JP2012042332A - Three-dimensional measurement device and three-dimensional measurement method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To improve measurement precision of a three-dimensional shape of a measurement object by reducing noise generated in a signal of the measurement object.SOLUTION: A plurality of patterns 217-220 which bisect a space are projected on a measurement object one after another, and current image data on the measurement object is obtained. Then a plurality of patterns 220-223 having been encoded based upon a Hadamard matrix are projected on the measurement object one after another, and current image data on the measurement object is obtained. Then an inverse matrix of the Hadamard matrix is used to convert the image data obtained by projecting the patterns 220-223 having been encoded based upon the Hadamard matrix into image data obtained by projecting a plurality patterns obtained by a shifting slit positions of a pattern comprising a plurality of slit lights. The three-dimensional shape of the measurement object is obtained through triangulation based upon the converted image data and the image data obtained by projecting patterns 217-220 which bisect the space.

Description

  The present invention relates to a three-dimensional measurement apparatus and a three-dimensional measurement method, and is particularly suitable for use in measuring a three-dimensional shape of a measurement target by projecting light onto the measurement target.

In general, a light cutting method, a spatial encoding method, and the like are known as methods for performing three-dimensional measurement of a measurement target.
In the light cutting method, first, laser slit light is applied to a measurement target, and the position of the measurement target reflecting the laser slit light is imaged by an imaging device. Then, the correspondence between the irradiation angle of the laser slit light and the imaging position of the imaging device is obtained, and based on the result, the three-dimensional information of the measurement object is restored by the principle of triangulation. However, in the light cutting method, since imaging is generally performed while scanning with laser slit light, it takes time to perform dense three-dimensional measurement.

  The spatial coding method uses a projector capable of projecting light having a two-dimensional pattern to solve the problem in the light cutting method (problem that requires time to scan the laser slit light). This is a technique for efficiently obtaining correspondence and performing three-dimensional measurement. In spatial coding, a space is generally divided by projecting a Gray code. Gray code can be imaged faster than the light cutting method because it is sufficient to image (logN) times to divide the space into N. However, in spatial coding, there is a case where the pattern is difficult to recognize depending on the resolution of the image sensor and the shape of the object, and there is a problem that the measurement accuracy is lowered. Therefore, in the method described in Patent Document 1, when a space is roughly divided by a spatial encoding pattern such as a Gray code, and a space is divided more densely, by projecting a plurality of slit lights onto a measurement target, The measurement accuracy is improved.

Japanese Patent Laid-Open No. 2005-3409

However, in the three-dimensional measuring apparatus that combines the projection of the spatial encoding pattern and the plurality of slit light patterns as described above, the light amount of the pattern decreases and noise increases because the slit light is projected. There was a problem of end.
The present invention has been made in view of such problems, and reduces noise generated in a signal of the measurement target when projecting light onto the measurement target and measuring the three-dimensional shape of the measurement target. An object is to improve the measurement accuracy of the three-dimensional shape of the measurement target.

  The three-dimensional measurement apparatus of the present invention projects a projection unit that projects light of a plurality of projection patterns having a light intensity distribution onto a measurement target, and the projection pattern is projected from a direction different from the light projection direction of the projection unit. Imaging means for imaging the measured object, and three-dimensional shape calculating means for calculating the three-dimensional shape of the measurement object based on the image captured by the imaging means, wherein the projecting means is a Hadamard matrix A plurality of projection patterns whose light intensity distributions are determined based on the above are projected onto the measurement object.

  According to the present invention, since a plurality of projection patterns whose light intensity distributions are determined based on the Hadamard matrix are projected onto the measurement target, noise generated in the signal of the measurement target is reduced, and the measurement target The measurement accuracy of the three-dimensional shape can be improved.

It is a figure which shows the structure of a three-dimensional measuring device. It is a figure which shows the conventional pattern. It is a figure which shows an example of the pattern of this embodiment. It is a figure explaining that the pattern using a Hadamard code can be reduced. It is a figure which shows the true value and actual value of the brightness | luminance of the captured image obtained by projecting the pattern shown in FIG.2 (c). It is a figure which shows the actual value and estimated value of the brightness | luminance of the picked-up image obtained by projecting the pattern shown in FIG.3 (b). It is a flowchart explaining the flow of a process of a three-dimensional measuring device.

FIG. 1 is a diagram illustrating an example of the configuration of the three-dimensional measurement apparatus according to the present embodiment.
The three-dimensional measuring apparatus includes an optical system 101, a projection unit 102, an image sensor 103, an exposure timing control unit 104, a projection pattern control unit 105, a control unit 106, a storage unit 107, a pattern recognition unit 108, and a three-dimensional shape calculation unit 109. It is configured with. Reference numeral 110 denotes a measurement target.
Next, detailed description of each part of the three-dimensional measuring apparatus will be given.
The optical system 101 guides light partially reflected by the measurement object 110 to the image sensor 103.
The projection unit 102 is, for example, a laser projector or a liquid crystal projector, and is a device capable of projecting (projecting) patterns (projection patterns) having different light intensities onto the measurement object 110. The projection unit 102 projects a pattern based on the projection pattern information input from the projection pattern control unit 105. Details of the pattern projected using the projection unit 102 will be described later.
The image sensor 103 outputs an image derived using the optical system 101 to the storage unit 107. The imaging element 103 images the measurement object 110 from a direction different from the pattern projection direction by the projection unit 102.

The exposure timing control unit 104 controls the image sensor 103 based on a control signal input from the control unit 106. Further, the exposure timing control unit 104 outputs a signal indicating that imaging has been completed to the control unit 106.
The projection pattern control unit 105 controls the projection unit 102 based on a control signal from the control unit 106. In addition, the projection pattern control unit 105 generates a projection pattern and outputs a signal indicating that the projection is completed to the control unit 106.

The control unit 106 outputs control signals to the projection pattern control unit 105 and the exposure timing control unit 104. Further, the control unit 106 outputs a control signal to the exposure timing control unit 104 in synchronization with reception of a signal indicating that the projection from the projection pattern control unit 105 is completed.
The storage unit 107 stores image data input from the image sensor 103. The stored image data is output to the pattern recognition unit 108.
The pattern recognition unit 108 analyzes the image data input from the storage unit 107, and uses the inverse matrix of the pattern projected on the measurement target based on the Hadamard matrix, and the image in which the slit light (slit position) is shifted. Convert to The pattern recognition unit 108 obtains a correspondence relationship between the position of the imaging element 103 and the position of the projection unit 102 based on an image obtained by imaging a pattern that divides the space and an image obtained by shifting the slit light. Pattern position information is obtained and output to the three-dimensional shape calculation unit 109.
The three-dimensional shape calculation unit 109 calculates the three-dimensional shape of the measurement object 110 based on the principle of triangulation based on the position information of the image shifted from the slit light output from the pattern recognition unit 108.

  The information processing apparatus 111 includes an exposure timing control unit 104, a projection pattern control unit 105, a control unit 106, a storage unit 107, a pattern recognition unit 108, and a three-dimensional shape calculation unit 109. The information processing apparatus 111 can be realized by, for example, an apparatus (for example, a PC) provided with a CPU, ROM, RAM, HDD, and various interfaces. In addition, the imaging unit 112 includes an optical system 101 and an imaging element 103. In addition to the optical system 101 and the image sensor 103, the imaging unit 112 includes known components necessary for imaging the subject (measurement target 110).

FIG. 2 is a diagram illustrating a conventional pattern projected using the projection unit 102 for the three-dimensional rule.
FIG. 2A is a diagram showing a general spatial coding pattern. Spatial encoding is performed by projecting a pattern that sequentially divides a space into two parts, such as patterns 201 to 205, and assigning a code that can uniquely identify the space to the space, and determining the correspondence between the imaging unit and the projection unit. This is a method for performing three-dimensional measurement based on the principle of surveying.

2B and 2C are diagrams illustrating patterns used in the technique described in Patent Document 1. FIG.
When a high-frequency pattern such as the spatial encoding pattern 205 shown in FIG. 2A is projected onto the measurement object 110, the pattern on the measurement object 110 may exceed the resolution of the image sensor 103. Therefore, there is a problem that it becomes difficult to recognize the measurement object 110. The technique described in Patent Document 1 improves such problems. In Patent Document 1, as the low-frequency patterns 206 to 208, the space is divided using the same pattern as the normal space encoding as shown in FIG. Next, like the patterns 209 to 212 shown in FIG. 2B, the plurality of patterns 209 to 212 obtained by shifting the slit positions of the patterns made of the plurality of slit lights are projected onto the measurement object 110. The reason why patterns such as the patterns 209 to 212 are used is to prevent the area on the measurement object 110 from exceeding the resolution of the image sensor 103 and prevent the measurement accuracy from being lowered.
Patterns 213 to 216 shown in FIG. 2C are patterns obtained by cutting out the minimum unit pattern of the patterns 209 to 212 shown in FIG.

FIG. 3 is a diagram showing an example of the pattern of the present embodiment projected using the projection unit 102 for the three-dimensional rule.
In the pattern used in the technique described in Patent Document 1, since the slit light is projected, there is a problem in that the amount of light of the pattern decreases and noise included in the signal (image data) of the measurement target 110 increases. Therefore, as a pattern projected using the projection unit 102 of the present embodiment, as a low frequency pattern 217 to 219, normal spatial coding as shown in FIG. 2A and FIG. The space is divided using the same (single or plural) patterns. Furthermore, in this embodiment, the projection unit 102 projects a plurality of patterns using Hadamard codes (a plurality of patterns determined based on Hadamard line examples) onto the measurement object 110 as the patterns 220 to 223.
FIG. 3B is a diagram illustrating the minimum unit patterns 224 to 227 of the patterns 220 to 223 using the Hadamard code illustrated in FIG. The pattern recognition unit 108 performs three-dimensional measurement by artificially converting the patterns 224 to 227 using Hadamard codes into an image on which the patterns 213 to 216 are projected. However, noise is reduced in the image data converted from the patterns 224 to 227 using the Hadamard code by the pattern recognition unit 108 as compared with the image data obtained when the patterns 213 to 216 are projected. It will be described later that noise generated in the image data is reduced by using the patterns 224 to 227 using the Hadamard code shown in FIG.

  FIG. 4 illustrates that a pattern using Hadamard codes can be reduced by one pattern when a plurality of patterns whose light and darkness (light intensity) are mutually inverted are used as patterns for dividing the space. FIG. In spatial coding, in general, in order to cancel the reflectance of an object to be measured 110, a pattern in which light and dark are reversed, such as patterns 228 and 229, patterns 230 and 231, patterns 232 and 233, is used. Therefore, by adding (synthesizing) images obtained by projecting patterns in which light and dark are reversed, a pattern 220 shown in FIG. Therefore, when a plurality of patterns with inverted light and dark are used as patterns for dividing the space, it is possible to reduce one pattern using Hadamard codes.

Next, patterns 224 to 227 using the Hadamard matrix shown in FIG.
The Hadamard matrix used for the projection pattern is an S-type H matrix, and the element H _n of the nth-order S-type H matrix can be obtained by the following expressions (1), (2), and (3). .

  Patterns 224 to 227 shown in FIG. 3B of this embodiment are determined based on a fourth-order Hadamard matrix represented by the following equation (4).

  Specifically, the patterns 220 to 223 shown in FIG. 3A and the patterns 224 to 227 shown in FIG. 3B are converted into binary Hadamard matrices according to the rules shown in the following equation (5), and then complemented. This is a matrix with a sign, and is a matrix as shown in equation (6). The matrix of the equation (6) is a 00 type correction reference Hadamard matrix in the classification of the fourth-order Hadamard matrix, and the main diagonal element is a uniform matrix. Of course, when the matrix element is 1, the pattern brightness is lowered, and when the matrix element is 0, the pattern brightness is raised, instead of the Hadamard matrix of the 00 type correction reference system, the 00 type normal system The Hadamard matrix may be used.

Here, it will be described that the noise included in the image data of the measurement target 110 is reduced by using the patterns 224 to 227 shown in FIG.
First, a case will be described in which the patterns 213 to 216 shown in FIG. 2C are projected and imaged instead of the patterns 224 to 227 shown in FIG.
FIG. 5 is a diagram showing an example of the true value (FIG. 5A) and the actual value (FIG. 5B) of the brightness of the captured image obtained by projecting the pattern shown in FIG. .
The true value of the brightness of the captured image is s ₁ , s ₂ , s ₃ , and s _4, and the noise during imaging is n ₁ , n ₂ , n ₃ , and n ₄ . However, noise at the time of imaging is not dependent on the signal, and the average is 0 and the variance is σ ² (σ is a standard deviation). The luminance values y ₁ , y ₂ , y ₃ , and y ₄ of the captured image captured when the patterns 213 to 216 are projected onto the measurement object 110 are expressed by the following equations (7) to (10).
y ₁ = s ₁ + n ₁ (7)
y ₂ = s ₂ + n ₂ (8)
y ₃ = s ₃ + n ₃ (9)
y ₄ = s ₄ + n ₄ (10)

  Here, the expected value E of the mean square error between the true value of the luminance of the captured image and the estimated value is expressed by the following equation (11).

FIG. 6 shows an example of the actual luminance value (FIG. 6 (a)) and estimated value (FIG. 6 (b)) of the captured image obtained by projecting the patterns 224 to 227 shown in FIG. 3 (b). FIG.
When the patterns 224 to 227 shown in FIG. 3B are projected onto the measurement object 110, the luminance values x ₁ , x ₂ , x ₃ , and x ₄ of the captured image that are actually observed are expressed by the following formula (12): It becomes like (15) Formula.
x ₁ = s ₁ + s ₂ + s ₃ + s ₄ + n ₁ (12)
x ₂ = s ₁ + s ₃ + n ₂ (13)
x ₃ = s ₁ + s ₂ + n ₃ (14)
x ₄ = s ₁ + s ₄ + n ₄ (15)

Here, the inverse matrix of the matrix shown in Expression (6) is expressed by the following Expression (16), and the estimated values s ₁ ′, s ₂ ′, s ₃ ′, and s ₄ ′ of the luminance of the captured image are The following equations (17) to (20) are obtained.

Here, the expected value E of the mean square error between the true values s ₁ , s ₂ , s ₃ and s ₄ of the brightness of the captured image and the estimated values s ₁ ′, s ₂ ′, s ₃ ′ and s ₄ ′ is The following equation (21) is obtained, which is ½ times the expected value E shown in equation (11). Therefore, it can be seen that when a pattern encoded based on the matrix of equation (6) is used, noise generated in the image data is halved.

Further, as the patterns 224 to 227 shown in FIG. 3B, an S matrix generated from a Hadamard matrix may be used. The S matrix is a matrix in which the elements of the first row and the first column of the Hadamard matrix are normalized to 1, excluding the elements of the first row and the first column, and 1 is replaced with 0 and −1 is replaced with 1. Moreover, the inverse matrix of S matrix can be calculated | required with the following (22) Formula. Here, 1n is an n × n matrix in which all elements are 1. In addition, S ^T is a transposed matrix of S.

Next, an example of the processing flow of the three-dimensional measurement apparatus will be described with reference to the flowchart of FIG.
First, the control unit 106 sends a control signal instructing to output a projection pattern to the projection pattern control unit 105. Upon receiving this control signal, the projection pattern control unit 105 controls the projection unit 102 to project the pattern for dividing the space onto the measurement object 110. Here, the projection patterns for dividing the space are, for example, patterns 217 to 219 shown in FIG. The projection pattern control unit 105 sends a signal indicating that the projection is completed to the control unit 106 at the timing when the projection is completed.

  Upon receiving this signal, the control unit 106 sends a control signal instructing imaging to the exposure timing control unit 104. Upon receiving this control signal, the exposure timing control unit 104 accumulates charges in the image sensor 103. The exposure timing control unit 104 controls the image sensor 103 and causes the storage unit 107 to record image data obtained by A / D converting an analog signal based on the electric charge accumulated in the image sensor 103 (step S701). .

  Next, the control unit 106 determines whether or not all projection and imaging of the pattern for dividing the space have been completed (step S702). If the result of this determination is that projection and imaging of all the patterns that divide the space have not been completed, processing returns to step S701. Then, projection of the next pattern, imaging in synchronization with the projection, and recording of image data obtained by the imaging are performed. For example, patterns 217 to 219 shown in FIG. 3A are projected in this order.

  Then, when all the projection and imaging of the pattern for dividing the space are completed, the process proceeds to step S703. The control unit 106 sends a control signal instructing to output a pattern encoded based on the Hadamard matrix to the projection pattern control unit 105. Upon receiving this control signal, the projection pattern control unit 105 controls the projection unit 102 to project a pattern based on the Hadamard matrix onto the measurement object 110. Here, the pattern based on the Hadamard matrix is, for example, 220 to 223 shown in FIG. The projection pattern control unit 105 sends a signal indicating that the projection is completed to the control unit 106 at the timing when the projection is completed.

  Upon receiving this signal, the control unit 106 sends a control signal instructing imaging to the exposure timing control unit 104. Upon receiving this control signal, the exposure timing control unit 104 accumulates charges in the image sensor 103. The exposure timing control unit 104 controls the image sensor 103 and causes the storage unit 107 to record image data obtained by A / D converting an analog signal based on the electric charge accumulated in the image sensor 103 (step S703). .

  Next, the control unit 106 determines whether or not all projection and imaging of the pattern based on the Hadamard matrix have been completed (step S704). As a result of this determination, if all projections and imaging of the pattern based on the Hadamard matrix have not been completed, the process returns to step S703. Then, projection of the next pattern, imaging in synchronization with the projection, and recording of image data obtained by the imaging are performed. For example, patterns 220 to 223 shown in FIG. 3A are projected in this order.

Then, when all the projection and imaging of the pattern based on the Hadamard matrix are completed, the process proceeds to step S705. The pattern recognition unit 108 reads out image data obtained by imaging a pattern based on the Hadamard matrix from the storage unit 107, and converts the read image data into image data in which slit light is shifted (step S705).
Next, the pattern recognition unit 108 determines the position of the image sensor 103 and the position of the projection unit 102 based on the image data obtained by imaging the pattern dividing the space and the image data obtained by shifting the slit light. To obtain pattern position information (step S706).
Next, the three-dimensional shape calculation unit 109 calculates the three-dimensional shape of the measurement target 110 based on the principle of triangulation based on the correspondence between the position of the image sensor 103 and the position of the projection unit 102 obtained by the pattern recognition unit 108. Is calculated (step S707).
Finally, the three-dimensional shape calculation unit 109 outputs information on the calculated three-dimensional shape (step S708).

  As described above, in the present embodiment, first, a plurality of patterns 217 to 219 that divide a space into two are projected sequentially (individually) onto the measurement object 110, and image data of the measurement object 110 at that time is obtained. Next, a plurality of patterns 220 to 223 that are encoded based on the Hadamard example and whose light intensity distribution is determined are sequentially (individually) projected onto the measurement object 110, and the image data of the measurement object 110 at that time is projected. obtain. Next, using the inverse of the Hadamard matrix, the image data obtained by projecting the patterns 220 to 223 encoded based on the Hadamard row example is shifted in the slit position of the pattern composed of a plurality of slit lights. The image data obtained by projecting a plurality of patterns is converted. Next, based on the converted image data and the image data obtained by projecting the patterns 217 to 220 dividing the space into two, the three-dimensional shape of the measurement object 110 is obtained by the principle of triangulation. Therefore, noise included in the image data can be reduced without reducing the amount of light of the pattern, so that the measurement accuracy of the three-dimensional shape of the measurement object 110 can be improved.

  In this embodiment, a pattern having an intensity distribution obtained by inverting the light intensity of an adjacent region is used as the plurality of patterns that divide the space into two. Therefore, the pattern using the Hadamard code can be reduced by one pattern, and it is not necessary to acquire image data of the pattern.

  The above-described embodiments are merely examples of implementation in carrying out the present invention, and the technical scope of the present invention should not be construed in a limited manner. That is, the present invention can be implemented in various forms without departing from the technical idea or the main features thereof.

(Other examples)
The present invention is also realized by executing the following processing. That is, first, software (computer program) for realizing the functions of the above embodiments is supplied to a system or apparatus via a network or various storage media. Then, the computer (or CPU, MPU, etc.) of the system or apparatus reads and executes the computer program.

  102 Projection unit, 111 Information processing device, 112 Imaging unit

Claims (14)

Projection means for projecting light of a plurality of projection patterns having a light intensity distribution onto a measurement object;
Imaging means for imaging the measurement object onto which the projection pattern is projected from a direction different from the light projection direction by the projection means;
Three-dimensional shape calculation means for calculating a three-dimensional shape of the measurement object based on an image captured by the imaging means;
The projection unit projects a plurality of projection patterns whose light intensity distributions are determined based on a Hadamard matrix onto the measurement target.   The projection unit individually projects each of a single or a plurality of projection patterns for dividing a space and a plurality of projection patterns whose light intensity distributions are determined based on a Hadamard matrix onto the measurement target. The three-dimensional measuring apparatus according to claim 1.   The three-dimensional measurement apparatus according to claim 2, wherein the plurality of projection patterns that divide the space include projection patterns in which light intensity distributions are mutually inverted.   4. The tertiary according to claim 3, wherein the three-dimensional shape calculation unit synthesizes an image obtained by imaging the projection pattern in which the light intensity distributions are mutually inverted by the imaging unit. Former measuring device.   The projection pattern in which the light intensity distribution is determined based on the Hadamard matrix is a projection pattern in which the light intensity distribution is determined based on the binary Hadamard matrix. The three-dimensional measuring apparatus according to item 1.   6. The three-dimensional measurement apparatus according to claim 5, wherein the binary Hadamard matrix is a 00-type normal Hadamard matrix or a 00-type correction Hadamard matrix.   5. The tertiary according to claim 1, wherein the plurality of patterns determined based on the Hadamard matrix are patterns determined based on an S matrix created from the Hadamard matrix. Former measuring device. A projection step of projecting light of a plurality of projection patterns having a distribution of light intensity onto a measurement object;
An imaging step of imaging the measurement target on which the projection pattern is projected from a direction different from the light projection direction of the projection step;
A three-dimensional shape calculation step of calculating a three-dimensional shape of the measurement object based on the image captured by the imaging step;
The projecting step projects a plurality of projection patterns whose light intensity distributions are determined based on a Hadamard matrix onto the measurement object.   In the projecting step, each of a single or a plurality of projection patterns for dividing a space and a plurality of projection patterns whose light intensity distributions are determined based on a Hadamard matrix are individually projected onto the measurement target. The three-dimensional measurement method according to claim 8.   The three-dimensional measurement method according to claim 9, wherein the plurality of projection patterns that divide the space include projection patterns in which light intensity distributions are mutually inverted.   11. The tertiary according to claim 10, wherein the three-dimensional shape calculation step combines images obtained by imaging the projection patterns in which the light intensity distributions are mutually inverted by the imaging step. Original measurement method.   The projection pattern in which the light intensity distribution is determined based on the Hadamard matrix is a projection pattern in which the light intensity distribution is determined based on the binary Hadamard matrix. 3. The three-dimensional measurement method according to item 1.   13. The three-dimensional measurement method according to claim 12, wherein the binary Hadamard matrix is a 00-type normal Hadamard matrix or a 00-type correction Hadamard matrix.   The tertiary pattern according to any one of claims 8 to 11, wherein the plurality of patterns determined based on the Hadamard matrix are patterns determined based on an S matrix created from the Hadamard matrix. Original measurement method.

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