KR102578312B1 - Hologram-based object three-dimensional mesurement device and method - Google Patents

Abstract

The present invention relates to a hologram-based three-dimensional object measurement device and method, the device comprising: a two-dimensional image generator that generates a hologram of at least one object to be captured as a two-dimensional image; an image segmentation unit configured to segment an object of interest among the at least one photographed object in the two-dimensional image and extract a two-dimensional reconstructed image of the object of interest; a depth position determination unit that determines a depth position of the two-dimensional reconstructed image; and a 3D measurement unit that performs 3D measurement on the object of interest based on the 2D reconstructed image and the depth position.

Description

Hologram-based object 3D measurement device and method {HOLOGRAM-BASED OBJECT THREE-DIMENSIONAL MESUREMENT DEVICE AND METHOD}

The present invention relates to a hologram-based object 3D measurement technology. More specifically, a hologram-based object that provides 3D measurement and visualization by photographing a hologram of an object and processing it with a numerical method to obtain the depth distribution of the object. It relates to 3D measuring devices.

Conventionally, the method of analyzing a hologram to determine the depth of an object was performed by dividing the hologram into areas, finding the focus position in each area, and extracting the depth position of the area.

However, in this conventional method, when objects corresponding to different depth positions are included in the divided area, the depth position of the object is not accurately derived, and in order to obtain three-dimensional information of the analysis object, all divided areas must be used. There was the inconvenience of having to find each depth location.

Korean Patent No. 10-1304695 (2013.08.30)

One embodiment of the present invention restores a hologram to obtain a two-dimensional image, extracts the in-focus depth position based on all or part of the inner area of the segmented two-dimensional image, and specifies the depth of the segmented area to determine the depth of the object. The objective is to provide a hologram-based 3D measurement device and method that can obtain 3D distribution.

Among embodiments, a hologram-based 3D object measuring apparatus includes: a 2D image generator that generates a hologram of at least one object to be captured as a 2D image; an image segmentation unit configured to segment an object of interest among the at least one photographed object in the two-dimensional image and extract a two-dimensional reconstructed image of the object of interest; a depth position determination unit that determines a depth position of the two-dimensional reconstructed image; and a 3D measurement unit that performs 3D measurement on the object of interest based on the 2D reconstructed image and the depth position.

The two-dimensional image generator can restore the hologram into the two-dimensional image through the equation below.

[Equation]

Here, i _R is the restored holographic two-dimensional image, represents the hologram, and z _r represents the reconstruction distance.

The 2D image generator may adjust z _r to obtain a 2D reconstructed image corresponding to a specific height and set z _r = -z to obtain a focused 2D image.

The image segmentation unit detects the image capacity of the 2D reconstructed image, and when the image capacity is greater than a certain standard, performs down sampling on the 2D reconstructed image and resizes the 2D reconstructed image. )can do.

The image segmentation unit removes noise through blurring based on a Gaussian filter on the 2D reconstructed image or the resized 2D reconstructed image, and performs an unsharp mask on the difference between the original image and the noise-removed image. Edge preservation can be sequentially performed through filtering (unsharp mask filtering) to increase the sharpness of the 2D reconstructed image or the resized 2D reconstructed image, respectively.

The image segmentation unit may perform image binarization on the two-dimensional reconstructed image with increased clarity to specify a region of the object of interest, and may perform morphological processing on the specified object of interest to distinguish the object of interest.

The depth position determination unit may determine the depth position by obtaining a Tamura coefficient of the two-dimensional image and determining a two-dimensional image at a depth where the Tamura coefficient is maximum.

The 3D measurement unit may generate a 3D depth matrix by placing the 2D reconstructed images at corresponding depth positions and measure the object of interest based on the 3D depth matrix.

The disclosed technology can have the following effects. However, since it does not mean that a specific embodiment must include all of the following effects or only the following effects, the scope of rights of the disclosed technology should not be understood as being limited thereby.

A hologram-based 3D object measuring device and method according to an embodiment of the present invention restores a hologram to obtain a 2D image and extracts a focused depth position based on all or part of the inner region of the segmented 2D image. By specifying the depth of the segmented area, the three-dimensional distribution of the object can be obtained.

1 is a diagram explaining the configuration of a hologram-based 3D object measurement system according to the present invention.
FIG. 2 is a diagram explaining the system configuration of the 3D object measurement device shown in FIG. 1.
FIG. 3 is a block diagram illustrating the functional configuration of the 3D object measurement device shown in FIG. 1.
Figure 4 is a flowchart explaining the hologram-based 3D measurement process of an object according to the present invention.
Figure 5 is a diagram explaining holographic photography of an object to be photographed.
Figure 6 is a diagram explaining an embodiment of an erosion operation and an expansion operation.
Figure 7 is a diagram explaining the depth position extraction method according to the present invention.
8A and 8B are diagrams explaining the 3D measurement method according to the present invention.

Since the description of the present invention is only an example for structural or functional explanation, the scope of the present invention should not be construed as limited by the examples described in the text. In other words, since the embodiments can be modified in various ways and can have various forms, the scope of rights of the present invention should be understood to include equivalents that can realize the technical idea. In addition, the purpose or effect presented in the present invention does not mean that a specific embodiment must include all or only such effects, so the scope of the present invention should not be understood as limited thereby.

Meanwhile, the meaning of the terms described in this application should be understood as follows.

Terms such as “first” and “second” are used to distinguish one component from another component, and the scope of rights should not be limited by these terms. For example, a first component may be named a second component, and similarly, the second component may also be named a first component.

When a component is referred to as being “connected” to another component, it should be understood that it may be directly connected to the other component, but that other components may exist in between. On the other hand, when a component is referred to as being “directly connected” to another component, it should be understood that there are no other components in between. Meanwhile, other expressions that describe the relationship between components, such as "between" and "immediately between" or "neighboring" and "directly neighboring" should be interpreted similarly.

Singular expressions should be understood to include plural expressions unless the context clearly indicates otherwise, and terms such as “comprise” or “have” refer to implemented features, numbers, steps, operations, components, parts, or them. It is intended to specify the existence of a combination, and should be understood as not excluding in advance the possibility of the presence or addition of one or more other features, numbers, steps, operations, components, parts, or combinations thereof.

For each step, identification codes (e.g., a, b, c, etc.) are used for convenience of explanation. The identification codes do not explain the order of each step, and each step clearly follows a specific order in context. Unless specified, events may occur differently from the specified order. That is, each step may occur in the same order as specified, may be performed substantially simultaneously, or may be performed in the opposite order.

The present invention can be implemented as computer-readable code on a computer-readable recording medium, and the computer-readable recording medium includes all types of recording devices that store data that can be read by a computer system. . Examples of computer-readable recording media include ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage device, HDD, and SSD. Additionally, the computer-readable recording medium can be distributed across computer systems connected to a network, so that computer-readable code can be stored and executed in a distributed manner.

All terms used herein, unless otherwise defined, have the same meaning as commonly understood by a person of ordinary skill in the field to which the present invention pertains. Terms defined in commonly used dictionaries should be interpreted as consistent with the meaning they have in the context of the related technology, and cannot be interpreted as having an ideal or excessively formal meaning unless clearly defined in the present application.

1 is a diagram explaining the configuration of a hologram-based 3D object measurement system according to the present invention.

Referring to FIG. 1 , the hologram-based 3D object measurement system 100 may include a hologram camera 110, a 3D object measurement device 130, and a database 150.

The hologram camera 110 may correspond to a device that can capture a hologram of an inspection object located on an objective plate. The hologram camera 110 may be connected to the 3D object measurement device 130 through a network, and a plurality of hologram cameras 110 may be simultaneously connected to the 3D object measurement device 130.

In one embodiment, the hologram camera 110 may be included and implemented as a component of the object 3D measurement device 130. In this case, the hologram camera 110 is an independent device that performs the operation of photographing a hologram of the object. It may correspond to a module.

In one embodiment, the holographic camera 110 includes a light source that generates electromagnetic waves, a splitting means that splits the electromagnetic waves, a scanning means that scans the object using an interference beam formed by the split electromagnetic waves, and reflection, fluorescence, or transmission from the object. It may include light detection means for detecting the beam.

The light source may include various means such as a laser generator capable of generating electromagnetic waves, a light emitting diode (LED), and a beam with low coherence such as heliogen light with a short coherence length.

The splitting means may split an electromagnetic wave generated from a light source, for example, a laser beam, into a first beam and a second beam. In one embodiment, the splitting means may include an optical fiber coupler, a beam splitter, and a geometric phase lens, and transmits the beam to the outside by guiding free space. In addition, it can be divided into a first beam and a second beam on the co-axis using a means that can split the beam on the co-axis (in-line), such as the geometric phase lens.

The scanning means may scan an object to be photographed using an interference beam (or interference pattern) formed by divided electromagnetic waves. The scanning means may correspond to a mirror scanner, but is not necessarily limited thereto, and may be replaced with various known scanning means. For example, the scanning means may scan the object by moving a Fresnel zone plate across the object. In this case, the scanning means can adjust the scanning position according to the control signal. Additionally, the scanning means can place the object to be photographed on the objective plate and scan the object by horizontally moving the object plate.

The light detection means can detect the beam and convert it into a current signal. In this case, the light detection means may generate a current according to the intensity of the detected beam. The light detection means may be implemented using a photodiode, but is not necessarily limited thereto, and may include various light detection means such as a photo-multiplier tube. Additionally, the light detection means may be implemented by including a concentrator that focuses the beam reflected, fluorescent, or transmitted from the object to be photographed.

The 3D measurement device 130 may be implemented as a server corresponding to a computer or program that can measure an object in 3D by photographing a hologram of the object and processing it using a numerical method to obtain the depth distribution of the object. The object 3D measurement device 130 can be wirelessly connected to an external system (not shown in FIG. 1) that performs an independent operation through Bluetooth, WiFi, a communication network, etc., and can exchange data with the external system through the network. there is.

In one embodiment, the object 3D measurement device 130 may store information necessary for the automatic optical inspection process in conjunction with the database 150. Meanwhile, unlike FIG. 1, the object 3D measurement device 130 may be implemented by including a database 150 therein.

The database 150 may correspond to a storage device that stores various information required in the process of performing the hologram-based 3D measurement method for an object according to the present invention. The database 150 can store information about the hologram of the object obtained from the hologram camera 110, and can store information about the two-dimensional image and depth position of the object, but is not necessarily limited thereto, and can be used for three-dimensional measurement of the object. The device 130 can store information collected or processed in various forms in the process of measuring the object in three dimensions by acquiring the depth distribution of the object.

FIG. 2 is a diagram illustrating the system configuration of the 3D object measurement device shown in FIG. 1.

Referring to FIG. 2 , the 3D object measurement device 130 may include a processor 210, a memory 230, a user input/output unit 250, and a network input/output unit 270.

The processor 210 can execute a hologram-based object 3D measurement procedure according to an embodiment of the present invention, manage the memory 230 that is read or written in this process, and volatile memory in the memory 230. You can schedule the synchronization time between and non-volatile memory. The processor 210 can control the overall operation of the object 3D measurement device 130 and is electrically connected to the memory 230, the user input/output unit 250, and the network input/output unit 270 to facilitate data flow between them. You can control it. The processor 210 may be implemented as a central processing unit (CPU) of the object 3D measurement device 130.

The memory 230 may be implemented as a non-volatile memory such as a solid state disk (SSD) or a hard disk drive (HDD) and may include an auxiliary memory device used to store all data required for the object 3D measurement device 130. and may include a main memory implemented as volatile memory such as RAM (Random Access Memory). Additionally, the memory 230 can store a set of instructions for executing the hologram-based 3D measurement method of an object according to the present invention by being executed by the electrically connected processor 210.

The user input/output unit 250 includes an environment for receiving user input and an environment for outputting specific information to the user, and includes an input adapter such as, for example, a touch pad, a touch screen, an on-screen keyboard, or a pointing device. It may include an output device including a device and an adapter such as a monitor or touch screen. In one embodiment, the user input/output unit 250 may correspond to a computing device connected through a remote connection, and in such case, the object 3D measurement device 130 may be performed as an independent server.

The network input/output unit 270 provides a communication environment for connection with the hologram camera 110 or an external system through a network, for example, LAN (Local Area Network), MAN (Metropolitan Area Network), WAN (Wide Area Network) Network) and VAN (Value Added Network) may include adapters for communication. Additionally, the network input/output unit 270 may be implemented to provide short-range communication functions such as WiFi and Bluetooth or wireless communication functions of 4G or higher for wireless transmission of data.

FIG. 3 is a block diagram illustrating the functional configuration of the 3D object measurement device shown in FIG. 1.

Referring to FIG. 3, the three-dimensional object measurement device 130 includes a two-dimensional image generator 310, an image segmentation unit 330, a depth position determination unit 350, a three-dimensional measurement unit 370, and a control unit 390. may include.

The 2D image generator 310 may generate a hologram of at least one object to be captured as a 2D image. Here, the photographing object may correspond to an object that is the target of 3D measurement. The two-dimensional image generator 310 can capture a hologram of the object to be photographed on the objective plate in conjunction with the hologram camera 110. That is, the two-dimensional image generator 310 can receive a hologram captured by the hologram camera 110 and store it in the database 150, and read the hologram stored in the database 150 to create a two-dimensional image based on it. can be created. Meanwhile, the two-dimensional image generator 310 may be implemented by including an independent module that operates in conjunction with the hologram camera 110, and the module generates a hologram of the object to be photographed on the objective plate through the hologram camera 110. It can be collected. Hereinafter, the module will be referred to as a hologram imaging module, and specific operations will be described.

More specifically, the hologram photographing module can photograph a hologram of an object to be photographed using a hologram photographing method based on optical scanning. In one embodiment, the hologram photographing module may generate a complex hologram as a result of photographing a photographing object.

Additionally, the hologram photographing module can photograph a hologram of the photographing object 550 using the hologram camera 510 in the configuration shown in FIG. 5 . At this time, the hologram camera 510 may be implemented to enable hologram photography based on optical scanning. Meanwhile, in FIG. 5, the holographic camera 510 is shown as detecting a beam reflected or fluorescent from the object 550, but the light transmits from the object 550 by placing the photo detector at the bottom of the objective surface 530. Of course, it can be implemented to detect the beam. In this case, it is preferable that the objective surface 530 is made of transparent glass or that the body of the photographing object 550 is open.

The hologram imaging module can express the hologram captured through the hologram camera 510 as shown in the following equations 1 to 5.

[Equation 1]

Here, O(x ₀ ,y ₀ ;z) is the 3-dimensional distribution of the reflectance of the object and is the 3-dimensional image of the object, is a convolution operation. And, (x,y) is the scan position of the scan beam designated by the scanning means, and z is the depth position of the object and corresponds to the distance from the focus of the spherical wave to the object.

[Equation 2]

Here, d is the distance between the focus of the first spherical wave and the focus of the second spherical wave. Holograms can correct distortion due to reduction and enlargement by adjusting d. D can be adjusted by changing the position and focal length of the lens according to the imaging law of the lens.

[Equation 3]

[Equation 4]

[Equation 5]

Here, M _img is the reduction or enlargement ratio of the image by the first lens when imaging the pattern of the surface of the polarization-sensitive lens (geometric phase lens) as the surface of the object area, and z _img is the distance from the focus position of the second spherical wave to the object. The distance, 2M ² _img f _gp , is the distance between each focus of the first and second adjusted spherical waves.

In one embodiment, the 2D image generator 310 may restore the hologram into a 2D image using Equation 6 below. That is, the hologram captured by the hologram camera 110 can be restored into a two-dimensional image through a restoration process.

[Equation 6]

Here, i _R is the restored hologram 2D image, represents a hologram expressed as shown in Equations 1 to 5 above, and z _r represents the restoration distance. In one embodiment, the 2D image generator 310 may obtain a 2D reconstructed image corresponding to a specific height by adjusting z _r in Equation 6 above. Additionally, the 2D image generator 310 may obtain a focused 2D image by setting z _r = -z. The hologram captured through the hologram camera 110 may be segmented through a predetermined process and used to extract depth information of the corresponding area or for 3D measurement. Meanwhile, a segmentation operation may be performed based on the 2D reconstructed image to be in focus generated by the 2D image generator 310.

The image segmentation unit 330 may extract a 2D restored image of the object of interest by segmenting the object of interest among at least one photographed object in the 2D image of the hologram. A two-dimensional image may include an object to be photographed, and the number of objects to be photographed may be one or multiple objects depending on the case. The segmentation operation for a 2D image may correspond to an operation of generating an independent 2D restored image for each object, and an independent 2D restored image may be generated for each object.

That is, the image segmentation unit 330 can segment a two-dimensional image of a hologram containing a plurality of objects to be captured, generate an independent two-dimensional reconstructed image for each object, and select and determine an object of interest from among the plurality of objects. . Meanwhile, one 2D restored image may be generated for one object of interest, but the present invention is not necessarily limited thereto, and of course, a plurality of 2D restored images may be generated for one object of interest.

In one embodiment, the image segmentation unit 330 detects the image capacity of the 2D reconstructed image, and when the image capacity is greater than a certain standard, performs down sampling on the 2D reconstructed image to obtain a 2D reconstructed image. You can resize. That is, if the image capacity of the 2D reconstructed image is too large, the image segmentation unit 330 may perform a pre-processing operation to reduce the image capacity. The image segmentation unit 330 may set a threshold for image capacity in advance for a preprocessing operation.

Additionally, the image segmentation unit 330 may use down sampling or convolution processing techniques as a preprocessing operation to reduce image capacity. First, in the case of downsampling, image capacity can be reduced through maximum value pooling. For example, if the input image is 4×4, the image segmentation unit 330 may divide the input image into regions having a size of 2×2, and select the largest value for each region to create a 2×2 size. An output image having can be generated.

Additionally, in the case of convolution processing, image capacity can be reduced through an average filter. That is, the image segmentation unit 330 can generate an output image by moving the filter within the input image and calculating an average value for the area overlapping with the filter. For example, in the case of a filter with a size of 3×3, if the total sum of values in the area overlapping with the filter is 27, the output value corresponding to the position of the filter may be determined as 27/9 = 3.

In one embodiment, the image segmentation unit 330 removes noise through blurring based on a Gaussian filter on a 2D reconstructed image or a resized 2D reconstructed image, and performs noise removal between the original image and the noise-removed image. Edge preservation can be sequentially performed through unsharp mask filtering on differences to increase the sharpness of the 2D restored image or the resized 2D restored image, respectively.

More specifically, the image segmentation unit 330 can perform noise filtering through Gaussian filter-based blurring on a 2-dimensional reconstructed image or a resized 2-dimensional reconstructed image. . Here, blurring may correspond to an operation of removing high-frequency components of the outline portion of the image through low-pass filtering. The high-frequency component within the image may correspond to an image component with a relatively large change rate of pixel value, and the image segmentation unit 330 may use a Gaussian filter for blurring. A Gaussian filter can be created based on a mathematically defined Gaussian function, and the amount of high and low frequencies according to noise removal can be adjusted through σ of the Gaussian function. In other words, the smaller the σ value, the less low-frequency components can be passed, and the larger the σ value, the more low-frequency components can be passed. In one embodiment, when the level of noise is severe, the image segmentation unit 330 may maximize the effect of blurring by applying a median filter in advance at a stage before performing blurring.

Additionally, the image segmentation unit 330 may perform edge preservation through unsharp mask filtering using the difference between the original image and the noise-removed image. Here, edge preservation may correspond to an image enhancement operation that sharpens the outline portion of the image through sharpening. At this time, sharpening, as opposed to blurring, can increase the contrast effect by emphasizing components corresponding to the high frequencies of the image, and can improve a blurry image to create a clear image.

As a result, the image segmentation unit 330 can obtain a noise-removed image through blurring based on the original image and obtain a function regarding the difference between the original image and the noise-removed image. The image segmentation unit 330 can ultimately obtain an image with increased clarity as a result of adding the corresponding function to the original image. Meanwhile, the image segmentation unit 330 may simultaneously perform noise removal and edge preservation through a bilateral filter, if necessary.

In one embodiment, the image segmentation unit 330 performs image binarization on a two-dimensional reconstructed image with increased clarity to specify the area of the object of interest, and performs morphological processing on the specified object of interest to distinguish the object of interest. can do.

More specifically, the image segmentation unit 330 sets a specific threshold and classifies the background and target object in the image through image binarization, which binarizes each pixel in the image into black and white based on the threshold. You can. In addition, the image segmentation unit 330 can specify the area of the object of interest by applying an optimal threshold value to each pixel after comparing it with surrounding values using an adaptive binarization technique that is robust to the shooting environment.

Afterwards, the image segmentation unit 330 performs morphology-based erosion and dilation operations on the binarized and specified area of the object of interest to remove remaining noise and define the area of the object. It can be firmed (see Figure 6).

For example, in figure (a) of FIG. 6, the erosion operation may correspond to an operation that cuts off the image (i.e., video), and a structuring element kernel consisting of 0 and 1 (610) ) can be applied. Additionally, the structuring element kernel 610 may be classified into a square, oval, cross, etc. depending on the shape filled with 1s. The image segmentation unit 330 applies the structuring element kernel 610 to the image and changes the value of the pixel to 0 if the area filled with 1 of the structuring element kernel 610 is not completely included at each pixel location. Erosion operations can be performed.

Additionally, in figure (b) of FIG. 6, the dilation operation may correspond to an operation that expands the image and may operate in a manner opposite to the erosion operation using the structuring element kernel 610. That is, the image segmentation unit 330 applies the structuring element kernel 610 to the image and changes the value of the pixel to 1 if the area filled with 1 of the structuring element kernel 610 is not completely included at each pixel location. The expansion operation can be performed using this method.

The depth position determination unit 350 may determine the depth position of the 2D reconstructed image of the object of interest. In order to extract the depth position from the segmented area, the depth position determination unit 350 may determine whether the 2D reconstructed image of the corresponding area is a focus image or not according to a predetermined standard.

In one embodiment, the depth position determination unit 350 may determine the depth position by obtaining the Tamura coefficient of the 2D reconstructed image and determining the 2D reconstructed image at the depth with the maximum Tamura coefficient. That is, the depth position determination unit 350 may determine the 2D reconstructed image based on the Tamura coefficient. At this time, the Tamura coefficient may correspond to one of the sharpness functions used in the autofocus algorithm and can be expressed as Equation 7 below.

[Equation 7]

Here, C is the Tamura coefficient, is the average value (mean) of the 2D reconstructed image, is the standard deviation.

The 3D measurement unit 370 may perform 3D measurement on the object of interest based on the 2D reconstructed image and depth position. The 3D measurement operation can be performed through the process of segmenting the hologram, collecting depth information of the segmented holograms, and then matching the depth information with the area of the segmented hologram. That is, the 3D measurement unit 370 can place the 2D restored images of segmented holograms at the corresponding depth and then integrate them to derive overall 3D information.

In one embodiment, the 3D measurement unit 370 may generate a 3D depth matrix by placing 2D reconstructed images at corresponding depth positions and measure the object of interest based on the 3D depth matrix. The 3D depth matrix may include a matching relationship between the depth position and the 2D reconstructed image of the hologram. The 3D measurement method is explained in more detail in FIG. 8.

The control unit 390 controls the overall operation of the object 3D measurement device 130 and includes a 2D image generator 310, an image segmentation unit 330, a depth position determination unit 350, and a 3D measurement unit 370. You can manage control flow or data flow between

Figure 4 is a flowchart explaining the hologram-based 3D measurement process of an object according to the present invention.

Referring to FIG. 4 , the 3D object measurement device 130 may sequentially perform a plurality of steps to process the hologram-based 3D object measurement method according to the present invention. More specifically, the 3D object measuring device 130 may generate a hologram of at least one photographed object as a 2D image through the 2D image generator 310 (step S410).

In addition, the 3D object measurement device 130 may segment an object of interest among at least one photographed object in a 2D image through the image segmentation unit 330 and extract a 2D restored image of the object of interest. (Step S430). The three-dimensional object measurement device 130 can determine the depth position of the two-dimensional reconstructed image through the depth position determination unit 350 (step S450), and determine the two-dimensional restored image and depth position through the three-dimensional measurement unit 370. Based on this, 3D measurement can be performed on the object of interest (step S470).

Figure 7 is a diagram explaining the depth position extraction method according to the present invention.

Referring to FIG. 7 , the 3D object measurement device 130 may determine the depth position of the 2D reconstructed image through the depth position determination unit 350. To this end, the object 3D measurement device 130 may acquire a hologram of at least one photographed object through the hologram camera 110 and generate a two-dimensional image of the hologram (Figures (a) and (b) )).

Afterwards, the 3D object measurement device 130 can perform segmentation centered on the object of interest in the hologram, and generate a 2D restored image of the segmented hologram through segmentation (Figure ⓒ). Finally, the object 3D measurement device 130 can calculate the Tamura coefficient (C) based on the 2D reconstructed image and determine the depth position (z ₁ ) where the Tamura coefficient has the maximum value (Figure ( d)).

The object 3D measurement device 130 may generate a plurality of segmented holograms by segmenting a two-dimensional image of the hologram, and may use a focus metric (e.g., The depth position can be independently determined based on the Tamura coefficient).

Additionally, the 3D object measurement device 130 may determine the depth position in each region based on the focus metric for at least one region of the 2D reconstructed image, and determine the depth position in each region based on the depth position in each region. The depth position for the restored image can be determined.

8A and 8B are diagrams explaining the 3D measurement method according to the present invention.

Referring to FIGS. 8A and 8B , the 3D object measurement device 130 may generate a hologram for a photographing object and perform segmentation. Thereafter, the object 3D measurement device 130 may extract the depth of each segmented hologram through Tamura coefficient (Tamura Coeffiecient). Next, the object 3D measurement device 130 may match the extracted depth information with the area of the segmented hologram to obtain a 2D restored image of the segmented hologram corresponding to the depth. Finally, the 3D object measurement device 130 can create a 3D matrix (i.e., 3D depth matrix) by combining the 2D restored images with the restored depth, and based on this, create a 3D matrix for the photographed objects. Measurements can be performed.

In addition, the object 3D measurement device 130 is capable of converting the relative depth into actual physical depth information by calibrating the extracted depth information based on a well-known measuring instrument, through which all 3D information of the object can be obtained. By doing so, three-dimensional analysis of the object can be performed.

In FIG. 8A, the object 3D measurement device 130 can generate segmented holograms for objects 1 and 2, respectively, and Z ₁ and Z ₂ , where the Tamura coefficients of each segmented hologram are maximized, are used as depth positions, respectively. It can be calculated.

In FIG. 8B, the object 3D measurement device 130 may construct a 3D matrix regarding the object by arranging the 2D restored image of the segmented hologram according to the depth position. At this time, the depth position may be defined based on the direction perpendicular to the xy plane, that is, the Z _r direction, and the object 3D measurement device 130 generates the corresponding two-dimensional restored images at the Z ₁ and Z ₂ positions on the Z _r axis. It can be placed.

The 3D object measuring device 130 according to the present invention can perform 3D measurement of photographed objects by arranging 2D reconstructed images at various depth positions. In addition, the 3D object measuring device 130 can select an object of interest from among photographed objects, segment a plurality of 2D restored images for the object of interest, and use the segmented 2D restored images to determine the object of interest. 3D measurement can be optionally performed.

Although the present invention has been described above with reference to preferred embodiments, those skilled in the art may make various modifications and changes to the present invention without departing from the spirit and scope of the present invention as set forth in the claims below. You will understand that you can do it.

100: Hologram-based object 3D measurement system
110: Hologram camera 130: 3D measurement device for object
150: database
510: Hologram camera 530: Objective surface
550: Shooting object
610: Structured element kernel

Claims (8)

a two-dimensional image generator that generates a hologram of at least one object to be photographed and generates the hologram as a two-dimensional image;
In the process of extracting an independent 2D reconstructed image for each object of interest by segmenting an object of interest among the at least one photographed object in the 2D image, the image capacity of the 2D restored image is detected and the image capacity is obtained. If it exceeds this specific standard, down sampling is performed on the 2D reconstructed image to resize the 2D reconstructed image, and a Gaussian filter based on the resized 2D reconstructed image is used. Increases the clarity of the resized 2D restored image by sequentially performing edge preservation through noise removal through blurring and unsharp mask filtering on the difference between the original image and the noise-removed image. perform image binarization on the resized two-dimensional reconstructed image with increased clarity to specify the area of the object of interest, and then perform morphology-based erosion and dilation operations on the specified object of interest. an image segmentation unit that distinguishes the object of interest;
a depth position determination unit that obtains a Tamura coefficient of the two-dimensional reconstructed image and determines a depth at which the Tamura coefficient is maximum for each object of interest as a depth position; and
For each object of interest, the corresponding 2-dimensional reconstructed image is arranged according to the depth position to generate a 3-dimensional depth matrix regarding the matching relationship between the depth position and the 2-dimensional restored image of the hologram, and the interest is based on the 3-dimensional depth matrix. Includes a 3D measurement unit that performs 3D measurement on the object,
In the process of restoring the hologram to the two-dimensional image through the equation below, the two-dimensional image generator adjusts z _r to obtain a two-dimensional restored image corresponding to a specific height and sets z _r = -z. A hologram-based three-dimensional object measurement device characterized by acquiring a focused two-dimensional image.
[Equation]


(Here, i _R is the restored holographic two-dimensional image, represents the hologram, z _r represents the reconstruction distance)
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