WO2018225530A1

WO2018225530A1 - Image processing device, image processing method, program, and projector device

Info

Publication number: WO2018225530A1
Application number: PCT/JP2018/020112
Authority: WO
Inventors: 宏昌長沼
Original assignee: ソニー株式会社
Priority date: 2017-06-09
Filing date: 2018-05-25
Publication date: 2018-12-13

Abstract

The present disclosure relates to an image processing device, an image processing method, a program, and a projector device that facilitate prompt correction for the effect on the surface shape and the color on a projection surface. A correction vector calculating unit calculates a correction vector used for projection-surface distortion correction for correcting distortions generated in an image according to the surface shape of a projection surface on the basis of a test pattern image acquired by capturing a test pattern projected onto an arbitrary projection surface. A correction data generating unit generates correction data used for projection-surface color correction for correcting image colors according to the color of the projection surface on the basis of the test pattern image. The test pattern is formed from round dots arranged in a grid pattern on a white background. The test pattern image used to calculate the correction vector and to generate the correction data is acquired by a single capture of the test pattern. The present technique is applicable to, for example, a projector device equipped with a projection unit and an imaging unit.

Description

Image processing apparatus, image processing method, program, and projector apparatus

The present disclosure relates to an image processing device, an image processing method, a program, and a projector device, and in particular, an image processing device and an image processing that are capable of correcting the influence of the surface shape and color of a projection surface more quickly. The present invention relates to a method, a program, and a projector apparatus.

In general, there are various types of projector devices. For example, a panel such as DLP (Digital Light Processing) or liquid crystal is used to transmit or reflect light from a light source, so that an image is projected on a projection surface such as a screen. Configured to project.

By the way, when projecting an image by a projector device using a wall as a projection surface in daily life instead of a flat screen having perfect diffuse reflection characteristics, the projected image may be distorted according to the surface shape of the projection surface. The color of the projected image may appear different depending on the color of the projection surface. Therefore, a projection plane distortion correction that corrects distortion generated in the image according to the surface shape of the projection plane is performed, and a projection plane color correction that corrects the color of the image according to the color of the projection plane is performed. Therefore, it is necessary to correct the influence of the surface shape and color of the projection surface.

Conventionally, as a technique for correcting projection plane distortion by image processing, a technique called active sensing using an imaging device is often used. In this method, a test pattern is projected from the projector device, the corresponding points between the projector device and the imaging device are obtained, and the distortion amount of the projector device is estimated from known information, so that an image corresponding to the surface shape of the projection surface Can be corrected.

For example, Patent Document 1 discloses a method of detecting a checker and a corner portion of the checker using a check pattern, and obtaining a corresponding point between the projector device and the imaging device.

Also, as a method for correcting the projection plane color by image processing, conventionally, multiple colors are projected from the projector device, the color of the projection plane is estimated from the subtractive color mixture result with the projection plane, and the influence of the color is corrected. A technique for obtaining a correction value to be used is often used.

However, when various walls in daily life are used as the projection plane, a color different from the actual projection plane is often estimated from the difference in spectral reflection. Therefore, in order to perform projection surface color correction with high accuracy by image processing, it is necessary to project a large number of colors from the projector device and repeat correction until the subtractive color mixture result with the projection surface reaches an expected value. Therefore, it is not only necessary to image many colors projected from the projector apparatus, but it is difficult to predict the time until the subtractive color mixture result with the projection surface converges to the expected value.

International Publication No. 2016/002510

As described above, when a wall in daily life is used as a projection plane, it is necessary to project a test pattern in order to perform projection plane distortion correction, and to repeat projection of many colors in order to perform projection plane color correction. there were. Therefore, these processes require a long time, and it has been required to perform the processes more quickly.

The present disclosure has been made in view of such a situation, and makes it possible to more quickly correct the influence of the surface shape and color of the projection surface.

An image processing apparatus according to one aspect of the present disclosure corrects distortion generated in an image according to a surface shape of the projection surface from a test pattern image obtained as a result of imaging a test pattern projected on an arbitrary projection surface. A correction vector calculation unit that obtains a correction vector used in distortion correction, and a correction data generation unit that generates correction data used in projection plane color correction that corrects the color of the image according to the color of the projection plane from the test pattern image The test pattern includes circular dots arranged in a grid pattern on a white background, and the test pattern image used for calculation of the correction vector and generation of the correction data is one time of the test pattern. It was obtained by imaging.

An image processing method or program according to one aspect of the present disclosure corrects distortion generated in an image according to a surface shape of the projection plane from a test pattern image obtained as a result of imaging a test pattern projected on an arbitrary projection plane. Obtaining a correction vector used in projection plane distortion correction, and generating, from the test pattern image, correction data used in projection plane color correction for correcting the color of the image according to the color of the projection plane, The circular dots are arranged in a grid pattern on a white background, and the test pattern image used for calculating the correction vector and generating the correction data is obtained by one imaging of the test pattern. is there.

A projector device according to an aspect of the present disclosure includes a projection unit that projects a test pattern on an arbitrary projection plane, an imaging unit that captures the test pattern, and a test pattern image obtained as a result of imaging the test pattern by the imaging unit A correction vector calculation unit for obtaining a correction vector used in correction of projection plane distortion for correcting distortion generated in the image according to the surface shape of the projection plane, and an image corresponding to the color of the projection plane from the test pattern image. A correction data generation unit for generating correction data used in projection plane color correction for correcting the color of the test pattern, wherein the test pattern includes circular dots arranged in a grid pattern on a white background, The test pattern image used for generation of correction data is obtained by one imaging of the test pattern.

In one aspect of the present disclosure, projection plane distortion correction is performed to correct distortion generated in an image according to a surface shape of the projection plane from a test pattern image obtained as a result of imaging a test pattern projected on an arbitrary projection plane. A correction vector to be used is obtained, and correction data used in projection plane color correction for correcting the color of the image according to the color of the projection plane is generated from the test pattern image. In the test pattern, circular dots are arranged in a grid pattern on a white background, and the test pattern image used for calculating the correction vector and generating the correction data is obtained by capturing the test pattern once. It is assumed that it was obtained.

According to one aspect of the present disclosure, correction for the influence of the surface shape and color of the projection surface can be performed more quickly.

It should be noted that the effects described here are not necessarily limited, and may be any of the effects described in the present disclosure.

It is a block diagram which shows the structural example of one Embodiment of the projector apparatus to which this technique is applied. It is a figure which shows an example of a test pattern. It is a figure which shows the structural example of a captured image process part. It is a flowchart explaining the process which projects the image which correct | amended corresponding to the influence of the surface shape and color of a projection surface. It is a flowchart explaining a correction vector calculation process. It is a flowchart explaining a correction data generation process. It is a flowchart explaining the production | generation process of a color ratio database. It is a figure which shows the example of distribution of the color ratio registered as a color ratio database. And FIG. 18 is a block diagram illustrating a configuration example of an embodiment of a computer to which the present technology is applied.

Hereinafter, specific embodiments to which the present technology is applied will be described in detail with reference to the drawings.

<Configuration example of projector device>
FIG. 1 is a block diagram illustrating a configuration example of an embodiment of a projector device to which the present technology is applied.

As shown in FIG. 1, the projector device 11 includes a projection unit 12, an imaging unit 13, a projection image processing unit 14, a captured image processing unit 15, and a storage unit 16. The projection plane distortion correction and the projection plane color correction can be performed based on the corresponding points.

The projection unit 12 projects an image on a projection surface (not shown) by transmitting or reflecting light emitted from the light source using, for example, DLP or liquid crystal. In addition, for example, when projecting an image onto projection surfaces of various surface shapes and colors, the projection unit 12 corrects distortion generated in the image due to the surface shape of the projection surface, It is possible to project an image that has undergone projection plane color correction for correcting that the color of the image looks different depending on the color. Furthermore, the projection unit 12 can project a test pattern (for example, FIG. 2 described later) used in the projection plane distortion correction and the projection plane color correction.

The imaging unit 13 uses, for example, an imaging device such as a CMOS (Complementary Metal Oxide Semiconductor) image sensor to image a test pattern that the projection unit 12 projects onto the projection surface. At this time, an image obtained by imaging the test pattern by the imaging unit 13 (hereinafter referred to as a test pattern image as appropriate) is distorted due to the surface shape of the projection surface, and the color looks different depending on the color of the projection surface. It will be a thing. Then, the imaging unit 13 supplies the test pattern image to the captured image processing unit 15.

For example, the projection image processing unit 14 performs projection plane distortion correction and projection plane color correction on an image reproduced by a reproduction device (not shown), and when projected onto the projection plane, there is no distortion and the colors look different. The image processed so as not to occur is supplied to the projection unit 12.

Based on the test pattern image supplied from the imaging unit 13, the captured image processing unit 15 generates correction vector calculation processing for obtaining a correction vector used in projection plane distortion correction and correction data used in projection plane color correction, for example. Correction data generation processing is performed. At this time, the captured image processing unit 15 can use the same test pattern image in the correction vector calculation process and the correction data generation process, and the imaging unit 13 needs to capture the test pattern only once.

The storage unit 16 stores a color ratio database that is referred to when the captured image processing unit 15 performs correction data generation processing. For example, as described later with reference to FIGS. 7 and 8, a color ratio database for performing projection plane color correction using a white region is obtained in advance and stored in the storage unit 16. For example, the color ratio database is a two-dimensional LUT (Lookup table) with the red color ratio (R / G) to green and the blue color ratio (B / G) to green as axes.

Thus, the projector apparatus 11 is configured, and the imaging unit 13 captures the test pattern projected by the projection unit 12 only once, and the correction vector is calculated using one test pattern image obtained by the imaging. Processing and correction data generation processing are performed. As a result, the projector device 11 projects the test pattern in order to correct the projection plane distortion and projects the projection pattern without repeating many color projections in order to perform the projection plane color correction. The influence of the surface shape and color of the projection surface on the image can be corrected quickly.

<Example of test pattern>
FIG. 2 shows an example of a test pattern used for projection plane distortion correction and projection plane color correction of the projector apparatus 11.

As shown in FIG. 2, the projector apparatus 11 employs a test pattern (so-called polka dot pattern) in which small circular dots are arranged in a grid pattern on a white background. In this test pattern, for example, the dot area is black and the area other than the dot is white. If the coordinates of the dots arranged in a grid pattern can be obtained, the dot shape of the test pattern is not limited to a circle, and for example, various arbitrary shapes such as a square and a triangle can be adopted. .

The captured image processing unit 15 obtains a correction vector used in projection plane distortion correction from the dot arrangement by using one test pattern image obtained by one imaging of such a test pattern, and obtains a white region. Correction data used in projection plane color correction can be generated.

<Configuration Example of Captured Image Processing Unit>
With reference to FIG. 3, the configuration of the captured image processing unit 15 and the processing performed in the captured image processing unit 15 will be described.

As shown in FIG. 3, the captured image processing unit 15 includes a corresponding point detection unit 21, a correction vector calculation unit 22, a color ratio detection unit 23, and a correction data creation unit 24.

Corresponding point detection unit 21 detects the centroids of all dots copied in the test pattern image supplied from imaging unit 13 and calculates the centroid coordinates of those dots. Then, the corresponding point detection unit 21 holds the barycentric coordinates of the dots according to the arrangement order of the dots arranged in the test pattern (for example, the raster order from the upper left), and the coordinates of the image projected by the projection unit 12 Then, a corresponding point with the coordinates of the image captured by the imaging unit 13 is detected.

Further, the corresponding point detection unit 21 does not need to obtain corresponding points with a fine granularity such as a pixel unit of the projected image. For example, the corresponding points have a granularity corresponding to dots that are discretely arranged in the test pattern. You can ask for. For example, the particle size of the dots arranged in the test pattern is set so that the surface shape of the projection surface is not extremely distorted and the coordinate density is sufficient for a curved surface with a gentle curvature.

The correction vector calculation unit 22 calculates a correction vector so that the barycentric coordinates of all the dots detected by the corresponding point detection unit 21 become a grid array. By applying this correction vector to the projection unit 12, distortion generated in the image can be geometrically corrected. In other words, the correction vector calculation unit 22 corrects the correction vector (that is, the barycentric coordinates of the detected dot) from the test pattern image in which the distortion is generated according to the surface shape of the projection surface. By calculating (correction vector having a grid array), it is possible to obtain a correction vector for correcting distortion generated in the image in accordance with the surface shape of the projection surface.

The color ratio detection unit 23 detects, for example, the color ratio using the white area in the test pattern of FIG. 2 for each corresponding point detected by the corresponding point detection unit 21.

The correction data creation unit 24 refers to the color ratio database stored in the storage unit 16, reads a correction value corresponding to the color ratio detected by the color ratio detection unit 23, and is detected by the corresponding point detection unit 21. Correction data including a plurality of correction values for each corresponding point is generated. As for the projection surface color correction, the test pattern (FIG. 2) used in the geometric correction is inverted and replaced with a color that will most contribute to the estimation of the color of the projection surface. That is, the correction data creation unit 24 corrects the correction data (that is, the detected color ratio to the detected color ratio) from the test pattern image that appears to be different depending on the color of the projection surface. Corresponding multiple correction values for each corresponding point) can be generated.

<Example of processing executed by projector device>
With reference to the flowchart shown in FIG. 4, an example of processing in which the projector device 11 projects an image corrected in accordance with the influence of the surface shape and color of the projection surface will be described.

In step S11, the projection unit 12 projects a test pattern as shown in FIG. 2 onto an arbitrary projection plane.

In step S12, the imaging unit 13 images the test pattern projected on the projection plane by the projection unit 12, and supplies the test pattern image obtained as a result of the imaging to the captured image processing unit 15.

In step S13, the captured image processing unit 15 performs a correction vector calculation process (see FIG. 5 described later) for obtaining a correction vector used in projection plane distortion correction, and supplies the correction vector to the projection image processing unit 14.

In step S14, the captured image processing unit 15 performs correction data generation processing (see FIG. 6 described later) for generating correction data used in projection surface color correction, and supplies the correction data to the projection image processing unit 14.

In step S15, the projection image processing unit 14 performs a projection image correction process for correcting distortion and color for the image to be projected. That is, the projection image processing unit 14 performs projection plane distortion correction using the correction vector supplied from the captured image processing unit 15 in step S13, and uses the correction data supplied from the captured image processing unit 15 in step S14. To correct the projection surface color. Then, by performing projection plane distortion correction and projection plane color correction by the projection image processing unit 14, distortion generated in the image due to the surface shape of the projection plane is corrected, and the color of the image looks different depending on the color of the projection plane. An image whose color has been corrected so as not to occur is supplied to the projection unit 12, and the projection unit 12 projects the image, and the processing is terminated.

FIG. 5 is a flowchart for explaining the correction vector calculation process in step S13 of FIG.

In step S21, the corresponding point detection unit 21 detects all dots copied in the test pattern image supplied from the imaging unit 13 in step S12 of FIG.

In step S22, the corresponding point detection unit 21 detects the centroids of all the dots detected in step S21, and calculates the centroid coordinates of those dots.

In step S23, for example, when the corresponding point detection unit 21 performs processing in raster order, the corresponding point detection unit 21 searches for a dot closest to the upper left end as a processing target that first holds the barycentric coordinates.

In step S24, the corresponding point detection unit 21 holds the barycentric coordinates of the dots specified by the search in step S23.

In step S <b> 25, for example, when processing in raster order, the corresponding point detection unit 21 searches for a dot closest to the right in the right direction as a processing target immediately before as a processing target for holding the barycentric coordinates. To do.

In step S26, the corresponding point detection unit 21 holds the barycentric coordinates of the dots specified by the search in step S25.

In step S27, the corresponding point detection unit 21 determines whether or not all dots in the current horizontal line have been processed, for example, when processing is performed in raster order. For example, when the dot at the right end of the current horizontal line is the processing target, it is determined that all the dots on the current horizontal line are the processing target.

In step S27, when the corresponding point detection unit 21 determines that all the dots in the current horizontal line are not to be processed, the process returns to step S25, and the next dot in the current horizontal line is processed. Thereafter, the same processing is repeated.

On the other hand, if the corresponding point detection unit 21 determines in step S27 that all dots in the current horizontal line are to be processed, the process proceeds to step S28.

In step S28, the corresponding point detection unit 21 moves the dot to be processed to the left end, and searches for the closest dot in the downward direction as the first dot of the next horizontal line.

In step S29, the corresponding point detection unit 21 determines whether, for example, all horizontal lines are processed, for example, if processing is performed in raster order, whether the lowest horizontal line is processed. Determine. For example, if the closest dot in the downward direction is specified as a result of the search in step S28, it is determined that not all horizontal lines are to be processed.

In step S29, when the corresponding point detection unit 21 determines that not all horizontal lines are to be processed, the process returns to step S26, and the horizontal line of the dot specified by the search in step S28 is set as a processing target. The same process is repeated.

On the other hand, if the corresponding point detection unit 21 determines in step S29 that all horizontal lines have been processed, that is, if the lowest horizontal line has been processed, the process proceeds to step S30. In this case, the center-of-gravity coordinates are held from the upper left dot to the lower right dot, which is the processing target.

In step S30, the correction vector calculation unit 22 calculates a correction vector in which the barycentric coordinates of all the dots detected and held by the corresponding point detection unit 21 in the processing of steps S21 to S29 become a grid array. And the correction vector calculation part 22 hold | maintains the calculated correction vector, and a correction vector calculation process is complete | finished.

FIG. 6 is a flowchart for explaining the correction data generation process in step S14 of FIG.

In step S41, the color ratio detection unit 23 extracts the color of the projection plane by extracting and smoothing portions other than the dots of the test pattern image supplied from the imaging unit 13 in step S12 of FIG.

In step S42, the color ratio detection unit 23 calculates and holds the red color ratio (R / G) to green and the blue color ratio (B / G) to green.

In step S43, the correction data creation unit 24 refers to the color ratio database stored in the storage unit 16, and holds the color ratio detection unit 23 in step S42 for each corresponding point detected by the corresponding point detection unit 21. A correction value corresponding to the current color ratio is extracted.

In step S44, the correction data creation unit 24 creates and holds correction data composed of the correction values extracted for each corresponding point in step S43, and the correction data generation process ends.

As described above, the projector device 11 can use the test pattern as shown in FIG. 2 to obtain a correction vector used for projection plane distortion correction and generate correction data used for projection plane color correction. . Then, the projection plane distortion correction is performed using the correction vector, and the image on which the projection plane color correction is performed using the correction data, that is, the distortion generated in the image due to the surface shape of the projection plane is corrected, and the color of the projection plane is corrected. It is possible to project an image that does not look different in the color of the image.

At this time, since the projector device 11 only needs to capture the test pattern once, the image can be corrected more quickly. In addition, by adopting the color ratio database as described above, the projector device 11 can correct all projection plane colors in the spectral range of the imaging unit 13 with high accuracy and create correction data at high speed. be able to.

Therefore, for example, when projecting an image on a colored distorted wall surface, the projector device 11 can perform projection plane distortion correction and projection plane color correction by one imaging of a test pattern, and the projected image Thus, the influence of the surface shape and color of the projection surface can be quickly corrected.

<An example of how to determine the correction value>
With reference to FIG. 7 and FIG. 8, a description will be given of how to obtain a correction value used in projection plane color correction using white.

For example, the white area (area other than the dots) of the test pattern in FIG. 2 projected by the projection unit 12 is an output when all the panel colors of the projection unit 12 are turned on. Using this spectral characteristic when outputting white, calculate the spectrum actually output by the product sum with the projected plane, and perform signal processing so that the spectrum becomes the spectrum at the time of perfect diffuse reflection. By doing so, the projection plane color is corrected.

That is, when a test pattern is projected, light based on the projector spectrum of the projection unit 12 is output. Since a normal screen has complete diffuse reflection characteristics, when the image is viewed by the human eye or imaged by the imaging unit 13, the light of the projector spectrum itself is observed, and the spectral characteristics of the imaging unit 13 and the projector spectrum of the projection unit 12 are observed. Is the amount of light observed. On the other hand, in the case of wall reflection, a reflection spectrum of the wall, for example, in the case of a colored wall, a characteristic that a specific wavelength is attenuated appears in the reflection spectrum. For this reason, in the case of a colored wall, the product sum of the projector spectrum and the reflection spectrum of the wall becomes light that is observed by a person or the imaging unit 13. Since the light is observed by the imaging unit 13, the detected hue and color ratio are different between the screen and the colored wall.

Therefore, by obtaining in advance the color ratio for each projection plane of various colors and storing it in the storage unit 16 as a color ratio database, it is possible to perform color correction according to the color of the projection plane.

The color ratio database generation process will be described with reference to the flowchart of FIG. The color ratio database can be generated by, for example, the captured image processing unit 15 using an image obtained by the imaging unit 13 capturing white images projected on projection surfaces of various colors.

In step S51, the captured image processing unit 15 obtains a spectrum at the time of complete diffuse reflection, that is, the projector of the projection unit 12, from an image obtained by the imaging unit 13 capturing white projected on a screen having complete diffuse reflection characteristics. Extract the spectrum.

In step S52, the captured image processing unit 15 calculates the product sum of the projector spectrum extracted in step S51 and the camera spectrum of the imaging unit 13 for observing the spectrum.

In step S53, the captured image processing unit 15 holds the product-sum value calculated in step S52 as a corrected target color ratio.

In step S54, the captured image processing unit 15 extracts the wall surface spectrum of the projection plane from the image obtained by the imaging unit 13 capturing the white color projected on the projection plane of the desired color.

In step S55, the captured image processing unit 15 calculates the product sum of the wall surface spectrum extracted in step S54, the projector spectrum, and the camera spectrum.

In step S56, since the product sum value calculated in step S55 is the actually observed color ratio, the captured image processing unit 15 obtains a comparison result between the color ratio and the correction target color ratio held in step S53. The correction target value is calculated.

In step S57, the captured image processing unit 15 determines whether or not to end the generation of the color ratio database. For example, when white is projected on the projection planes of all desired colors and all of the correction target values are calculated, it is determined that the generation of the color ratio database is finished.

If it is determined in step S57 that the generation of the color ratio database is not terminated, the process returns to step S54, and the same process is repeated for the projection plane of the color for which the correction target value has not yet been calculated. Done.

On the other hand, if it is determined in step S57 that the generation of the color ratio database is to be terminated, the process proceeds to step S58.

In step S58, the captured image processing unit 15 stores the correction target values calculated for the projection planes of all colors as a target by repeating the processing of steps S54 to S56 as the color ratio database of the storage unit 16, and the processing is as follows. Is terminated.

In the projector device 11, correction values (parameters) for correction calculated in advance are accumulated in the storage unit 16 as a color ratio database, the color ratio is obtained from the imaging result of the imaging unit 13, and the color A correction value for appropriate correction is adopted from the ratio. Here, the color ratio is obtained by previously obtaining the ratio of red to blue with respect to green from the spectral result of the known imaging unit 13, and using this as a key, a correction value can be selected from the color ratio database.

For example, FIG. 8 shows an example of color ratio distribution registered as a color ratio database.

FIG. 8 plots the color ratio by obtaining the relationship with the spectral characteristics of the imaging unit 13 from a spectral database (SOCS: Standard Object Color Color Spectra) in which spectral reflectances of various materials are registered. Based on the color ratio plotted in this way, the captured image processing unit 15 can call a correction value corresponding to the estimated color of the projection plane and perform projection plane color correction according to the color of the projection plane. .

FIG. 9 is a block diagram showing an example of the hardware configuration of a computer that executes the above-described series of processing by a program.

In a computer, a CPU (Central Processing Unit) 101, a ROM (Read Only Memory) 102, a RAM (Random Access Memory) 103, and an EEPROM (Electronically Erasable Memory and Programmable Read Only Memory) 104 are interconnected by a bus 105. . An input / output interface 106 is further connected to the bus 105, and the input / output interface 106 is connected to the outside.

In the computer configured as described above, for example, the CPU 101 loads the program stored in the ROM 102 and the EEPROM 104 to the RAM 103 via the bus 105 and executes the program, thereby performing the above-described series of processing. A program executed by the computer (CPU 101) can be written in the ROM 102 in advance, and can be installed or updated from the outside in the EEPROM 104 via the input / output interface 105.

<Combination example of configuration>
In addition, this technique can also take the following structures.
(1)
A correction vector for obtaining a correction vector used in projection plane distortion correction for correcting distortion generated in an image according to the surface shape of the projection plane from a test pattern image obtained as a result of imaging a test pattern projected on an arbitrary projection plane A calculation unit;
A correction data generation unit that generates correction data used in projection plane color correction for correcting the color of the image according to the color of the projection plane from the test pattern image,
In the test pattern, circular dots are arranged in a grid pattern on a white background,
The image processing apparatus, wherein the test pattern image used for calculating the correction vector and generating the correction data is obtained by one imaging of the test pattern.
(2)
The image processing apparatus according to (1), wherein the correction vector calculation unit calculates a correction vector so that barycentric coordinates of the dots extracted from the test pattern image become a grid array.
(3)
The correction data generation unit detects a color ratio using a white region of the test pattern projected onto the projection plane, and generates the correction data with reference to a previously obtained color ratio database. The image processing apparatus according to (1) or (2) above.
(4)
From a test pattern image obtained as a result of imaging a test pattern projected on an arbitrary projection plane, a correction vector used in projection plane distortion correction for correcting distortion generated in the image according to the surface shape of the projection plane is obtained.
Generating, from the test pattern image, correction data used in projection plane color correction for correcting the color of the image according to the color of the projection plane;
In the test pattern, circular dots are arranged in a grid pattern on a white background,
The image processing method, wherein the test pattern image used for calculating the correction vector and generating the correction data is obtained by one imaging of the test pattern.
(5)
From a test pattern image obtained as a result of imaging a test pattern projected on an arbitrary projection plane, a correction vector used in projection plane distortion correction for correcting distortion generated in the image according to the surface shape of the projection plane is obtained.
Generating, from the test pattern image, correction data used in projection plane color correction for correcting the color of the image according to the color of the projection plane;
In the test pattern, circular dots are arranged in a grid pattern on a white background,
The test pattern image used for calculation of the correction vector and generation of the correction data is obtained by one imaging of the test pattern. A program for causing a computer to execute processing.
(6)
A projection unit that projects a test pattern on an arbitrary projection plane;
An imaging unit for imaging the test pattern;
A correction vector calculation unit for obtaining a correction vector used in projection plane distortion correction for correcting distortion generated in the image according to the surface shape of the projection plane, from a test pattern image obtained as a result of imaging the test pattern by the imaging unit; ,
A correction data generation unit that generates correction data used in projection plane color correction for correcting the color of the image according to the color of the projection plane from the test pattern image,
In the test pattern, circular dots are arranged in a grid pattern on a white background,
The test pattern image used for calculation of the correction vector and generation of the correction data is obtained by one imaging of the test pattern.

Note that the present embodiment is not limited to the above-described embodiment, and various modifications can be made without departing from the gist of the present disclosure. Moreover, the effect described in this specification is an illustration to the last, and is not limited, There may exist another effect.

11 projector device, 12 projection unit, 13 imaging unit, 14 projection image processing unit, 15 captured image processing unit, 16 storage unit, 21 corresponding point detection unit, 22 correction vector calculation unit, 23 color ratio detection unit, 24 correction data creation Part

Claims

A correction vector for obtaining a correction vector used in projection plane distortion correction for correcting distortion generated in an image according to the surface shape of the projection plane from a test pattern image obtained as a result of imaging a test pattern projected on an arbitrary projection plane A calculation unit;
A correction data generation unit that generates correction data used in projection plane color correction for correcting the color of the image according to the color of the projection plane from the test pattern image,
In the test pattern, circular dots are arranged in a grid pattern on a white background,
The image processing apparatus, wherein the test pattern image used for calculating the correction vector and generating the correction data is obtained by one imaging of the test pattern.
The image processing apparatus according to claim 1, wherein the correction vector calculation unit calculates a correction vector such that barycentric coordinates of the dots extracted from the test pattern image become a grid array.
The correction data generation unit detects a color ratio using a white region of the test pattern projected onto the projection plane, and generates the correction data with reference to a previously obtained color ratio database. The image processing apparatus according to claim 1.
From a test pattern image obtained as a result of imaging a test pattern projected on an arbitrary projection plane, a correction vector used in projection plane distortion correction for correcting distortion generated in the image according to the surface shape of the projection plane is obtained.
Generating, from the test pattern image, correction data used in projection plane color correction for correcting the color of the image according to the color of the projection plane;
In the test pattern, circular dots are arranged in a grid pattern on a white background,
The image processing method, wherein the test pattern image used for calculating the correction vector and generating the correction data is obtained by one imaging of the test pattern.
From a test pattern image obtained as a result of imaging a test pattern projected on an arbitrary projection plane, a correction vector used in projection plane distortion correction for correcting distortion generated in the image according to the surface shape of the projection plane is obtained.
Generating, from the test pattern image, correction data used in projection plane color correction for correcting the color of the image according to the color of the projection plane;
In the test pattern, circular dots are arranged in a grid pattern on a white background,
The test pattern image used for calculation of the correction vector and generation of the correction data is obtained by one imaging of the test pattern. A program for causing a computer to execute processing.
A projection unit that projects a test pattern on an arbitrary projection plane;
An imaging unit for imaging the test pattern;
A correction vector calculation unit for obtaining a correction vector used in projection plane distortion correction for correcting distortion generated in the image according to the surface shape of the projection plane, from a test pattern image obtained as a result of imaging the test pattern by the imaging unit; ,
A correction data generation unit that generates correction data used in projection plane color correction for correcting the color of the image according to the color of the projection plane from the test pattern image,
In the test pattern, circular dots are arranged in a grid pattern on a white background,
The test pattern image used for calculation of the correction vector and generation of the correction data is obtained by one imaging of the test pattern.