness Detector ROI 4430 and right Brightness Detector ROI 4432.
AND Gate 4460 is wired to the ObjectDetect Judge, and “Hole” Contrast Detector 4470, corresponding to Contrast Detector ROI 4420, is wired to the ObjectPass Judge. The Judges in this example are configured for visual event detection and direct control of a reject actuator.
Pixel size information is provided by pixel size controls 5630. Direction controls 5632 allow the user to specify the direction of motion, from which the size in pixels of the field of view in the direction of motion can be determined. In an embodiment using the LM9630 imager, for example, the FOV is 128 pixels when the direction of motion is horizontal, and 100 pixels when it is vertical. FOV size spinner 5634 allows the user to estimate the size in physical units, for example inches or centimeters, of the field of view in the direction of motion. From these values the pixel size in physical units can be inferred. Note that precise values are not needed to practice the invention—the FOV size can be estimated by eye, by placing a ruler in the FOV, or by other well-known methods. The pixel size controls 5630 of FIG. 15 are intended to be illustrative only—it will be obvious that many alternate methods and structures can be used to obtain equivalent information.
In the first brightness zone 5620, the desired shutter time is less than the motion shutter time and the desired gain is approximately equal to the minimum allowable gain value. This means that there is so much light that the shutter time has to be shorter than the motion shutter time to achieve suitable brightness.
In the second brightness zone 5622, the desired shutter time is approximately equal to the motion shutter time. This means that a value for the desired video gain can be found within its allowable range that provides the highest fidelity while avoiding excessive blurring.
In the third brightness zone 5624, the desired shutter time is greater than the motion shutter time and the desired gain is approximately equal to the maximum allowable gain value. This means that there is so little light that longer shutter times are needed, and the increased blurring will have to be tolerated.
FIG. 16 will be used to describe the details of an illustrative embodiment wherein a variety of vision detector parameters are determined from production line information. Input values 5700 are provided by a user interacting with an HMI as illustrated in FIG. 15 and described above. Internal parameters 5702 are built into the vision detector based on engineering choices made by a designer of ordinary skill in the art, following the teachings of the invention. Any of these internal parameters could also be entered using HMI 830. Other internal parameters used by the illustrative embodiment but not shown in FIG. 16 will also be described. Intermediate values 5704 are produced and used at various points, and vision detector parameters 5706 are computed and set.
In the illustrative embodiment, imager 960 is an LM9630 with field of view 128×100 pixels. The shutter time parameter can be set in the range 10-20,480 μs. The video gain parameter is set to one of 32 steps by an integer g in the range 0-31:
video gain=1.1136g
Shutter motion parameter 5720 specifies that the production line should move no more than 0.33 pixels relative to the FOV during the shutter time to avoid excessive blurring. Apparent line speed value 5750 is estimated based on the nominal line speed:
apparent line speed value 5750 (853.3 pixels/sec)=line speed input 5710 (20 in/sec)×(128 pixels/FOV)/FOV size input 5712 (3 in/FOV).
line speed (20 in/sec)=object spacing input 5716 (10 in)×object frequency (2 Hz)
brightness shutter time value 5754 (634 μs)=(100 μs)×40.18brightness parameter input 5714 (0.5)
minimum idle time 5780 (75 ms)=minimum idle motion parameter 5730 (0.5 FOV)×FOV size input 5712 (3 in/FOV)/line speed input 5710 (20 in/sec)
maximum idle time 5782 (300 ms)=maximum idle motion parameter 5732 (2.0 FOV)×FOV size input 5712 (3 in/FOV)/line speed input 5710 (20 in/sec)
minimum idle time 5780 (75 ms)=minimum idle period parameter 5734 (0.15)×object period value 5756 (500 ms)
maximum idle time 5782 (300 ms)=maximum idle period parameter 5736 (0.60)×object period value 5756 (500 ms)
expected frame count value 5764 (8 frames)=floor[detection range length value 5766 (15 pixels)/frame motion value 5762 (1.77 pixels/frame)]
minimum frame count parameter 5792 (4 frames)=floor[0.5×expected frame count value 5764 (8 frames)]
maximum frame count parameter 5794 (12 frames)=ceiling[1.5×expected frame count value 5764 (8 frames)]
trigger frame count parameter 5796 (6 frames)=round[0.8×expected frame count value 5764 (8 frames)]
At least half (0.5) of the expected number of frames must be found to contain sufficient evidence that an object is present in the FOV in order to judge that an object has been detected.
Dynamic image analysis may be terminated and a decision made when 1.5 times the number of expected frames have been analyzed.
When using an external trigger, analyze slightly less than (0.8) the number of expected frames, to avoid analyzing frames where the object may have moved beyond the detection range.
Note that if all pixel size and production line information were known perfectly, and if object appearance were always reliable in all viewing perspectives within the detection range, then all of these parameters could be set to 1.0 so that all of the frames count parameters would be equal to the expected number of frames. The actual values used above reflect the fact that in practice production conditions and pixel size are only estimated and may differ from nominal values, and object appearance may not be reliable at all viewing perspectives within the detection range. Clearly other values for these constants may be desirable for specific applications. Note further that these comments apply equally to many parameter choosing tasks, such as the idle period and idle motion internal parameters.
1. A method for setting an idle time parameter of a vision detector comprising
configuring the vision detector to detect a sequence of discrete objects in continuous motion at a nominal object speed relative to a field of view of the vision detector, including detecting each object of the sequence of discrete objects responsive to an analysis of at least one frame captured by the vision detector, each frame comprising an image of the field of view;
choosing a motion parameter that specifies a desired motion of an object, in units related to pixels, during an idle step of the vision detector, the idle step comprising an interval of time during which objects are not detected;
estimating, responsive to the nominal object speed, an apparent object speed in units related to pixels per unit of time;
computing, responsive to the apparent object speed and the motion parameter, a desired idle time; and
setting the idle time parameter of the vision detector to the desired idle time.
2. The method of claim 1, wherein the step of choosing the motion parameter includes choosing the motion parameter so as to avoid detecting an object more than once, and so as to avoid missing an object.
3. The method of claim 1, wherein the idle time parameter comprises a minimum idle time parameter.
4. The method of claim 1, wherein the idle time parameter comprises a maximum idle time parameter.
5. The method of claim 1, wherein the step of computing the desired idle time comprises computing a ratio of the motion parameter to the apparent line speed.
6. A method for setting an idle time parameter of a vision detector comprising:
configuring the vision detector to detect a sequence of discrete objects in continuous motion relative to a field of view of the vision detector, the sequence of discrete objects having a nominal object period between successive objects, wherein configuring the vision detector includes detecting each object of the sequence of discrete objects responsive to an analysis of at least one frame captured by the vision detector, each frame comprising an image of the field of view;
choosing a motion parameter that specifies a desired motion of an object in the sequence of discrete objects, as a fraction of the nominal object period, during an idle step of the vision detector, the idle step comprising an interval of time during which objects are not detected;
computing, responsive to the nominal object period and the motion parameter, a desired idle time; and
7. The method of claim 6, wherein the step of choosing the motion parameter includes choosing the motion parameter so as to avoid detecting an object more than once, and so as to avoid missing an object.
8. The method of claim 6, wherein the idle time parameter comprises a minimum idle time parameter.
9. The method of claim 6, wherein the idle time parameter comprises a maximum idle time parameter.
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US10979535 US7545949B2 (en) 2004-06-09 2004-11-02 Method for setting parameters of a vision detector using production line information
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