WO2024075510A1

WO2024075510A1 - Image processing method and image processing device

Info

Publication number: WO2024075510A1
Application number: PCT/JP2023/033903
Authority: WO
Inventors: 千奈澤田
Original assignee: 株式会社Ｓｃｒｅｅｎホールディングス
Priority date: 2022-10-03
Filing date: 2023-09-19
Publication date: 2024-04-11
Also published as: JP2024053178A

Abstract

This image processing method is for detecting a position of a detection target from a captured image acquired periodically, wherein the following steps are repeated multiple times: a) a step (S103) for analyzing a region to be analyzed in the captured image, and deriving a detection error and the position of the detection target; and b) steps (S104 to S107) for changing the region to be analyzed on the basis of the magnitude of the detection error. Due to this configuration, the region to be analyzed can be shrunk while keeping the detection error within a prescribed range. Consequently, it is possible to reduce the amount of computation without increasing the detection error in image processing for detecting a specific object from time-series image data.

Description

Image processing method and image processing device

The present invention relates to technology for analyzing captured images that are periodically input from outside.

In various industrial equipment, including printing devices and laser drawing devices, the position of a specific object, such as an alignment mark, may be detected from captured image data, and the position of the device may be controlled based on the detection results.

In such a device, if image processing is performed on the entire range of a captured image to detect the position every time a captured image is input, the amount of calculations increases and it is inefficient. A method for reducing the amount of calculations to address this problem is described, for example, in Patent Document 1.

In Patent Document 1, the image is converted to a low resolution and the low resolution data is analyzed to determine whether an object is present. Then, only if it is determined that an object is present is the original high resolution image used to perform calculations again, thereby reducing the amount of calculations.

JP 2020-52647 A

The method of Patent Document 1 is effective when there are times when the object to be detected is not present in the captured image. However, when detecting the position of an alignment mark, the object to be detected is always within the shooting range, and its positional changes are tracked. For such purposes, even if the method of Patent Document 1 is used, the amount of calculations cannot be reduced.

The present invention has been developed in consideration of these circumstances, and aims to provide a technology that reduces the amount of calculations required in image processing to detect specific objects from time-series image data.

In order to solve the above problem, the first invention of the present application is an image processing method for detecting the position of a detection target from a periodically acquired photographed image, the method including the steps of: a) analyzing an analysis target area of the photographed image to obtain the position of the detection target and a detection error; and b) changing the analysis target area based on the magnitude of the detection error, and repeating steps a) and b) multiple times.

The second invention of the present application is the image processing method of the first invention, in which in step b), the analysis target area is reduced if the detection error is smaller than a predetermined first threshold value.

The third invention of the present application is the image processing method of the second invention, in which in step b), when the analysis target area is reduced, the size is set to at least a predetermined minimum range.

The fourth invention of the present application is the image processing method of the second or third invention, in which in step b), the analysis target area is enlarged if the detection error is greater than a predetermined second threshold value.

The fifth invention of the present application is an image processing method according to any one of the first to fourth inventions, further comprising a step c) of enlarging the analysis target area if the displacement of the detection target is greater than a reference value after steps a) and b).

The sixth invention of the present application is an image processing device that detects the position of a detection target from a photographed image that is periodically acquired, and includes an analysis region extraction unit that extracts an analysis target region of the photographed image input from outside and generates an image for analysis, a mark position analysis unit that analyzes the image for analysis and determines the position of the detection target and the detection error, and an analysis region determination unit that changes the analysis target region based on the detection error.

According to the first to sixth aspects of the present application, it is possible to reduce the area to be analyzed while keeping the detection error within a predetermined range. Therefore, it is possible to reduce the amount of calculations while suppressing a decrease in detection accuracy.

In particular, according to the second aspect of the present application, it is possible to reduce the amount of calculations while suppressing a decrease in detection accuracy.

In particular, according to the fourth aspect of the present invention, when the detection error increases, the area to be analyzed is expanded to reduce the detection error, thereby making it possible to keep the detection error within a predetermined range.

FIG. 1 is a perspective view of a drawing device equipped with an image processing device. 2 is a block diagram showing electrical connections between a control unit and each unit in the drawing apparatus. FIG. FIG. 2 is a control block diagram of a position detection unit serving as an image processing device. 10 is a flowchart showing a flow of image processing in a position detection unit. FIG. 13 is an image diagram showing the relationship between a captured image and an area to be analyzed. FIG. 13 is an image diagram showing the relationship between a captured image and an area to be analyzed. FIG. 13 is an image diagram showing the relationship between a captured image and an area to be analyzed. FIG. 13 is an image diagram showing the relationship between a captured image and an area to be analyzed.

Below, an embodiment of the present invention will be described with reference to the drawings.

1. Configuration of the rendering device
A drawing device 1 including a position detection unit 90, which is an image processing device according to an embodiment of the present invention, will be described below with reference to Figures 1 and 2. Figure 1 is a perspective view of the drawing device 1. Figure 2 is a block diagram showing electrical connections between a control unit 10 including a position detection unit 90 and each unit in the drawing device.

This drawing device 1 is a device that irradiates the upper surface of a substrate W, such as a semiconductor substrate or a glass substrate coated with a photosensitive material, with spatially modulated light to draw an exposure pattern on the upper surface of the substrate W. As shown in Figures 1 and 2, the drawing device 1 includes a transport mechanism 20, a frame 30, a drawing processing unit 40, a camera 50, and a control unit 10.

The transport mechanism 20 is a device that transports the flat stage 22 in a horizontal direction in a substantially constant posture on the upper surface of the base 21. The transport mechanism 20 has a main scanning mechanism 23, a sub-scanning mechanism 24, and a rotation mechanism 25 (see FIG. 2). The main scanning mechanism 23 is a mechanism for transporting the stage 22 in the main scanning direction, which is one horizontal direction. The sub-scanning mechanism 24 is a mechanism for transporting the stage 22 in the sub-scanning direction, which is one of the horizontal directions and perpendicular to the main scanning direction. The substrate W is held in a horizontal posture on the upper surface of the stage 22, and moves together with the stage 22 in the main scanning direction and the sub-scanning direction. The rotation mechanism 25 can adjust the angle of the stage 22 around the vertical axis relative to the base 21.

The frame 30 is a structure for holding the drawing processing unit 40 above the base 21. The frame 30 has a pair of support pillars 31 and a bridge portion 32. The pair of support pillars 31 are erected with a gap between them in the sub-scanning direction. Each support pillar 31 extends upward from the upper surface of the base 21. The bridge portion 32 extends in the sub-scanning direction between the upper ends of the two support pillars 31. The stage 22 holding the substrate W passes between the pair of support pillars 31 and below the bridge portion 32.

The drawing processing unit 40 has two optical heads 41. The two optical heads 41 are fixed to the bridge unit 32 with a gap between them in the sub-scanning direction. The drawing processing unit 40 also has an illumination optical system and a laser oscillator (not shown), and a laser driver 42 (see FIG. 2). The illumination optical system, the laser oscillator, and the laser driver 42 are housed, for example, in the internal space of the bridge unit 32. The laser driver 42 is electrically connected to the laser oscillator. When the laser driver 42 is operated, a pulsed light is emitted from the laser oscillator. The pulsed light emitted from the laser oscillator is then introduced into the optical head 41 via the illumination optical system.

An optical system including a spatial modulator is provided inside the optical head 41. The pulsed light introduced into the optical head 41 is modulated by the spatial modulator into a predetermined pattern and irradiated onto the top surface of the substrate W. This exposes a photosensitive material such as a resist applied to the top surface of the substrate W.

Camera 50 (see FIG. 2) is not shown in FIG. 1. Camera 50 is attached, for example, to the underside of bridge portion 32 of frame 30. Camera 50 captures an image of the top surface of substrate W placed on stage 22, and inputs the resulting captured image Di to control unit 10. Control unit 10 detects the position of alignment mark M provided on the top surface of substrate W from image Di captured by camera 50. This allows control unit 10 to detect the position and attitude of substrate W.

The control unit 10 is a means for controlling the operation of each part of the drawing device 1. As conceptually shown in FIG. 1, the control unit 10 is composed of a computer having a processor 101 such as a CPU, a memory 102 such as a RAM, and a storage unit 103 such as a hard disk drive. A computer program P for controlling the operation of the drawing device 1 is stored in the storage unit 103.

As shown in FIG. 2, the control unit 10 is electrically connected to the drawing processing unit 40 (including the optical head 41 and the laser driving unit 42), the main scanning mechanism 23, the sub-scanning mechanism 24, the rotation mechanism 25, and the camera 50. The control unit 10 reads out the computer program P and data D stored in the storage unit 103 into the memory 102, and the processor 101 performs arithmetic processing based on the computer program P and the data D, thereby controlling the operation of each of the above-mentioned units in the drawing device 1. This allows the drawing process in the drawing device 1 to proceed.

The control unit 10 has a position detection unit 90, a transport control unit 91, and a drawing control unit 92. The functions of the position detection unit 90, the transport control unit 91, and the drawing control unit 92 are realized by the processor 101 of the computer that constitutes the control unit 10 operating in accordance with a computer program P.

The position detection unit 90 periodically receives captured images Di from the camera 50. The position detection unit 90 analyzes the captured images Di and detects the position, size, angle, etc. of the alignment mark M to detect the position and posture of the substrate W. The position detection unit 90 passes the detection result Do, which is information obtained by the analysis, to the transport control unit 91.

The transport control unit 91 controls each part of the transport device 20. In order to transport the substrate W in a predetermined manner, the transport control unit 91 transports the substrate W while correcting the position of the substrate W based on the detection result Do input from the position detection unit 90.

The drawing control unit 92 controls each part of the drawing processing unit 40. When the drawing device 1 is in operation, the operation of the transport mechanism 20 by the transport control unit 91 and the operation of the drawing processing unit 40 by the drawing control unit 92 are performed in conjunction with each other. Specifically, exposure by the optical head 41 and transport of the substrate W by the transport device 20 are repeatedly performed. More specifically, exposure is performed on a strip-shaped area (swath) extending in the sub-scanning direction by irradiating pulsed light from the optical head 41 while the sub-scanning mechanism 24 transports the stage 22 in the sub-scanning direction. Thereafter, the main scanning mechanism 23 transports the stage 22 by one swath in the main scanning direction. The drawing device 1 draws a pattern on the entire top surface of the substrate W by repeating such exposure in the sub-scanning direction and transport of the stage 22 in the main scanning direction.

While such a drawing process is being performed, the position detection unit 90 analyzes the position, size, angle, etc. of the alignment mark M based on the captured image Di input from the camera 50, and inputs the detection result Do (see FIG. 3) to the transport control unit 91. This enables the transport control unit 91 to check whether the position of the substrate W has deviated from the desired position, and corrects the position of the substrate W if a deviation occurs. This allows a pattern to be drawn with high precision on the top surface of the substrate W.

2. Configuration of image processing device
Next, a position detection unit 90 as an image processing device according to an embodiment of the present invention will be described with reference to Fig. 3. As described above, the position detection unit 90 is an image processing device realized by the control unit 10, and detects the position of the alignment mark M, which is the detection target, from the captured image Di periodically captured by the camera 50. As shown in Fig. 3, the position detection unit 90 has an analysis area extraction unit 81, a mark position analysis unit 82, and an analysis area determination unit 83.

The analysis area extraction unit 81 extracts an area to be analyzed from the captured image Di input from outside the position detection unit 90, and generates an image for analysis D1. Specifically, the analysis area extraction unit 81 cuts out a part of the image from the captured image Di captured by the camera 50 based on area information D3 input from the analysis area determination unit 83, and generates an image for analysis D1. Then, the analysis image D1 and area information D3, which is position information of the image for analysis D1, are passed to the mark position analysis unit 82.

The mark position analysis unit 82 analyzes the analysis image D1 and obtains a detection result Do, including the position, size, and angle of the alignment mark M, and a detection error D2. The mark position analysis unit 82 then passes the detection result Do to the transport control unit 91, and passes the detection result Do and the detection error D2 to the analysis area determination unit 83.

The mark position analysis unit 82 performs inference using a convolution operation on the entire area of the analysis image D1 to detect the position of the alignment mark M. At this time, an estimated error indicating the likelihood of the result is obtained at the same time as the position detection. The mark position analysis unit 82 sets this estimated error as the detection error D2. Since the amount of calculation increases or decreases depending on the size of the analysis image D1, the smaller the size of the analysis image D1, the less the amount of calculation and the faster the calculation can be performed.

The analysis area determination unit 83 changes the area to be analyzed based on the detection result Do and the detection error D2, and passes area information D3, which is coordinate information of the area to be analyzed, to the analysis area extraction unit 81. Specifically, the analysis area determination unit 83 determines the size and position of the area to be analyzed based on the detection result Do and the detection error D2. Then, the analysis area determination unit 83 passes area information D3, which includes the size and position of the area to be analyzed, to the analysis area extraction unit 81.

Specifically, the analysis area determination unit 83 of this embodiment reduces the analysis target area when the detection error D2 is smaller than a predetermined first threshold. Note that even when the detection error D2 is smaller than the first threshold, i.e., when the analysis target area is reduced, the analysis area determination unit 83 sets the analysis target area to a size equal to or larger than a predetermined minimum range.

In addition, the analysis area determination unit 83 of this embodiment enlarges the analysis target area when the detection error D2 is equal to or greater than a predetermined second threshold. In addition, the analysis area determination unit 83 does not change the size of the analysis target area when the detection error D2 is equal to or greater than the first threshold and less than the second threshold.

In addition, after changing the size of the analysis target area due to the detection error D2, the analysis target area determination unit 83 may enlarge the analysis target area based on the displacement amount of the alignment mark M. In this embodiment, the analysis target area determination unit 83 enlarges the analysis target area when the displacement amount of the alignment mark M is greater than a predetermined reference value.

The analysis area determination unit 83 changes the position of the analysis target area according to the displacement of the position of the alignment mark M in the detection result Do. For example, the analysis area determination unit 83 changes the position of the analysis target area so that the center position of the analysis target area is as close as possible to the center position of the nearest alignment mark M.

<3. Image processing flow>
Next, the flow of image processing in the position detection unit 90 will be described with reference to Figures 4 to 6. Figure 4 is a flowchart showing the flow of image processing in the position detection unit 90. Figures 5 to 8 are conceptual diagrams showing the relationship between the captured image Di and the area to be analyzed. Below, the flow of image processing will be described with reference to the examples of Figures 5 to 8.

In the examples of Figures 5 to 8, the captured image Di is square-shaped and has the same number of vertical pixels as the same number of horizontal pixels, but the present invention is not limited to this. The captured image Di may also be rectangular with a different number of vertical pixels than the horizontal pixels. Also, in the examples of Figures 5 to 8, the alignment mark M is cross-shaped, and the intersection point is referred to as the center position. Note that the alignment mark M may be any other shape. Also, the center position of the alignment mark M may be, for example, the center of the two-dimensional coordinate range of the rectangle in which the alignment mark M exists, or it may be the center of gravity.

The image processing shown in FIG. 4 is started at the same time as the transfer of the substrate W begins in the drawing device 1. In the image processing, first, the position detection unit 90 acquires the first captured image Di. Specifically, regular image capture by the camera 50 is started, and the first captured image Di is input to the position detection unit 90 (step S101).

The analysis area extraction unit 81 extracts the area to be analyzed from the input photographed image Di and generates an image for analysis D1 (step S102). Note that in the first step S102, the area to be analyzed is not set, so the area information D3 at the start of image processing is set to the entire range of the photographed image Di. Therefore, the analysis area extraction unit 81 uses the photographed image Di as it is as the image for analysis D1.

Next, the mark position analysis unit 82 analyzes the analysis image D1 and detects the position, angle, size, etc. of the alignment mark M (step S103). At this time, the mark position analysis unit 82 also calculates a detection error D2, which is an estimated error. The mark position analysis unit 82 passes the detection result Do, which includes the position, angle, and size of the alignment mark M, and the detection error D2 to the analysis area determination unit 83.

Then, the analysis area determination unit 83 compares the value of the detection error D2 with a predetermined first threshold and a second threshold (step S104). Then, the analysis area determination unit 83 changes the size of the analysis target area according to the magnitude of the value of the detection error D2 (steps S105 to S111). Note that the second threshold has a value larger than the first threshold.

If it is determined in step S104 that the detection error D2 is smaller than the first threshold value (step S104: less than first threshold value), the analysis region determination unit 83 reduces the size of the analysis region (step S105). Specifically, for example, the size of the analysis region is reduced by p pixels in both the vertical and horizontal directions. In other words, if the size of the analysis region at that time is m pixels x n pixels, it is reduced to (m-p) pixels x (n-p) pixels.

The analysis area determination unit 83 also changes the position of the analysis area so that the center position of the area to be analyzed coincides as closely as possible with the center position of the alignment mark M.

In this way, the analysis area determination unit 83 reduces the area to be analyzed when the detection error D2 is relatively small. This makes it possible to reduce the amount of calculations in the next image analysis process (step S103) while suppressing a decrease in detection accuracy.

Following step S105, the analysis area determination unit 83 determines whether the size after reduction is equal to or larger than a predetermined minimum area size (step S106). The minimum area size may be a predetermined fixed value, or may vary based on the detection result Do. For example, the minimum area size may vary based on the size of the alignment mark M in the detection result Do. In that case, for example, if the size of the alignment mark M is approximately x pixels square, the size of the area to be analyzed may be (x+q) pixels square, or a constant multiple of x pixels square.

If it is determined in step S104 that the detection error D2 is equal to or greater than the first threshold and less than the second threshold (step S104: equal to or greater than the first threshold and less than the second threshold), the analysis region determination unit 83 does not change the size of the analysis target region (step S108). At this time, the analysis region determination unit 83 changes the position of the analysis target region so that the center position of the analysis target region coincides with the center position of the alignment mark M as closely as possible.

If it is determined in step S104 that the detection error D2 is equal to or greater than the second threshold (step S104: equal to or greater than the second threshold), the analysis area determination unit 83 expands the size of the area to be analyzed (step S109). Specifically, for example, the size of the area to be analyzed is increased by r pixels in both the vertical and horizontal directions. In other words, if the size of the area to be analyzed at that time is m pixels x n pixels, it is increased to (m + r) pixels x (n + r) pixels.

In this way, the analysis region determination unit 83 expands the analysis target region when the detection error D2 is relatively large, i.e., when the detection error D2 increases. This reduces the detection error D2 in the next image analysis process (step S103), and suppresses a decrease in detection accuracy.

After the judgment in step S104, or after steps S105 to S107, step S108, or step S109 are completed, the analysis area determination unit 83 judges whether the displacement of the alignment mark M is greater than a reference value (step S110). The displacement of the alignment mark M is, for example, calculated as the difference between the center position of the latest alignment mark M and the center position of the alignment mark M one time before. Note that the displacement of the alignment mark M may be, for example, calculated as the difference between the center position of the latest alignment mark M and the center position of the alignment mark M a predetermined k times before, or may be calculated by taking into account not only the difference in center positions but also the angle of the alignment mark M.

In step S110, if the displacement of the alignment mark M is greater than a predetermined reference value (step S110: Yes), the size of the area to be analyzed is enlarged (step S111). Specifically, for example, the size of the area to be analyzed is enlarged by s pixels in both the vertical and horizontal directions. In other words, if the size of the area to be analyzed at that time is m pixels x n pixels, it is set to (m + s) pixels x (n + s) pixels. The analysis area determination unit 83 then passes area information D3 including the size and position of the area to be analyzed to the analysis area extraction unit 81, and the process returns to step S101.

On the other hand, in step S110, if the displacement of the alignment mark M is equal to or less than the predetermined reference value (step S110: No), the size and position of the analysis target area at that time are passed to the analysis area extraction unit 81 as area information D3, and the process returns to step S101.

In this way, each time a captured image Di is acquired and analyzed, the size of the area to be analyzed is adjusted according to the value of the detection error. This makes it possible to reduce the area to be analyzed without causing the detection error to exceed a predetermined second threshold value. In other words, the amount of calculation required for analysis can be reduced while maintaining the detection accuracy of the alignment mark M at a certain level or higher.

Here, Figs. 5 to 8 show examples of changes in the analysis target area in the image processing of this embodiment. Figs. 5 to 8 show a case where the position and angle of the cross-shaped alignment mark M do not move (there is no displacement), the detection error is less than the first threshold value in the first to seventh steps S104, and the displacement of the alignment mark M is equal to or less than the reference value in the first to seventh steps S110.

In Figures 5 to 8, the range of the captured image Di is indicated by a solid line. The first analysis target area A1, the second analysis target area A2, the third analysis target area A3, the fourth analysis target area A4, the fifth analysis target area A5, the sixth analysis target area A6, the seventh analysis target area A7, and the eighth analysis target area A8 are indicated by dashed lines. Note that the range of the first analysis target area A1 is shown slightly inside the solid line showing the captured image Di. In reality, A1 is the same range as Di, but because the range is unclear when the solid and dashed lines overlap, they are intentionally shifted when displayed.

In the examples of Figures 5 to 8, the captured image Di and the first analysis target area A1 are 200 pixels square. In step S104 for the first time, the detection error is less than the first threshold, so in step S105, the size of the analysis target area is reduced by 20 pixels to 180 pixels square. Here, as shown in Figure 5, if the analysis target area is set so that its center coincides with the center of the alignment mark M, the area indicated by A2' in Figure 5 becomes the analysis target area. Since area A2' has an area that does not overlap with the captured image Di, in the examples of Figures 5 to 8, the position of the analysis target area is corrected, and area A2 in the captured image Di, which is 180 pixels square and whose center is closest to the center of the alignment mark M, is set as the analysis target area.

Subsequently, in the second step S104, since the detection error is less than the first threshold, in step S105, the size of the analysis target area is reduced by 20 pixels to 160 pixels square. Here, as shown in FIG. 6, if the analysis target area is set so that its center coincides with the center of the alignment mark M, the area indicated by A3' in FIG. 6 becomes the analysis target area. Since area A3' has an area that does not overlap with the captured image Di, the position of the analysis target area is corrected, and area A4 in the captured image Di, which is 160 pixels square and whose center is closest to the center of the alignment mark M, is set as the analysis target area.

In the third iteration of step S104, the size of the area to be analyzed is similarly reduced by 20 pixels each time to 140 pixels square. Here, as shown in FIG. 7, if the area to be analyzed is set so that its center coincides with the center of the alignment mark M, the area indicated by A4' in FIG. 7 becomes the area to be analyzed. Since area A4' has an area that does not overlap with the captured image Di, the position of the area to be analyzed is corrected, and area A4 in the captured image Di, which is 140 pixels square and whose center is closest to the center of the alignment mark M, is set as the area to be analyzed.

In step S104 from the fourth to the seventh times, the size of the analysis target area is similarly reduced by 20 pixels each time, to 120 pixels square, 100 pixels square, and 80 pixels square, respectively. As shown in FIG. 8, in these cases, when the analysis target area is set so that its center coincides with the center of the alignment mark M, all of the analysis target areas A5 to A8 shown in FIG. 8 are within the captured image Di, so there is no need to correct their positions.

As shown in the examples of Figures 5 to 8, the amount of calculations required for image analysis can be appropriately reduced by reducing the area to be analyzed to a portion of the area of the alignment mark M so that the detection error falls within a specified range. In actual image processing, the position of the alignment mark M fluctuates. The area to be analyzed also follows the movement of the alignment mark M to include the alignment mark M and its surrounding area. At that time, the area to be analyzed is appropriately reduced so that the detection error of the alignment mark M falls within a specified range.

4. Modifications
Although the embodiment of the present invention has been described above, the present invention is not limited to the above embodiment.

In the above embodiment, the control object of the control unit 10 having the position detection unit 90, which is an image processing device, was the drawing device 1. Therefore, this position detection unit 90 appropriately adjusted the analysis target area in order to detect the position and angle of the alignment mark M provided on the substrate W. However, the objects detected by the image processing device of the present invention are not limited to this. For example, it can be used for various purposes, such as detecting alignment marks provided on a surveying object in a surveying device, or detecting alignment marks provided on a substrate in a substrate inspection device.

In the above embodiment, the detection error value was divided into three ranges: less than the first threshold, greater than or equal to the first threshold and less than the second threshold, and greater than or equal to the second threshold, and three processes were selected for reducing, leaving the analysis target area unchanged, and expanding. However, the present invention is not limited to this.

For example, the first threshold and the second threshold may be the same threshold. Then, if the detection error is less than the threshold, the analysis target area may be reduced, and if the detection error is equal to or greater than the threshold, the analysis target area may be expanded.

Furthermore, for example, four ranges of the detection error are set by three thresholds, a first threshold, a second threshold, and a third threshold, and when the detection error is less than the first threshold, the analysis target area is reduced by two steps, when the detection error is equal to or greater than the first threshold and less than the second threshold, the analysis target area is reduced by one step, when the detection error is equal to or greater than the second threshold and less than the third threshold, the analysis target area is expanded by one step, and when the detection error is equal to or greater than the third threshold, the analysis target area is expanded by two steps.

Furthermore, the elements appearing in the above embodiments and variations may be combined as appropriate to the extent that no contradictions arise.

REFERENCE SIGNS LIST 1 Drawing device 10 Control unit 50 Camera 81 Analysis area extraction unit 82 Mark position analysis unit 83 Analysis area determination unit 90 Position detection unit D1 Image for analysis D2 Detection error D3 Area information Di Photographed image Do Detection result

Claims

An image processing method for detecting a position of a detection target from a photographed image that is periodically acquired, comprising:
a) analyzing an analysis target area of the captured image to obtain a position of the detection target and a detection error;
b) changing the analysis target region based on the magnitude of the detection error;
Including,
The image processing method further comprises repeating the steps a) and b) multiple times.
2. The image processing method according to claim 1,
In the step b), the analysis target region is reduced if the detection error is smaller than a predetermined first threshold.
3. The image processing method according to claim 2,
An image processing method, comprising the steps of: in step b), reducing the analysis target region to a size at least equal to or larger than a predetermined minimum range.
4. The image processing method according to claim 2, further comprising:
In the step b), the analysis target region is enlarged if the detection error is greater than a predetermined second threshold.
5. The image processing method according to claim 1, further comprising:
c) after steps a) and b), expanding the analysis target region when the displacement of the detection target is greater than a reference value.
An image processing device that detects a position of a detection target from a photographed image that is periodically acquired,
an analysis region extraction unit that extracts an analysis target region of the photographed image input from outside and generates an analysis image;
a mark position analysis unit that analyzes the analysis image and obtains a position of the detection target and a detection error;
an analysis region determination unit that changes the analysis target region based on the detection error;
The image processing device includes: