CN102645555A - Micromotion measuring method - Google Patents
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- CN102645555A CN102645555A CN2012100401027A CN201210040102A CN102645555A CN 102645555 A CN102645555 A CN 102645555A CN 2012100401027 A CN2012100401027 A CN 2012100401027A CN 201210040102 A CN201210040102 A CN 201210040102A CN 102645555 A CN102645555 A CN 102645555A
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Abstract
The invention relates to a micromotion measuring method, which is characterized by comprising the following steps of: collecting a group of blurred images with a microstructure by using a computer micro vision system with automatic control exposure time and photoelectric conversion coefficient; extracting alpha channel information of a group of blurred images from the blurred image with the microstructure by using a Spectralmatting algorithm; and establishing a light stream constraint model based on the alpha channel information of the blurred images, the distance gradient among the alpha channel information, the gradient of the channel information of the motion blurred image obtained through affine transformation containing multiple motion types such as translation and rotation in the basic valley in combination with the time gradient of the corresponding image channel information to be tested, wherein the gradient of the motion blurred image channel information represents the motion parameter vector and the time gradient of the image channel information to be tested, that is the difference value of the image channel information collected before and after the motion of the microstructure; and the required micromotion measuring result can be obtained according to the established blurred image motion constraint model. In comparison with the prior art, the micromotion measuring method has the advantages of high measuring precision and low cost of the measuring device by utilizing the blurred information of the motion blurred image for micromotion measurement of microstructures.
Description
Technical field
The present invention relates to a kind of motion measuring method.
Background technology
Little/the manufacturing technology of receiving has a wide range of applications in fields such as automobile, new forms of energy, flexible electronic, photoelectron, MEMS/NEMS (little/receive Mechatronic Systems) and biologic medicals.Little/receive and make, little/dynamic property of system received all has very important significance to its design, manufacturing and reliability operation, therefore little/the system dynamic characteristic of receiving is tested to seem particularly crucial.In addition, nano-precision micrometric displacement detection technique is one of gordian technique of research precise jiggle platform.
In the microstructure micromotion measuring method of being reported, the little vision measuring method of computing machine does not need complicated optical interference circuit system and LASER Light Source.Simultaneously, measured in the method motion can be observed measured target and motion conditions thereof intuitively directly from video image, thereby convenience realizes man-machine interaction and tested motion is made an explanation.For this reason, the little visible sensation method of computing machine becomes gradually and measures the effective method of microstructure micromotion.In the little visible sensation method of computing machine of the measurement micromotion of being reported, great majority all are based on sequence picture rich in detail design.These methods adopt high speed imaging equipment to shorten the time shutter of video camera usually or adopt the stroboscopic imaging device " to freeze " target image and avoid the fuzzy of image, thereby reduce the influence that motion blur is measured micromotion.Yet these the two kinds methods of eliminating motion blur have increased the cost of equipment or the complicacy of measurement.In conjunction with the little visible sensation method of computing machine, directly utilize the blurred picture of microstructure to carry out the measurement of high precision micromotion, can reduce the cost or the complicacy of measurement.
Through analysis-by-synthesis and comparison to prior art, mainly there is the problem of the following aspects in the present micromotion measuring method of reporting: the little visible sensation method of computing machine that (1) adopts high speed imaging equipment and stroboscopic imaging device to eliminate motion blur has increased the cost of equipment or the complicacy of measurement; (2) the present method of reporting of directly utilizing blurred picture information to carry out estimation, angular velocity measurement, amplitude measurement and tachometric survey all need at first be set up the motion blur image model; And need the type of known movement function, thereby need design different Measurement Algorithm for different type of sports; (3) method of directly utilizing the motion blur image fuzzy message to carry out estimation that exists at present is not to measure and design to the micromotion of microstructure, and precision is lower when being used to measure the microstructure micromotion.
Summary of the invention
Goal of the invention of the present invention is to provide a kind of deficiency that overcomes prior art, directly adopts the fuzzy message of motion blur image to carry out the accuracy method that the microstructure micromotion is measured.
The present invention realizes like this; Employing has the little vision system of computing machine of automatic control time shutter and photoelectric conversion factors and gathers the blurred picture of one group of microstructure; From the blurred picture of this group microstructure, adopt Spectral matting algorithm to extract the α channel information of one group of blurred picture then; According to the α channel information of this group blurred picture and the gradient between these α channel informations; And the gradient
that includes the motion blur image that affined transformation obtained
channel information of multiple type of sports such as translation and rotation through basic basin combines the time gradient
of corresponding testing image
channel information; Set up a kind of similar optical flow constraint model
that is used for;
is the gradient of motion blur image
channel information;
expression kinematic parameter vector; The time gradient of
expression testing image
channel information; Be the difference of image
channel information of collection before and after the microstructure motion, just can obtain needed micromotion measurement result according to this blurred picture kinematic constraint model of setting up.The unit of the micromotion measurement result that is obtained
is a pixel, according to the picture pick-up device that is adopted intrinsic pixel transitions become parasang parameter (is 0.1 millimeter like some picture pick-up device one pixel) to be converted into a millimeter unit.
In the formula;
is the gradient of motion blur image
channel information;
expression kinematic parameter vector; The time gradient of
expression testing image
channel information, i.e. the difference of image
channel information of gathering before and after the microstructure motion.
is actually a test image
channel information time gradient.That is to say; Gather a sub-picture before the microstructure motion; Extract
channel information (being labeled as
) of this image; Moved after
(if being displacement); Take a sub-picture again; And extract its
channel information (being labeled as
);
so is a vector.
Here, the median filter that utilizes little template carries out medium filtering to the blurred picture of the microstructure of gathering, and removes the influence of shot noise to measurement result.In addition, the little vision system of computing machine is installed on the vibration isolation table to reduce the influence that the mechanical noise that caused by factors such as extraneous vibrations is measured micromotion.
The calculating of blurred picture α channel information gradient adopts gradient filter to carry out.When adopting gradient filter to calculate; Earlier blurred picture being carried out multiple dimensioned method decomposes; Blurred picture is after multiple dimensioned method is decomposed; At first adopt the gradient of the gradient filter calculation of alpha channel information of little tap, calculate the gradient of the big pixel motion yardstick layer blurred picture α-channel information of last one deck several times after the iteration again with the gradient filter of big tap number.This layering estimation approach not only can improve the micromotion measuring accuracy, and can accelerate the measuring speed of algorithm.
In order further to improve the micromotion measuring accuracy, the kinematic parameter in the blurred picture kinematic constraint model adopts the Robust Estimation method to calculate.Least square method with traditional is compared, and the error of Robust Estimation method reaches after the saturation value, no longer increases, so outlier has received certain restriction to the influence of finally separating, thereby can further improve measuring accuracy.
Precision with algorithm is a horizontal ordinate; Efficient is ordinate; Make up a precision-efficient two dimension Performance Evaluation coordinate system; The filter tap number through different calculation of alpha channel information gradients is set or the yardstick number of plies of multiple dimensioned method obtain different precision, efficient coordinate parameters, adopt the precision and the efficient of this coordinate parameters assessment micromotion Measurement Algorithm.According to precision and efficient performance assessment result, revise the micromotion Measurement Algorithm of design, not only measuring accuracy height but also measuring speed are fast to make the algorithm of design.Simultaneously, the data that obtained and laser interferometer are measured the data that obtain to the micromotion of microstructure compare, verify that the method that direct employing blurred picture of the present invention is measured micromotion can measure high-precision microstructure micromotion.
The present invention compared with present technology, the fuzzy message with direct employing motion blur image is carried out the advantage that the microstructure micromotion is measured, measuring accuracy is high, the measuring equipment cost is low.
Description of drawings:
Fig. 1 is a blurred picture kinematic constraint modeling process synoptic diagram of the present invention;
Fig. 2 is a micromotion Measurement Algorithm process flow diagram;
Fig. 3 is that microstructure blurred picture micromotion is measured process flow diagram.
Embodiment:
Combine accompanying drawing and embodiment that the present invention is done describes in further detail at present:
As shown in Figure 1; The present invention realizes like this; Employing has the little vision system of computing machine of automatic control time shutter and photoelectric conversion factors and gathers the blurred picture of one group of microstructure; From the blurred picture of this group microstructure, adopt Spectral matting algorithm to extract the α channel information of one group of blurred picture then; According between α channel information and these α channel informations of this group blurred picture apart from gradient; And the gradient
that includes the motion blur image that affined transformation obtained
channel information of multiple type of sports such as translation and rotation through basic basin combines the time gradient
of corresponding testing image
channel information; Set up a kind of similar optical flow constraint model
that is used for;
is the gradient of motion blur image
channel information;
expression kinematic parameter vector; The time gradient of
expression testing image
channel information; Be the difference of image
channel information of collection before and after the microstructure motion, just can obtain needed micromotion measurement result according to this blurred picture kinematic constraint model of setting up.
As shown in Figure 3, the median filter that utilizes little template carries out medium filtering to the blurred picture of the microstructure of gathering and realizes squelch, removes the influence of shot noise to measurement result.In addition, the little vision system of computing machine is installed on the vibration isolation table carries out system calibrating, to reduce the influence that the mechanical noise that caused by factors such as extraneous vibrations is measured micromotion through the precision calibration piece.
As shown in Figure 2, the gradient calculation of the α channel information of blurred picture adopts gradient filter to carry out.When adopting gradient filter to calculate; Earlier blurred picture being carried out multiple dimensioned method decomposes; Blurred picture is after multiple dimensioned method is decomposed; At first adopt the gradient of the gradient filter calculation of alpha channel information of little tap, calculate the gradient ▽ α of the big pixel motion yardstick layer blurred picture α channel information of last one deck several times after the iteration again with the gradient filter of big tap number.
Like Fig. 2, shown in 3, the The data Robust Estimation method that constitutes blurred picture kinematic constraint model is handled.
As shown in Figure 3; Precision with algorithm is a horizontal ordinate; Efficient is ordinate, makes up a precision-efficient two dimension Performance Evaluation coordinate system, the filter tap number through different α channel information gradients are set or the yardstick number of plies of multiple dimensioned method; Obtain different precision, efficient coordinate parameters, adopt the precision and the efficient of this coordinate parameters assessment micromotion Measurement Algorithm.According to precision and efficient performance assessment result, revise the micromotion Measurement Algorithm of design, not only measuring accuracy height but also measuring speed are fast to make the algorithm of design.Simultaneously, the data that obtained and laser interferometer are measured the data that obtain to the micromotion of microstructure compare, verify that the method that direct employing blurred picture of the present invention is measured micromotion can measure high-precision microstructure micromotion.
Claims (10)
1. micromotion measuring method; It is characterized in that adopting the little vision system of computing machine to gather the blurred picture of one group of microstructure with automatic control time shutter and photoelectric conversion factors; From the blurred picture of this group microstructure, adopt Spectral matting algorithm to extract the α channel information of one group of blurred picture then; According between α channel information and these α channel informations of this group blurred picture apart from gradient; And the gradient
that includes the motion blur image that affined transformation obtained
channel information of multiple type of sports such as translation and rotation through basic basin combines the time gradient
of corresponding testing image
channel information; Set up a kind of similar optical flow constraint model
that is used for;
is the gradient of motion blur image
channel information;
expression kinematic parameter vector; The time gradient of
expression testing image
channel information; Be the difference of image
channel information of collection before and after the microstructure motion, just can obtain needed micromotion measurement result according to this blurred picture kinematic constraint model of setting up.
2. micromotion measuring method according to claim 1, the median filter that it is characterized in that utilizing little template carries out medium filtering to the blurred picture of the microstructure of gathering, and removes the influence of shot noise to measurement result.
3. micromotion measuring method according to claim 1 and 2 is characterized in that the little vision system of computing machine is installed on the vibration isolation table to reduce the influence that the mechanical noise that caused by factors such as extraneous vibrations is measured micromotion.
4. micromotion measuring method according to claim 1 and 2 is characterized in that the calculating of the gradient of blurred picture α channel information adopts gradient filter to carry out.
5. micromotion measuring method according to claim 3 is characterized in that the calculating of the gradient of blurred picture α channel information adopts gradient filter to carry out.
6. micromotion measuring method according to claim 4; When it is characterized in that adopting gradient filter to calculate; Earlier blurred picture being carried out multiple dimensioned method decomposes; Blurred picture at first adopts the gradient of the gradient filter calculation of alpha channel information of little tap after multiple dimensioned method is decomposed, calculate the gradient of the big pixel motion yardstick layer blurred picture α channel information of last one deck several times after the iteration again with the gradient filter of big tap number.
7. micromotion measuring method according to claim 5; When it is characterized in that adopting gradient filter to calculate; Earlier blurred picture being carried out multiple dimensioned method decomposes; Blurred picture at first adopts the gradient of the gradient filter calculation of alpha channel information of little tap after multiple dimensioned method is decomposed, calculate the gradient of the big pixel motion yardstick layer blurred picture α channel information of last one deck several times after the iteration again with the gradient filter of big tap number.
8. according to claim 1 or 2 or 5 or 6 or 7 described micromotion measuring methods, it is characterized in that the The data Robust Estimation method that constitutes blurred picture kinematic constraint model is handled.
9. according to claim 6 or 7 described micromotion measuring methods; It is characterized in that the precision with algorithm is a horizontal ordinate; Efficient is ordinate, makes up a precision-efficient two dimension Performance Evaluation coordinate system, the filter tap number through different α channel information gradients are set or the yardstick number of plies of multiple dimensioned method; Obtain different precision, efficient coordinate parameters; Adopt the precision and the efficient of this coordinate parameters assessment micromotion Measurement Algorithm,, revise the micromotion Measurement Algorithm of design according to precision and efficient performance assessment result; Not only measuring accuracy height but also measuring speed are fast to make the algorithm of design; Simultaneously, the data that obtained and laser interferometer are measured the data that obtain to the micromotion of microstructure compare, verify that the method that direct employing blurred picture of the present invention is measured micromotion can measure high-precision microstructure micromotion.
10. micromotion measuring method according to claim 8; It is characterized in that the precision with algorithm is a horizontal ordinate; Efficient is ordinate, makes up a precision-efficient two dimension Performance Evaluation coordinate system, the filter tap number through different α channel information gradients are set or the yardstick number of plies of multiple dimensioned method; Obtain different precision, efficient coordinate parameters; Adopt the precision and the efficient of this coordinate parameters assessment micromotion Measurement Algorithm,, revise the micromotion Measurement Algorithm of design according to precision and efficient performance assessment result; Not only measuring accuracy height but also measuring speed are fast to make the algorithm of design; Simultaneously, the data that obtained and laser interferometer are measured the data that obtain to the micromotion of microstructure compare, verify that the method that direct employing blurred picture of the present invention is measured micromotion can measure high-precision microstructure micromotion.
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| CN107431784A (en) * | 2015-02-18 | 2017-12-01 | 索尼公司 | The system and method that cigarette is detected during operation is dissected |
| CN110108348A (en) * | 2019-05-15 | 2019-08-09 | 湖南科技大学 | Thin-wall part micro breadth oscillation measurement method and system based on motion amplification optical flow tracking |
| CN110948485A (en) * | 2019-11-21 | 2020-04-03 | 佛山科学技术学院 | Calculation method for accurate numerical solution of rope traction parallel robot flexible cable catenary model |
| CN111257592A (en) * | 2020-03-05 | 2020-06-09 | 广东零偏科技有限公司 | Static discrimination method for detection device |
| CN114630062A (en) * | 2022-03-10 | 2022-06-14 | 杭州指数星空智能设备制造有限责任公司 | Method for improving dynamic range of TOF sensor |
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Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107431784A (en) * | 2015-02-18 | 2017-12-01 | 索尼公司 | The system and method that cigarette is detected during operation is dissected |
| CN107431784B (en) * | 2015-02-18 | 2020-02-18 | 索尼公司 | System and method for detecting smoke during anatomical surgery |
| CN105651377A (en) * | 2016-01-11 | 2016-06-08 | 衢州学院 | Video data mining-based non-contact object vibration frequency measurement method |
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| CN110108348A (en) * | 2019-05-15 | 2019-08-09 | 湖南科技大学 | Thin-wall part micro breadth oscillation measurement method and system based on motion amplification optical flow tracking |
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| CN111257592A (en) * | 2020-03-05 | 2020-06-09 | 广东零偏科技有限公司 | Static discrimination method for detection device |
| CN114630062A (en) * | 2022-03-10 | 2022-06-14 | 杭州指数星空智能设备制造有限责任公司 | Method for improving dynamic range of TOF sensor |
| CN114630062B (en) * | 2022-03-10 | 2024-03-12 | 杭州指数星空智能设备制造有限责任公司 | Method for improving dynamic range of TOF sensor |
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Application publication date: 20120822 |