KR101659443B1 - High resolution particle image velocimetry technique using combined cross corrleation and optical flow method - Google Patents

High resolution particle image velocimetry technique using combined cross corrleation and optical flow method Download PDF

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KR101659443B1
KR101659443B1 KR1020150090302A KR20150090302A KR101659443B1 KR 101659443 B1 KR101659443 B1 KR 101659443B1 KR 1020150090302 A KR1020150090302 A KR 1020150090302A KR 20150090302 A KR20150090302 A KR 20150090302A KR 101659443 B1 KR101659443 B1 KR 101659443B1
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South Korea
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tracking
image
particle
particles
displacement
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KR1020150090302A
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Korean (ko)
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김응수
송민섭
박소현
박민영
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서울대학교산학협력단
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
    • G01P5/00—Measuring speed of fluids, e.g. of air stream; Measuring speed of bodies relative to fluids, e.g. of ship, of aircraft
    • G01P5/18—Measuring speed of fluids, e.g. of air stream; Measuring speed of bodies relative to fluids, e.g. of ship, of aircraft by measuring the time taken to traverse a fixed distance
    • G01P5/22—Measuring speed of fluids, e.g. of air stream; Measuring speed of bodies relative to fluids, e.g. of ship, of aircraft by measuring the time taken to traverse a fixed distance using auto-correlation or cross-correlation detection means

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  • Engineering & Computer Science (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Image Analysis (AREA)

Abstract

According to a first embodiment of the present invention, a particle tracking method is capable of analyzing the displacement of a particle by photographing a flow field, including at least one tracking particle able to be identified through multiple photographed images, at regular time intervals. The method includes: a step of including at least one tracking particle, and dividing each of the images into pixel areas by unit of an analysis area which is a pixel area of a regular size to track the included tracking particle; a step of calculating a correlation coefficient by unit of the analysis area for each of the images based on the tracking particle included in each analysis area in a mutual position between the images; and a step of calculating the average velocity distribution of the tracking particle, included in each analysis area, between the images based on the calculated correlation coefficient.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention [0001] The present invention relates to a method and apparatus for measuring a flow velocity of a high-precision particle image using a correlation coefficient and an optical flow integration method,

The present invention relates to a method and an apparatus for measuring a high-precision particle image flow rate using a correlation coefficient and an optical flow integration method, and more particularly, Estimating the approximate velocity distribution of the particles through an existing correlation coefficient analysis method, transforming the captured second image based on the estimated velocity distribution, and calculating the sensitivity for the image based on the transformed second image and the first image To a method for measuring velocity distribution of particles in a flow field by reapplication of a high optical flow technique.

Image PIV (PIV) is an optical measurement technique that can simultaneously measure the velocity components of two- and three-dimensional all-propane fields. It is a technique to analyze the flow field using images obtained by inserting tracking particles into the flow field and applying appropriate illumination.

Conventional image particle velocimetry (PIV) uses a method to calculate the correlation coefficient between two image frames and to analyze the velocity of a predetermined interrogation area.

This method is highly reliable in analyzing the velocity distribution of particles in general, but requires an analysis area of more than a certain size, so there is a limit to the resolution of the space and it is necessary to observe the movement of particles over a certain distance between two image frames Do.

Therefore, in order to analyze the cross correlation coefficient, it is necessary to set the analysis area above a certain size. Therefore, there is a problem that the spatial resolution is limited in analyzing the particle velocity distribution. In order to measure the velocity distribution of the particle accurately, And it is necessary to set the size of the analysis area. If the above condition is not satisfied, there is a problem that the accuracy of the analysis of the velocity distribution of the particles is poor.

In this regard, Korean Patent Laid-Open Publication No. 10-2009-0114125 relates to a multi-plane particle image flow velocity measuring apparatus for observing a flow area of a large area and acquiring a flow field, A plurality of cameras each for acquiring an image, a horizontal guide for mounting the camera to adjust the horizontal position of the camera, and a vertical guide for adjusting the vertical position of the horizontal guide by mounting the horizontal guide. However, the techniques disclosed in the above patent documents do not solve the above-described problems.

Therefore, a technique for solving the above-described problems is required.

On the other hand, the background art described above is technical information acquired by the inventor for the derivation of the present invention or obtained in the derivation process of the present invention, and can not necessarily be a known technology disclosed to the general public before the application of the present invention .

An embodiment of the present invention has an object to prevent degradation of spatial resolution by setting an analysis area of a predetermined size or larger in order to calculate a displacement and a velocity corresponding to a position of a region by analyzing cross correlation coefficients.

In addition, one embodiment of the present invention is a method of converting a photographed frame using displacement and velocity distribution of a low-resolution particle calculated using a cross-correlation coefficient, thereby realizing high spatial resolution and accurate velocity distribution And the like.

According to a first aspect of the present invention, there is provided a method for measuring a displacement of a particle by photographing a flow field including at least one tracking particle that can be identified through a plurality of photographed images at a predetermined time interval, The method comprising the steps of: determining a pixel area of each image with respect to the plurality of images in a unit of an analysis area, which is a pixel area of a predetermined size, which includes at least one of the at least one tracking particle, Calculating a correlation coefficient on an analysis domain basis for each of the plurality of images based on the tracking particles included in each of the analysis regions of mutually corresponding positions between the plurality of images, , An average velocity fraction of the tracking particles contained in each interpretation region between the plurality of images A may include the step of calculating.

According to a second aspect of the present invention, there is provided a particle tracking apparatus for analyzing a displacement of a particle by photographing a flow field including at least one tracking particle capable of being identified through a plurality of photographed images at regular time intervals, A particle photographing unit that sequentially photographs a flow field including particles at a predetermined time interval and a particle photographing unit that includes at least one of the at least one tracking particle, Calculating a correlation coefficient for each of the plurality of images on the basis of the tracing particles included in each of the analysis regions of mutually corresponding positions between the plurality of images, for each of the plurality of images And based on the calculated correlation coefficients, Calculating an average of the velocity distribution of the particles contained trace cross-correlation calculations may include a.

According to one embodiment of the present invention, the analysis area is analyzed by analyzing the cross-correlation coefficients to set an analysis area having a predetermined size or larger to calculate a displacement and a velocity corresponding to the position of the area, It is possible to prevent degradation of resolution.

In addition, according to any one of the tasks of the present invention, the optical flow technique transforms photographed frames using displacement and velocity distributions of low-resolution particles calculated using cross-correlation coefficients, thereby achieving high spatial resolution and accuracy It is possible to obtain the velocity distribution of the particles having the particle size distribution.

The effects obtained by the present invention are not limited to the above-mentioned effects, and other effects not mentioned can be clearly understood by those skilled in the art from the following description will be.

1 is a block diagram of a particle tracking apparatus according to an embodiment of the present invention.
2 is a flowchart illustrating a particle tracking method according to an embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings, which will be readily apparent to those skilled in the art. The present invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. In order to clearly illustrate the present invention, parts not related to the description are omitted, and similar parts are denoted by like reference characters throughout the specification.

Throughout the specification, when a part is referred to as being "connected" to another part, it includes not only "directly connected" but also "electrically connected" with another part in between . Also, when an element is referred to as "comprising ", it means that it can include other elements as well, without departing from the other elements unless specifically stated otherwise.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, the present invention will be described in detail with reference to the accompanying drawings.

Before describing this, we first define the meaning of the terms used below.

In the present invention, the 'tracking particle' is a particle capable of scattering light of a light source and being photographed through a camera, and is mixed with a fluid to move the particle so that the particle flow can be grasped in the fluid field.

In order to calculate the displacement of the tracking particle between consecutive two frames with a short interval of 'short interval', 'cross correlation method' And finding the displacement of the analysis region having the maximum correlation coefficient.

The network N may be a local area network (LAN), a wide area network (WAN), a value added network (VAN), a personal area network (PAN) mobile radio communication network, Wibro (Wireless Broadband Internet), Mobile WiMAX, HSDPA (High Speed Downlink Packet Access) or satellite communication network.

The particle tracking device 10 may be implemented as a computer, a portable terminal, a television, a wearable device, or the like, which can be connected to a remote server through a network N or connected to other terminals and servers. Here, the computer includes, for example, a notebook computer, a desktop computer, a laptop computer, and the like, each of which is equipped with a web browser (WEB Browser), and the portable terminal may be a wireless communication device , Personal Communication System (PCS), Personal Digital Cellular (PDC), Personal Handyphone System (PHS), Personal Digital Assistant (PDA), Global System for Mobile communications (GSM), International Mobile Telecommunication (IMT) (W-CDMA), Wibro (Wireless Broadband Internet), Smart Phone, Mobile WiMAX (Mobile Worldwide Interoperability for Microwave Access) (Handheld) based wireless communication device. In addition, the television may include an Internet Protocol Television (IPTV), an Internet television (TV), a terrestrial TV, a cable TV, and the like. Further, the wearable device is an information processing device of a type that can be directly worn on a human body, for example, a watch, a glasses, an accessory, a garment, shoes, or the like, and can be connected to a remote server via a network, Lt; / RTI >

FIG. 1 is a block diagram for explaining a particle tracking apparatus 10 according to an embodiment of the present invention. The particle tracking apparatus 10 will be described in detail with reference to FIG.

First, the particle tracking apparatus 10 may include a particle photographing unit 110. The particle photographing unit 110 may sequentially photograph the flow field including one or more tracking particles that can be identified through the photographed image at regular time intervals.

That is, the particle photographing unit 110 can emit a laser beam or the like as a light source in a flow field in which the tracking particles are mixed, and can shoot light scattered by the tracking particles through the camera at regular time intervals.

The particle tracking apparatus 10 may include a cross-correlation calculation unit 120. The cross-correlation calculating unit 120 may calculate the displacement of the tracking particle using the cross-correlation coefficient based on the image taken at a predetermined time interval in the particle photographing unit 110

In other words, the local velocity of the flow field can be obtained by knowing the straight line distance and direction in which the tracking particles passing through a certain point move during the minute time interval.

For this purpose, the cross-correlation calculation unit 120 sets an analysis region, which is a pixel window of a fixed size including the tracking particles, in two shot images measured according to time intervals, And the displacement and velocity of the tracking particle corresponding to the position of the analysis region can be calculated.

For example, the cross-correlation calculation unit 120 may set an analysis region of a predetermined pixel size including one or more tracking particles in a first one of a plurality of sequentially captured images.

Then, based on the pixel values of the analyzed regions of the first image, the cross-correlation calculating section 120 calculates the cross-correlation values based on the pixel values of the analyzed regions of the first image in the second image photographed after a predetermined time interval from the first image The area can be specified.

For example, the cross-correlation calculation unit 120 can calculate the correlation coefficient between the analysis regions between the first image and the second image, and can select the region of the second image having the maximum correlation coefficient.

At this time, the cross-correlation calculating unit 120 may search the second image region at intervals of at least one pixel to search the region of the second image having the maximum correlation coefficient.

The cross correlation calculation unit 120 then calculates the average velocity distribution of one or more tracking particles included in the analysis region using the position of the tracking particles in the selected region in the second frame and the difference in position of the tracking particles in the first image .

Thus, by performing a cross-correlation method on the entire captured image of the interpretation region set in the image, the displacement and velocity of all the tracking particles included in the captured image can be calculated.

The particle tracking device 10 may include a frame transformer 130. The frame conversion unit 130 generates a conversion frame in which the position of each tracking particle is corrected for one or more tracking particles in the second image using the displacement of one or more tracking particles calculated by the cross correlation calculation unit 120 can do.

For example, the frame transformer 130 may change the position of the one or more tracking particles in the second image inversely by the displacement of each tracking particle calculated for one or more tracking particles in the second image.

By doing so, it is possible to generate a transformed transformed frame such that the second image is similar to the first image, and the displacement of the tracing particle between the first image and the transformed frame becomes very small.

And the velocity distribution calculation unit 140 may calculate the displacement of one or more tracking particles based on the positions of the one or more tracking particles in each of the first image and the conversion frame.

For example, the velocity distribution calculation unit 140 can calculate the displacement by searching the position in the transformation frame for each of the one or more tracking particles included in the first image using the optical flow method.

Then, the velocity distribution calculation unit 140 can generate a velocity distribution having a high spatial resolution based on displacements calculated for each pixel between the first image and the transform frame, for example, displacements of one pixel or less.

In this way, it is possible to obtain a spatial high-resolution velocity distribution that can be applied to all fields utilizing fluid, and precise measurement can be performed by applying this technique to the minute motion that was difficult to measure previously.

In addition to the fluid field, it can also be used as a measurement technique for multi-dimensionally measuring the shape and shape of solid structures and distortions, and precise measurement of very minute changes is possible

Also, it can be used as a measurement method for measuring the spatial density distribution of air, temperature distribution, and the like.

The particle tracking method according to the embodiment shown in FIG. 2 includes the steps of the particle tracking apparatus 10 shown in FIG. 1 and being processed in a time-series manner. Therefore, even if omitted from the following description, the above description of the particle tracking apparatus 10 shown in FIG. 1 can be applied to the particle tracking method according to the embodiment shown in FIG.

First, the particle tracking apparatus 10 may sequentially photograph a flow field including one or more tracking particles that can be identified through the photographed image at a predetermined time interval, in order to analyze the displacement and velocity of the particles in the flow field (S2000) .

Then, the particle tracking device 10 can calculate the displacement of the tracking particle between the two images through a cross-correlation method between the two images, based on the captured plurality of images (S2001).

To this end, the particle tracking device 10 can set an interpretation area of a certain pixel size including the one or more tracking particles in a first one of a plurality of sequentially photographed images.

And the particle tracking device 10 is configured to calculate a difference between a pixel value of an interpretation area of the first image in a second image photographed after a certain time interval from the first image, And the displacement of the corresponding tracking particle between one or more tracking particles included in the analysis region of the first image and one or more tracking particles included in the region specified in the second image can be calculated.

Based on the displacement of the tracking particles calculated as described above, the particle tracking device 10 can generate a low-velocity velocity distribution based on the displacement of the calculated tracking particles.

Then, the particle tracking apparatus 10 can convert the image using the generated low-resolution velocity distribution (S2002).

That is, the particle tracking device 10 may use the computed displacements of one or more tracking particles to generate a transformation frame in which the position of each tracking particle is corrected for one or more tracking particles in the second image.

For example, the particle tracking device 10 may be configured to move the position of one or more tracking particles in the second image backward by the displacement of each tracking particle calculated for one or more tracking particles in the second image, A transformation frame similar to the position of the tracking particle can be generated.

Then, the particle tracking apparatus 10 can generate a velocity distribution having a high spatial resolution based on the first image and the transformation frame (S2003).

For example, the particle tracking device 10 may be configured to determine, based on the position of one or more tracking particles in each of the first image and the transform frame, to determine, for each pixel included in the first image, The position of the pixel can be searched.

In this way, fine displacements can be calculated for each of at least one tracking particle between the first image and the transform frame.

Thereafter, the particle tracking device 10 can generate a spatially high resolution velocity distribution based on fine displacements for each tracking particle.

The particle tracking method according to the embodiment described with reference to FIG. 2 may also be implemented in the form of a recording medium including instructions executable by a computer such as a program module executed by a computer. Computer readable media can be any available media that can be accessed by a computer and includes both volatile and nonvolatile media, removable and non-removable media. In addition, the computer-readable medium can include both computer storage media and communication media. Computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Communication media typically includes any information delivery media, including computer readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave, or other transport mechanism.

The particle tracking method according to an embodiment of the present invention may also be implemented as a computer program (or a computer program product) including instructions executable by a computer. A computer program includes programmable machine instructions that are processed by a processor and can be implemented in a high-level programming language, an object-oriented programming language, an assembly language, or a machine language . The computer program may also be recorded on a computer readable recording medium of a type (e.g., memory, hard disk, magnetic / optical medium or solid-state drive).

Thus, the particle tracking method according to an embodiment of the present invention can be implemented by a computer program as described above being executed by a computing device. The computing device may include a processor, a memory, a storage device, a high-speed interface connected to the memory and a high-speed expansion port, and a low-speed interface connected to the low-speed bus and the storage device. Each of these components is connected to each other using a variety of buses and can be mounted on a common motherboard or mounted in any other suitable manner.

Where the processor may process instructions within the computing device, such as to display graphical information to provide a graphical user interface (GUI) on an external input, output device, such as a display connected to a high speed interface And commands stored in memory or storage devices. As another example, multiple processors and / or multiple busses may be used with multiple memory and memory types as appropriate. The processor may also be implemented as a chipset comprised of chips comprising multiple independent analog and / or digital processors.

The memory also stores information within the computing device. In one example, the memory may comprise volatile memory units or a collection thereof. In another example, the memory may be comprised of non-volatile memory units or a collection thereof. The memory may also be another type of computer readable medium such as, for example, a magnetic or optical disk.

And the storage device can provide a large amount of storage space to the computing device. The storage device may be a computer readable medium or a configuration including such a medium and may include, for example, devices in a SAN (Storage Area Network) or other configurations, and may be a floppy disk device, a hard disk device, Or a tape device, flash memory, or other similar semiconductor memory device or device array.

It will be understood by those skilled in the art that the foregoing description of the present invention is for illustrative purposes only and that those of ordinary skill in the art can readily understand that various changes and modifications may be made without departing from the spirit or essential characteristics of the present invention. will be. It is therefore to be understood that the above-described embodiments are illustrative in all aspects and not restrictive. For example, each component described as a single entity may be distributed and implemented, and components described as being distributed may also be implemented in a combined form.

The scope of the present invention is defined by the appended claims rather than the detailed description and all changes or modifications derived from the meaning and scope of the claims and their equivalents are to be construed as being included within the scope of the present invention do.

10: particle tracking device
110: particle photographing unit
120: cross-correlation calculation unit
130; The frame-
140: velocity distribution calculation unit

Claims (13)

A particle tracking method for analyzing a displacement of a particle by photographing a flow field including at least one tracking particle that can be identified through a plurality of photographed images at a predetermined time interval,
Dividing a pixel region of each image with respect to the plurality of images into at least one of the one or more tracking particles and in units of analysis regions which are pixel regions of a predetermined size that perform tracking of the tracking particles included;
Calculating correlation coefficients for each of the plurality of images on an analysis region basis on the basis of the tracking particles included in each of the analysis regions corresponding to positions mutually corresponding to the plurality of images; And
And calculating an average velocity distribution of the tracking particles included in each of the analysis regions between the plurality of images based on the calculated correlation coefficients. The method according to claim 1,
Wherein the calculating the correlation coefficient comprises:
Calculating a correlation coefficient between each interpretation area in the first image and each interpretation area in the second image taken consecutively with the first image,
Wherein the step of calculating the velocity distribution comprises:
Determining a position in a second image having a correlation coefficient calculated for each analysis region as the largest value as an average displacement of the tracking particles contained in each analysis region in the first image, . 3. The method of claim 2,
The particle tracking method includes:
Using the average displacement of the tracking particles contained in each of the analysis regions to generate a transformed image in which the position of each tracking particle is corrected for the one or more tracking particles in the second image, Way. The method of claim 3,
Wherein the step of generating the transformed image comprises:
Reversing the position of the one or more tracking particles in the second image by a displacement of each tracking particle calculated for each analysis area in the second image. 5. The method of claim 4,
The particle tracking method includes:
Further comprising calculating displacement of each of the one or more tracking particles based on the position of the one or more tracking particles in each of the first image and the transformed image. 6. The method of claim 5,
Wherein calculating the displacement of each of the one or more tracking particles comprises:
Searching for the same tracking particle within the constant pixel distance from the same position as the position in the first image in the transformed image for each of the one or more tracking particles. 1. A particle tracking apparatus for analyzing a displacement of a particle by photographing a flow field including at least one tracking particle capable of being identified through a plurality of photographed images at a predetermined time interval,
A particle photographing unit sequentially photographing a flow field including the at least one tracking particle at regular time intervals; And
Dividing a pixel region of each image with respect to the plurality of images in a unit of an analysis region that is a pixel region of a predetermined size that includes at least one of the one or more tracking particles and performs tracking of the included tracking particles; Calculating a correlation coefficient for each of the plurality of images on the basis of the analysis area on the basis of the tracking particles included in each of the analysis areas corresponding to the mutually corresponding positions of the plurality of images, And a cross-correlation calculation unit for calculating an average velocity distribution of the tracking particles included in the region. 8. The method of claim 7,
The cross-
Calculating a correlation coefficient between each interpretation region in the first image and each interpretation region in the second image captured successively from the first image, And determines a position in the image as an average displacement of the tracking particles included in each of the analysis regions in the first image. 9. The method of claim 8,
The particle tracking device comprises:
Further comprising a frame transformer for generating a transformed image by correcting the position of each of the tracking particles with respect to the at least one tracking particle in the second image by using an average displacement of the tracking particles included in each of the analysis areas, Tracking device. 10. The method of claim 9,
The frame converter may include:
And moves the position of the one or more tracking particles in the second image back by a displacement of each tracking particle calculated for each analysis region in the second image. 11. The method of claim 10,
The particle tracking device comprises:
Further comprising a velocity distribution calculation unit that calculates a displacement of each of the one or more tracking particles based on the position of the one or more tracking particles in each of the first image and the conversion image. 12. The method of claim 11,
The velocity distribution calculation unit may calculate,
Wherein in the transformed image for each of the one or more tracking particles, the same tracking particle is searched within a certain pixel distance from the same position as the position in the first image. A computer program stored on a recording medium for performing the method of any one of claims 1 to 6, performed by a computing device.
KR1020150090302A 2015-05-28 2015-06-25 High resolution particle image velocimetry technique using combined cross corrleation and optical flow method KR101659443B1 (en)

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CN109035324A (en) * 2018-07-20 2018-12-18 润电能源科学技术有限公司 A kind of coal dust flow-speed measurement method and device based on image recognition
CN110440766A (en) * 2019-08-13 2019-11-12 陕西煤业化工技术研究院有限责任公司 A kind of water-bearing layer hydrogeological parameter measuring device and method
KR102218310B1 (en) * 2019-11-07 2021-02-23 강원대학교산학협력단 Flow measurement device using image sensor
CN113960043A (en) * 2021-10-20 2022-01-21 中国人民解放军国防科技大学 Method and device for determining time evolution characteristics of supersonic/hypersonic turbulence
KR20220065436A (en) * 2020-11-13 2022-05-20 단국대학교 산학협력단 Determination method of the searching window based on optical flow alogorithm

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KR101305305B1 (en) * 2012-06-12 2013-09-06 동의대학교 산학협력단 System and method for measuring surface image velocity using correlation analysis of spatio-temporal images

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JP2003084006A (en) * 2001-09-13 2003-03-19 Mitsubishi Electric Corp Flow velocity measuring apparatus and method for measuring flow velocity using the same
KR101305305B1 (en) * 2012-06-12 2013-09-06 동의대학교 산학협력단 System and method for measuring surface image velocity using correlation analysis of spatio-temporal images

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Publication number Priority date Publication date Assignee Title
CN109035324A (en) * 2018-07-20 2018-12-18 润电能源科学技术有限公司 A kind of coal dust flow-speed measurement method and device based on image recognition
CN110440766A (en) * 2019-08-13 2019-11-12 陕西煤业化工技术研究院有限责任公司 A kind of water-bearing layer hydrogeological parameter measuring device and method
KR102218310B1 (en) * 2019-11-07 2021-02-23 강원대학교산학협력단 Flow measurement device using image sensor
KR20220065436A (en) * 2020-11-13 2022-05-20 단국대학교 산학협력단 Determination method of the searching window based on optical flow alogorithm
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CN113960043A (en) * 2021-10-20 2022-01-21 中国人民解放军国防科技大学 Method and device for determining time evolution characteristics of supersonic/hypersonic turbulence

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