CN110225335A - Camera stability assessment method and device - Google Patents
Camera stability assessment method and device Download PDFInfo
- Publication number
- CN110225335A CN110225335A CN201910535068.2A CN201910535068A CN110225335A CN 110225335 A CN110225335 A CN 110225335A CN 201910535068 A CN201910535068 A CN 201910535068A CN 110225335 A CN110225335 A CN 110225335A
- Authority
- CN
- China
- Prior art keywords
- variance
- camera
- abscissa
- ordinate
- marginal point
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N17/00—Diagnosis, testing or measuring for television systems or their details
- H04N17/002—Diagnosis, testing or measuring for television systems or their details for television cameras
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10016—Video; Image sequence
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Geometry (AREA)
- Computer Vision & Pattern Recognition (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Biomedical Technology (AREA)
- General Health & Medical Sciences (AREA)
- Multimedia (AREA)
- Signal Processing (AREA)
- Image Analysis (AREA)
Abstract
The present invention provides a kind of camera stability assessment method and devices, this method comprises: obtaining continuous multiframe edge contour image；It include the edge contour of the target object of camera shooting in multiframe edge contour image；Determine the variance of the ordinate of same marginal point in multiframe edge contour image；According to the stability of square error estimation camera.The accuracy of camera stability assessment can be improved in the present invention.
Description
Technical field
The present invention relates to technical field of high-precision measurement, more particularly, to a kind of camera stability assessment method and device.
Background technique
In the production and scientific research link of the industrial departments such as space flight, machinery, machine vision metrology side is more and more used
Method carries out high-acruracy survey task, usual high-acruracy survey task to camera imaging stability and measurement result stability requirement compared with
It is high.Existing camera sensor is divided into CCD (Charge-coupled Device, charge coupled cell) and CMOS
Two kinds of (Complementary Metal Oxide Semiconductor, complementary metal oxide semiconductor).Cmos image passes
Sensor integrated level is high, and distance is close between each element, circuit, and than more serious, imaging noise is high for interference between each other.Ccd image
Transducer sensitivity is high, and noise is low, but expensive.Before specific measurement task starts, need to carry out camera type selecting work,
Select a imaging effect good, reliable and stable, the phase chance haveing excellent performance has the work to get twice the result with half the effort to subsequent measurement task
With.Selection camera model usually requires to assess the stability of the model camera.
Currently, in order to assess the stability of camera, existing method based on the pixel value of pixel in acquisition image change into
Row assessment, for the two field pictures of continuous acquisition, chooses some pixel in two field pictures, obtains two pixel values, if two
The difference of a pixel value is less than certain threshold value, then differentiates that camera is stablized.This method is simpler, but adjacent two field pictures are used only not
Camera stability can accurately be measured.Another existing method is assessed based on characteristic point state change in acquisition image, continuous acquisition N
Every frame image is divided into multiple regions by frame image, and the description vectors of image are generated using the angle point detected in each region,
The changed number of regions of angle point existence in N frame image is calculated according to description vectors, according to angle point in N frame image
The changed number of regions of existence determines whether the N frame image is stable, and then can judge whether camera is stable.The party
Method excessively relies on the accuracy of Corner Detection, and existing Corner Detection Algorithm is not very robust, there are more erroneous detection,
Situations such as missing inspection, this can cause large effect to final camera stability assessment result.How camera is accurately and effectively measured
Stability is current field of high-precision measurement urgent problem to be solved.
Summary of the invention
The present invention provides a kind of camera stability assessment method and device, camera stability assessment is can be improved in the present invention
Accuracy.
In a first aspect, the embodiment of the invention provides a kind of camera stability assessment methods, this method comprises:
Obtain continuous multiframe edge contour image；It include the target of camera shooting in the multiframe edge contour image
The edge contour of object determines the variance of the ordinate of same marginal point in the multiframe edge contour image；According to the variance
Assess the stability of camera.
Second aspect, the embodiment of the present invention also provide a kind of camera stability assessment device, which includes: acquisition mould
Block, for obtaining continuous multiframe edge contour image；It include the target of camera shooting in the multiframe edge contour image
The edge contour of object；Computing module, for determining the side of the ordinate of same marginal point in the multiframe edge contour image
Difference；Evaluation module, for the stability according to the square error estimation camera.
The third aspect, the embodiment of the present invention also provide a kind of electronic equipment, including memory, processor, deposit in memory
The computer program that can be run on a processor is contained, processor realizes above-mentioned camera stability assessment when executing computer program
Method.
Fourth aspect, the embodiment of the present invention also provide a kind of meter of non-volatile program code that can be performed with processor
Calculation machine readable medium, said program code make the processor execute above-mentioned camera stability assessment method.
The embodiment of the present invention brings following the utility model has the advantages that the embodiment of the invention provides a kind of camera stability assessment sides
Method and device, this method passes through first obtains continuous multiframe edge contour image, to increase for camera stability assessment
Amount of images improves the accuracy of camera stability assessment；Secondly, determining the vertical of same marginal point in each frame border contour images
The variance of coordinate, variance can describe the fluctuation of ordinate, then, reflect the stability of camera, finally, can be with according to variance
Generate the stability assessment result of camera.Therefore, the accuracy of camera stability assessment can be improved in the embodiment of the present invention.
Other features and advantages of the present invention will illustrate in the following description, also, partly become from specification
It obtains it is clear that understand through the implementation of the invention.The objectives and other advantages of the invention are in specification, claims
And specifically noted structure is achieved and obtained in attached drawing.
To enable the above objects, features and advantages of the present invention to be clearer and more comprehensible, preferred embodiment is cited below particularly, and cooperate
Appended attached drawing, is described in detail below.
Detailed description of the invention
It, below will be to specific in order to illustrate more clearly of the specific embodiment of the invention or technical solution in the prior art
Embodiment or attached drawing needed to be used in the description of the prior art be briefly described, it should be apparent that, it is described below
Attached drawing is some embodiments of the present invention, for those of ordinary skill in the art, before not making the creative labor
It puts, is also possible to obtain other drawings based on these drawings.
Fig. 1 is camera stability assessment method flow diagram provided in an embodiment of the present invention；
Fig. 2 be camera stability assessment method provided in an embodiment of the present invention in comprising photographic subjects gray level image and
The photographic subjects edge contour image extracted after edge detection is carried out using Canny operator；
Fig. 3 is target area logic arrangement schematic diagram in camera stability assessment method provided in an embodiment of the present invention；
Fig. 4 is the ROI region schematic diagram chosen in camera stability assessment method provided in an embodiment of the present invention；
Fig. 5 is the ROI region schematic diagram that should not be chosen in camera stability assessment method provided in an embodiment of the present invention；
Fig. 6 is the preferable camera assessment result broken line schematic diagram of stability provided in an embodiment of the present invention；
Fig. 7 is the poor camera assessment result broken line schematic diagram of stability provided in an embodiment of the present invention；
Fig. 8 is camera stability assessment apparatus structure schematic diagram provided in an embodiment of the present invention；
Fig. 9 is another structural schematic diagram of camera stability assessment device provided in an embodiment of the present invention；
Figure 10 is electronic devices structure schematic block diagram provided in an embodiment of the present invention.
Specific embodiment
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with attached drawing to the present invention
Technical solution be clearly and completely described, it is clear that described embodiments are some of the embodiments of the present invention, rather than
Whole embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art are not making creative work premise
Under every other embodiment obtained, shall fall within the protection scope of the present invention.
The embodiment of the invention provides a kind of camera stability assessment method and devices, and camera stability assessment can be improved
Accuracy and reliability, can be used in high-precision commercial measurement task, to selecting a imaging effect good, reliable and stable, property
Camera that can be excellent provides technical support.
For convenient for understanding the present embodiment, first to a kind of camera stability assessment disclosed in the embodiment of the present invention
Method describes in detail.
The embodiment of the invention provides a kind of camera stability assessment method, camera stability assessment shown in Figure 1
Method flow diagram, method includes the following steps:
Step S102 obtains continuous multiframe edge contour image；It include that camera is shot in multiframe edge contour image
Target object edge contour.
Edge contour image can be obtained after processing by the picture including target object that camera is shot, edge contour figure
The edge contour of target object including camera shooting as in.Target object refers to the bat selected for assessing camera stability
Object is taken the photograph, can be the object of oblong object, triangle, pentagon object or other shapes.
It should be noted that the total quantity of multiframe edge contour image is needed much larger than 1, and every edge contour image
In include target object edge contour, to improve the accuracy and reliability of camera stability assessment.
Step S104 determines the variance of the ordinate of same marginal point in multiframe edge contour image.
Marginal point is the one group of coordinate points chosen on the edge contour in edge contour image.To every frame border profile diagram
It can determine one group of marginal point, the abscissa of edge contour point is identical in different frame, and ordinate is different, therefore, to each cross
Coordinate calculates the variance of corresponding all ordinates.Using the marginal point with identical abscissa as same marginal point.
Step S106, according to the stability of square error estimation camera.
Variance can describe the fluctuation of camera, and then reflect that the stability of camera therefore can be by judging variance
Size, to assess the stability of camera.The embodiment of the present invention has used the statistical significance of variance, intuitively can effectively illustrate
Problem provides more accurate assessment result.Variance can be further analyzed calculating, and by calculated result and default threshold
Value compares or analyzes the stability assessment result for obtaining camera.
A kind of camera stability assessment method provided in an embodiment of the present invention, first by obtaining continuous multiframe edge wheel
Wide image improves the accuracy of camera stability assessment to increase the amount of images for being used for camera stability assessment；Secondly, really
The variance of the ordinate of same marginal point, variance can describe the fluctuation of ordinate in fixed each frame border contour images, then,
The stability for reflecting camera, finally, the stability assessment result of camera can be generated according to variance.Therefore, the embodiment of the present invention
The accuracy of camera stability assessment can be improved.
In order to determine the marginal point in edge contour image, and variance is determined according to obtained marginal point coordinate, for assessment
Camera stability provides foundation, in the embodiment of the present invention, determines the ordinate of same marginal point in multiframe edge contour image
Variance specifically includes the following steps:
(1) the identical region of selected pixels coordinate in multiframe edge contour image respectively, obtains multiple target areas；It is more
It include the part edge profile of target object in a target area.
It can be by setting parameter preset with the identical region of selected pixels coordinate in edge contour image.Parameter preset
Upper left pixel location information, horizontal pixel range information and vertical pixel range information including wanting the region of selection,
ROI region (Region Of Interest, area-of-interest) can be marked off in edge contour image according to parameter preset,
Using the ROI region marked off as target area.Since the parameter preset that each frame uses is identical, and multiframe edge contour image
Size is identical, therefore, can select that size is identical and the identical multiple targets of pixel coordinate from each frame border contour images
Region.
It should be noted that the quantity of target area is identical with the frame number of edge contour image, and target area and edge
Contour images correspond.The ROI region schematic diagram of selection shown in Figure 4, (a) in Fig. 4 are when target object is ellipse
When round, the ROI region schematic diagram that can be chosen, (b) in Fig. 4 is the ROI that can choose when target object is triangle
Area schematic, (c) in Fig. 4 are the ROI region schematic diagrames that can choose when target object is pentagon.
It is further to note that parameter preset can obtain continuous multiframe edge contour figure by manually setting
As after, position and the size of ROI region are manually determined according to edge contour image according to certain screening rule, confirms the area
Upper left pixel location information, horizontal pixel range information and the vertical pixel range information in domain.For example, screening rule can be with
Being should not be comprising interlaced, excessively complicated profile in ROI region, and should not choose and as shown in Figure 5 should not choose
The contour area of hypotelorism shown in ROI region schematic diagram.To guarantee the part side in target area including target object
Edge profile needs to guarantee that during determining parameter preset, the ROI region chosen includes the part edge profile of target object.
Parameter preset can also be obtained by other methods, and the embodiment of the present invention is not especially limited.
(2) one group of abscissa is generated in each target area respectively, and corresponding one group vertical seat is generated according to abscissa
It is marked with the one group of marginal point determined in each target area；Wherein, the abscissa of corresponding edge point is identical in different groups.
A target area can be chosen at random, generate one group at random for edge contour region in the target area
Abscissa, this group of abscissa includes multiple abscissa data, for example, the coordinate data number that one group of abscissa includes can be greater than
100.Due to including the part edge profile of target object in target area, part edge can be obtained according to one group of abscissa
One group of ordinate corresponding with this group of abscissa on profile regard abscissa point corresponding with ordinate as marginal point.Due to one
The coordinate data that group abscissa includes be it is multiple, therefore, the marginal point number that one group of marginal point includes also is multiple, and its number
It is identical as the coordinate data number in one group of given abscissa.
When given one group of abscissa, it is denoted as x1,x2,…,xM, wherein M is the coordinate data number of this group of abscissa, reference
Target area logic arrangement schematic diagram as shown in Figure 3, according to the edge contour in abscissa and target area, it is available with
The corresponding one group of ordinate of abscissa, is denoted asWherein subscript indicates that the ordinate is first aim region
In ordinate.This group of abscissa is applied in remaining each target area in addition to the target area chosen, can be obtained respectively
The corresponding ordinate into remaining each target area in addition to the target area chosen: according to the method described above, available each
Ordinate in target area, is denoted asWherein, j=1,2 ..., N, N indicate the number of target area.?
After obtaining the abscissa and ordinate in a target area, the marginal point of available one group of target area is denoted asWherein, i=1,2 ..., M.
It should be noted that the abscissa in different target areas is identical, due to the edge in different target areas
Profile may be different, therefore the ordinate in different target areas may be different.Finally, one group is determined to each target area
Marginal point, this group of marginal point number are multiple.Multiple groups marginal point, the abscissa phase of each group marginal point are determined to multiple target areas
Together, ordinate may be different.It should also be noted that, the embodiment of the present invention can also give one group of ordinate, and sat by vertical
Mark generates one group of corresponding abscissa with one group of marginal point in each target area of determination, specifically gives abscissa or indulges and sits
Mark, selects, the embodiment of the present invention is not especially limited according to actual needs.
It should be noted that one group of abscissa can be generated at random, to make the embodiment of the present invention be suitable for more Multiple Shape
Target object, the shape of target object can also be directed to, set the corresponding mode for generating abscissa, the embodiment of the present invention pair
This is not especially limited.
It should also be noted that, a target area can be chosen at random, it can also be by all target areas according to certain
Logical order sequence, for example each target area can be sorted sequentially in time, target area logic shown in Figure 3
Schematic diagram is arranged, the first aim region after selecting logic sequence, for edge contour institute in the target area selected
One group of abscissa is generated at random in region.How to select a target area to generate one group of abscissa, it can be according to practical need
It asks and is selected, comparison of the embodiment of the present invention is not especially limited.It is further to note that can also be according to same mark
Standard generates one group of abscissa respectively simultaneously in all target areas.
(3) variance of the ordinate of abscissa same edge point is calculated.
Marginal point includes the information of abscissa and ordinate, due to the abscissa phase for including in different target areas
It together, can information to the ordinate for including in different target areas be for statistical analysis obtains variance.Variance can be used for
The fluctuation for describing ordinate, the stability of camera can be further reflected by the fluctuation of ordinate.
In view of the complexity in order to reduce calculating, the assessment efficiency of the embodiment of the present invention is improved, continuous multiframe is obtained
The step of edge contour image, comprising the following steps:
(1) the continuous multiframe initial pictures of camera shooting are obtained.
The embodiment of the present invention, which can be used fixed camera on the table and be continuously shot multiframe at regular intervals, includes
The image of fixed target object on the table, using the image as initial pictures.For example, camera can (T be greater than every T
Equal to 0.2 second) second is continuously shot N (N is integer greater than 0 and N much larger than 1) frame image, to obtain initial pictures.Wherein,
Camera can be face battle array gray scale CCD (CMOS) camera.
It should be noted that guarantee that acquisition image grayscale is stablized, it should be by center of circle camera lens used in shooting, face battle array gray scale
CCD (CMOS) camera, source of parallel light, photographic subjects are placed in darkroom the influence for avoiding environment light；It the use of regulated power supply is parallel
Light source provides stable voltage and current to guarantee that source of parallel light keeps stable output；It the use of regulated power supply is face battle array gray scale
CCD (CMOS) camera provides stable voltage and current to guarantee that face battle array gray scale CCD (CMOS) camera keeps stable power supply.
It is further to note that avoid camera and wanting between photographic subjects object that there are relative motions to assessment result
It impacts, by camera and photographic subjects object should be wanted to fix on the table, and camera and target object can be to greatest extent
Prevent because mechanical shaking is influence caused by assessment result.In shooting process, source of parallel light power is adjusted, keeps image grey
Maximum gradation value is spent between 175 to 185, and minimum gradation value is between 0 to 10.Assuming that camera and wanting between photographic subjects object
There is no relative motion.
(2) edge detection is carried out to continuous initial pictures respectively according to edge detection algorithm, obtains continuous multiframe side
Edge contour images.
Edge detection algorithm can be Canny algorithm (Canny edge detector, Canny edge detection algorithm).Make
Edge detection process carried out to every frame initial graphics respectively with Canny algorithm, available continuous multiframe edge contour image,
Gray level image comprising photographic subjects shown in Figure 2 and Canny operator is used to carry out the bat extracted after edge detection
Object edge contour images are taken the photograph, when target object is oblong object, in the grayscale image such as Fig. 2 of a certain frame initial pictures
(a) shown in, after edge detection process, obtained (b) in edge contour image such as Fig. 2 is shown.When target object is three
When angular object or pentagon object, the grayscale image and edge contour image of a certain frame initial pictures can be distinguished in referring to fig. 2
(c)-Fig. 2 in (f) shown in, details are not described herein.
The fluctuation situation of camera is described in view of variance can be used, in order to further describe camera in y direction
The step of stability, the variance of the ordinate of calculating abscissa same edge point, comprising: calculate the corresponding each group edge of abscissa
The average value of point ordinate；According to the corresponding variance of mean value calculation abscissa.
For example, can correspond to obtain N number of target area, be generated in each target area if there is N frame border contour images
One group of abscissa obtains N group abscissa, and every group of abscissa has M marginal point, the abscissa phase of corresponding edge point in different groups
Together, i.e. M marginal point corresponding abscissa in N number of target area is all x1,x2,…,xM, and this group of abscissa is corresponding vertical
Coordinate may be different, calculating and x1,x2,…,xMIt is correspondingCalculate M abscissa difference in N group marginal point
M side corresponding with abscissa can be calculated according to M obtained average value in the average value of corresponding N number of ordinate
Difference finally obtains { (x1,S1),(x2,S2)…(xM,SM)}。
In view of the fluctuation situation for more scientific ground camera acquisition image, further reflect the stability of camera, counts
The step of calculating the average value of the corresponding each group marginal point ordinate of abscissa, specifically includes the following steps:
The flat of each ordinate of the marginal point in each target area with identical abscissa is calculated according to the following formula
Mean value:Wherein,Indicate that the marginal point i's in each target area with identical abscissa is each vertical
The average value of coordinate, wherein i=1,2 ..., M, M are the marginal point for including in the corresponding one group of marginal point in a target area
Number,Indicate the ordinate of the marginal point i in each target area with identical abscissa, wherein j=1,2 ..., N, N table
Show the number of target area.
For example, for one group of abscissa on horizontal axis X, x1,x2,…,xM, wherein x1Corresponding first marginal point, x1In N
Corresponding N number of marginal point is in a target areaUse above-mentioned formula
It calculates on the longitudinal axis Y of N number of coordinateThe average value of coordinate, it is availableLikewise, can calculate
It obtainsTo obtain that there is identical abscissa x1,x2,…,xMM marginal point of N group each ordinate average value
It is specific to wrap the step of variance corresponding according to mean value calculation abscissa after obtaining the average value of ordinate
Include following steps:
The side of each ordinate of the marginal point in each target area with identical abscissa is calculated according to the following formula
Difference；Wherein, SiIndicate the variance of each ordinate of marginal point i,Indicate each target area
In with identical abscissa marginal point i each ordinate average value.
Obtaining abscissa x1,x2,…,xMM marginal point of N group each ordinate average valueLater, it counts
Calculate abscissa x1Corresponding variance S1,And it is denoted as (x1,S1).Likewise, calculating S2~SM, most
Available { (x eventually1,S1),(x2,S2)…(xM,SM)}。
In view of variance is obtained as the parameter for measuring camera stability for the ease of assessing camera stability from multi-angle
To more intuitive camera stability assessment as a result, generating the step of the stability assessment result of camera according to variance and preset threshold
Suddenly, comprising:
Maximum variance value, minimum variance value and mean of variance are determined according to variance；According to maximum variance value, minimum variance
Value, mean of variance and preset threshold generate the stability assessment result of camera.
By determining that maximum variance value, minimum variance value and mean of variance to describe camera fluctuation, help to provide
More accurate assessment result is analyzed maximum variance value, minimum variance value and mean of variance, is handled, final to combine in advance
If threshold value obtains more intuitive camera stability assessment result.Variance is to measure the amount of data sample fluctuation size, is calculated
The Y axis coordinate value variance result come is able to reflect the fluctuation situation of camera acquisition image, further reflects camera stability.
The step of determining maximum variance value, minimum variance value and mean of variance according to variance, comprising:
Maximum variance value, minimum variance value and mean of variance are determined according to the following formula；Smax=Max { S1,S2…SM,
Smin=Min { S1,S2…SM,Wherein, SmaxIndicate maximum variance value, SminIndicate minimum variance value,Table
Show that mean of variance, M indicate the number of marginal point in each target area.
The step of generating the stability assessment result of camera according to variance and preset threshold, comprising the following steps: will be maximum
The absolute value or minimum variance value of the difference of variance yields and mean of variance and the absolute value of the difference of mean of variance are used as and comment
Estimate parameter.
Assessing parameter can beOrAssessment parameter is also possible to according to maximum variance value, minimum
The parameter for the other forms that variance yields or mean of variance obtain can be adjusted, the embodiment of the present invention according to actual needs
Comparison is not especially limited.
Judge to assess whether parameter is greater than preset threshold, if so, determining that camera stability is unqualified；If not, determining
Camera qualified stability.
Assessment parameter describe the fluctuation of ordinate, if assessment parameter be greater than preset threshold, illustrate camera fluctuation compared with
Greatly, there are stability problem, can in high-acruracy survey task measurement accuracy and measurement stability affect greatly, answer
Otherwise the superior camera of other selection performance illustrates that camera fluctuates smaller, high stability, to high-acruracy survey knot
Fruit has an impact smaller, can choose the model camera.
In addition, it is necessary to which explanation, is obtaining data { (x1,S1),(x2,S2)…(xM,SM) and mean of variance after,
It can be used but not limited to line chart drawing tool and draw line chart, can intuitively observe camera stability according to line chart is
It is no that there are problems.The preferable camera assessment result broken line schematic diagram of stability shown in Figure 6 and stability shown in Fig. 7 compared with
The camera assessment result broken line schematic diagram of difference, wherein the longitudinal axis is variance yields, and horizontal axis is the abscissa value of marginal point, figure middle polyline
It is according to data { (x1,S1),(x2,S2)…(xM,SM) obtain, horizontal line is according to data in figureObtained scedastic line.Comparison diagram 6 and Fig. 7, in Fig. 6Quantity it is obviously few
In the second width line chartQuantity, and the mean value of Fig. 6Less than the mean value of the second width figure.
If the difference for assessing parameter and preset threshold is excessive and line chart inQuantity is more, variance SiDraw
Figure display effect is that the coordinate on scedastic line is more, illustrates that the model camera imaging stabilizing effect is poor, may be right
Measurement accuracy and measurement stability in high-acruracy survey task affect greatly, it should it is more excellent further to select performance
Camera.If the difference for assessing parameter and preset threshold is smaller and line chart inNegligible amounts, variance SiDrawing
Display effect is that the coordinate on scedastic line is less, illustrates that camera imaging stabilizing effect is preferable, to high-acruracy survey result
It has an impact smaller, it is proposed that select the model camera.If the difference for assessing parameter and preset threshold is larger but line chart inNegligible amounts, variance SiPlot and display effect be that coordinate on scedastic line is less, but has extremely individual points to occur
Larger situation is fluctuated in jump, at this time may be as caused by the factors such as electromagnetic interference, temperature, light source.It can be repeated several times and adopt
The image of collection target object is detected, and chooses new ROI region, and repeatedly measurement sees whether that there is also assessment parameters and pre-
If the difference of threshold value is larger but line chart inThe phenomenon that negligible amounts, illustrates camera imaging stability if not
There is no problem, can choose the model camera.Otherwise the superior camera of performance should further be selected.
In order to further ensure the accuracy of stability assessment result, this method may also comprise the following steps:: according to more
The target object of kind shape generates multiple stability assessment results of camera；Camera is determined according to multiple stability assessment results
Stability.
It, can be to the mesh of various shapes in order to avoid because photographic subjects object shapes are influencing caused by final assessment result
Mark object is shot, and generates stability assessment respectively to the target object of each shape as a result, final camera can be set
The condition that stability need to meet are as follows: the stability assessment result generated to the target object of each shape is qualification.
Camera stability assessment method, apparatus provided by the invention and electronic equipment pass through the N frame figure that arrives to continuous acquisition
The edge contour figure of photographic subjects is extracted as carrying out edge detection, calculates the side of the Y axis coordinate value of the same marginal point of N frame image
Difference.Because variance is to measure the amount of data sample fluctuation size, the Y axis coordinate value variance result calculated is able to reflect camera and adopts
The fluctuation situation for collecting image, further reflects camera stability.The embodiment of the present invention does not depend on special hardware device, uses
It is in extensive range.It is compared with the pixel value variation appraisal procedure based on acquisition image slices vegetarian refreshments, the embodiment of the present invention has used variance
Statistical significance, intuitively can effectively describe the problem, provide more accurate assessment result.Be based on angle point distribution transformation
Situation method is compared, and the embodiment of the present invention avoids the erroneous detection missing inspection situation in Corner Detection, improves camera stability assessment
Accuracy.The present invention can be used in high-precision commercial measurement task, good to a imaging effect of selection, reliable and stable, property
Camera that can be excellent provides technical support.
The embodiment of the present invention also provides a kind of camera stability assessment device, camera stability assessment shown in Figure 8
Apparatus structure schematic diagram, the device include:
Module 81 is obtained, for obtaining continuous multiframe edge contour image；It include phase in multiframe edge contour image
The edge contour of the target object of machine shooting；Computing module 82, for determining same marginal point in multiframe edge contour image
The variance of ordinate；Evaluation module 83, for the stability according to square error estimation camera.
Computing module is specifically used for: the identical region of selected pixels coordinate in multiframe edge contour image respectively obtains
Multiple target areas；It include the part edge profile of target object in multiple target areas；Respectively in each target area
One group of abscissa is generated, and corresponding one group of ordinate is generated with one group of edge in each target area of determination according to abscissa
Point；Wherein, the abscissa of corresponding edge point is identical in different groups；Calculate the variance of the ordinate of abscissa same edge point.
Calculate the average value of the corresponding each group marginal point ordinate of abscissa；According to the corresponding side of mean value calculation abscissa
Difference.
The average value of the corresponding each group marginal point ordinate of abscissa is calculated according to following formula:
Wherein,Indicate the average value of each ordinate of the marginal point i in each target area with identical abscissa, wherein i=
1,2 ..., M, M are the marginal point number for including in the corresponding one group of marginal point in a target area,Indicate each target area
In with identical abscissa marginal point i ordinate, wherein j=1,2 ..., N, N indicate target area number.According to such as
Lower formula calculates variance:Wherein, SiIndicate the variance of each ordinate of marginal point i,
Indicate the average value of each ordinate of the marginal point i in each target area with identical abscissa.
Module is obtained, is specifically used for: obtaining the continuous multiframe initial pictures of camera shooting；Respectively to continuous initial graph
As carrying out edge detection, continuous multiframe edge contour image is obtained.
Evaluation module is specifically used for: determining maximum variance value, minimum variance value and mean of variance according to variance；According to
Maximum variance value, minimum variance value, mean of variance generate the stability assessment result of camera.
Maximum variance value, minimum variance value and mean of variance: S are determined according to following formula according to variancemax=Max
{S1,S2…SM, Smin=Min { S1,S2…SM,Wherein, SmaxIndicate maximum variance value, SminIndicate minimum
Variance yields, S indicate that mean of variance, M indicate the number of marginal point in each target area.By maximum variance value and mean of variance
The absolute value or minimum variance value of the difference of value and the absolute value of the difference of mean of variance are as assessment parameter；Judgement assessment ginseng
Whether number is greater than preset threshold, if so, determining that camera stability is unqualified；If not, determining camera qualified stability.
Another structural schematic diagram of camera stability assessment device shown in Figure 9, the device can also include mentioning
Rising mould block 84, hoisting module is used for: multiple stability assessment results of camera are generated according to the target object of various shapes；According to
Multiple stability assessment results determine the stability of camera.
The technical effect of camera stability assessment device provided by the embodiment of the present invention, realization principle and generation is with before
It is identical to state camera stability assessment embodiment of the method, to briefly describe, Installation practice part does not refer to place, can refer to aforementioned
Corresponding contents in embodiment of the method.
The embodiment of the present invention also provides a kind of electronic equipment, and electronic devices structure schematic block diagram shown in Figure 10 should
Electronic equipment includes memory 91, processor 92, and the computer program that can be run on a processor is stored in memory, processing
The step of device realizes any of the above-described kind of method when executing computer program.
Electronic equipment provided in an embodiment of the present invention has phase with camera stability assessment method provided by the above embodiment
Same technical characteristic reaches identical technical effect so also can solve identical technical problem.
It is apparent to those skilled in the art that for convenience and simplicity of description, the electronics of foregoing description
The specific work process of equipment, can refer to corresponding processes in the foregoing method embodiment, and details are not described herein
The embodiment of the present invention also provide it is a kind of with processor can be performed non-volatile program code it is computer-readable
The step of medium, program code makes processor execute any of the above-described kind of method.
It should be understood by those skilled in the art that, the embodiment of the present invention can provide as method, system or computer program
Product.Therefore, complete hardware embodiment, complete software embodiment or reality combining software and hardware aspects can be used in the present invention
Apply the form of example.Moreover, it wherein includes the computer of computer usable program code that the present invention, which can be used in one or more,
The computer program implemented in usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.) produces
The form of product.
The present invention be referring to according to the method for the embodiment of the present invention with the flowchart and/or the block diagram of computer program product
Come what is described.It should be understood that can be realized by computer program instructions each flow and/or block in flowchart and/or the block diagram,
And the combination of the process and/or box in flowchart and/or the block diagram.These computer program instructions be can provide to general meter
Calculation machine, special purpose computer, Embedded Processor or other programmable data processing devices processor to generate a machine, make
It obtains and is generated by the instruction that computer or the processor of other programmable data processing devices execute for realizing in flow chart one
The device for the function of being specified in a process or multiple processes and/or one or more blocks of the block diagram.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates,
Enable the manufacture of device, the command device realize in one box of one or more flows of the flowchart and/or block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or
The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one
The step of function of being specified in a box or multiple boxes.
Finally, it should be noted that embodiment described above, only a specific embodiment of the invention, to illustrate the present invention
Technical solution, rather than its limitations, scope of protection of the present invention is not limited thereto, although with reference to the foregoing embodiments to this hair
It is bright to be described in detail, those skilled in the art should understand that: anyone skilled in the art
In the technical scope disclosed by the present invention, it can still modify to technical solution documented by previous embodiment or can be light
It is readily conceivable that variation or equivalent replacement of some of the technical features；And these modifications, variation or replacement, do not make
The essence of corresponding technical solution is detached from the spirit and scope of technical solution of the embodiment of the present invention, should all cover in protection of the invention
Within the scope of.Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. a kind of camera stability assessment method characterized by comprising
Obtain continuous multiframe edge contour image；It include the target object of camera shooting in the multiframe edge contour image
Edge contour；
Determine the variance of the ordinate of same marginal point in the multiframe edge contour image；
According to the stability of the square error estimation camera.
2. the method according to claim 1, wherein determining same marginal point in the multiframe edge contour image
Ordinate variance, comprising:
The identical region of selected pixels coordinate in the multiframe edge contour image respectively, obtains multiple target areas；It is described
It include the part edge profile of the target object in multiple target areas；
One group of abscissa is generated in each target area respectively, and corresponding one group vertical seat is generated according to the abscissa
It is marked with the one group of marginal point determined in each target area；Wherein, the abscissa of corresponding edge point is identical in different groups；
Calculate the variance of the ordinate of abscissa same edge point.
3. the method according to claim 1, wherein the step for obtaining continuous multiframe edge contour image
Suddenly, comprising:
Obtain the continuous multiframe initial pictures of camera shooting；
Edge detection is carried out to the continuous initial pictures respectively, obtains continuous multiframe edge contour image.
4. according to the method described in claim 2, it is characterized in that, calculate abscissa same edge point ordinate variance,
Include:
Calculate the average value of the corresponding each group marginal point ordinate of abscissa；
According to the corresponding variance of abscissa described in the mean value calculation.
5. according to the method described in claim 4, it is characterised by comprising:
The average value of the corresponding each group marginal point ordinate of the abscissa is calculated according to following formula:
Wherein,Indicate the average value of each ordinate of the marginal point i in each target area with identical abscissa,
Wherein, i=1,2 ..., M, M are the marginal point number for including in the corresponding one group of marginal point in a target area,Indicate each
The ordinate of marginal point i in the target area with identical abscissa, wherein j=1,2 ..., N, N indicate target area
Number；
Variance is calculated according to following formula:
Wherein, SiIndicate the variance of each ordinate of marginal point i,Indicate that there is identical horizontal seat in each target area
The average value of each ordinate of target marginal point i.
6. the method according to claim 1, wherein according to the stability of the square error estimation camera, comprising:
Maximum variance value, minimum variance value and mean of variance are determined according to the variance；
The stability assessment result of camera is generated according to the maximum variance value, the minimum variance value, the mean of variance.
7. according to the method described in claim 6, it is characterised by comprising:
Maximum variance value, minimum variance value and mean of variance are determined according to following formula according to the variance:
Smax=Max { S1,S2…SM, Smin=Min { S1,S2…SM,
Wherein, SmaxIndicate maximum variance value, SminIndicate minimum variance value,Indicate that mean of variance, M indicate each target area
The number of marginal point in domain；
According to the maximum variance value, the minimum variance value, the mean of variance generate camera stability assessment as a result,
Include:
By the absolute value or the minimum variance value of the maximum variance value and the difference of the mean of variance and the variance
The absolute value of the difference of average value is as assessment parameter；
Judge whether the assessment parameter is greater than preset threshold,
If so, determining that camera stability is unqualified；
If not, determining camera qualified stability.
8. a kind of camera stability assessment device characterized by comprising
Module is obtained, for obtaining continuous multiframe edge contour image；It include camera in the multiframe edge contour image
The edge contour of the target object of shooting；
Computing module, for determining the variance of the ordinate of same marginal point in the multiframe edge contour image；
Evaluation module, for the stability according to the square error estimation camera.
9. a kind of electronic equipment, including memory, processor, be stored in the memory to run on the processor
Computer program, which is characterized in that the processor realizes that the claims 1 to 7 are any when executing the computer program
The step of method described in item.
10. a kind of computer-readable medium for the non-volatile program code that can be performed with processor, which is characterized in that described
Program code makes the processor execute described any the method for claim 1-7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910535068.2A CN110225335B (en) | 2019-06-20 | 2019-06-20 | Camera stability evaluation method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910535068.2A CN110225335B (en) | 2019-06-20 | 2019-06-20 | Camera stability evaluation method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110225335A true CN110225335A (en) | 2019-09-10 |
| CN110225335B CN110225335B (en) | 2021-01-12 |
Family
ID=67814193
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910535068.2A Expired - Fee Related CN110225335B (en) | 2019-06-20 | 2019-06-20 | Camera stability evaluation method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110225335B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110955243A (en) * | 2019-11-28 | 2020-04-03 | 新石器慧通（北京）科技有限公司 | Travel control method, travel control device, travel control apparatus, readable storage medium, and mobile device |
| CN111246100A (en) * | 2020-01-20 | 2020-06-05 | Oppo广东移动通信有限公司 | Anti-shake parameter calibration method and device and electronic equipment |
| CN113365047A (en) * | 2021-08-10 | 2021-09-07 | 苏州维嘉科技股份有限公司 | Method and device for detecting repeated target-grabbing precision of camera and camera system |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101739693A (en) * | 2009-12-11 | 2010-06-16 | 中兴通讯股份有限公司 | Motion image display method and device |
| CN101895783A (en) * | 2009-05-18 | 2010-11-24 | 华晶科技股份有限公司 | Detection device for stability of digital video camera and digital video camera |
| CN103049911A (en) * | 2012-12-20 | 2013-04-17 | 成都理想境界科技有限公司 | Contour detection stability judging method and image searching method |
| CN105139404A (en) * | 2015-08-31 | 2015-12-09 | 广州市幸福网络技术有限公司 | Identification camera capable of detecting photographing quality and photographing quality detecting method |
| CN105844651A (en) * | 2016-04-14 | 2016-08-10 | 吴本刚 | Image analyzing apparatus |
| CN105933698A (en) * | 2016-04-14 | 2016-09-07 | 吴本刚 | Intelligent satellite digital TV program play quality detection system |
| US20170188022A1 (en) * | 2015-12-28 | 2017-06-29 | Automotive Research & Test Center | Calibration method for merging object coordinates and calibration board device using the same |
| US20180249142A1 (en) * | 2017-02-27 | 2018-08-30 | Intel Corporation | Field calibration of stereo cameras with a projector |
-
2019
- 2019-06-20 CN CN201910535068.2A patent/CN110225335B/en not_active Expired - Fee Related
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101895783A (en) * | 2009-05-18 | 2010-11-24 | 华晶科技股份有限公司 | Detection device for stability of digital video camera and digital video camera |
| CN101739693A (en) * | 2009-12-11 | 2010-06-16 | 中兴通讯股份有限公司 | Motion image display method and device |
| CN103049911A (en) * | 2012-12-20 | 2013-04-17 | 成都理想境界科技有限公司 | Contour detection stability judging method and image searching method |
| CN105139404A (en) * | 2015-08-31 | 2015-12-09 | 广州市幸福网络技术有限公司 | Identification camera capable of detecting photographing quality and photographing quality detecting method |
| US20170188022A1 (en) * | 2015-12-28 | 2017-06-29 | Automotive Research & Test Center | Calibration method for merging object coordinates and calibration board device using the same |
| CN105844651A (en) * | 2016-04-14 | 2016-08-10 | 吴本刚 | Image analyzing apparatus |
| CN105933698A (en) * | 2016-04-14 | 2016-09-07 | 吴本刚 | Intelligent satellite digital TV program play quality detection system |
| US20180249142A1 (en) * | 2017-02-27 | 2018-08-30 | Intel Corporation | Field calibration of stereo cameras with a projector |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110955243A (en) * | 2019-11-28 | 2020-04-03 | 新石器慧通（北京）科技有限公司 | Travel control method, travel control device, travel control apparatus, readable storage medium, and mobile device |
| CN110955243B (en) * | 2019-11-28 | 2023-10-20 | 新石器慧通（北京）科技有限公司 | Travel control method, apparatus, device, readable storage medium, and mobile apparatus |
| CN111246100A (en) * | 2020-01-20 | 2020-06-05 | Oppo广东移动通信有限公司 | Anti-shake parameter calibration method and device and electronic equipment |
| CN111246100B (en) * | 2020-01-20 | 2022-03-18 | Oppo广东移动通信有限公司 | Anti-shake parameter calibration method and device and electronic equipment |
| CN113365047A (en) * | 2021-08-10 | 2021-09-07 | 苏州维嘉科技股份有限公司 | Method and device for detecting repeated target-grabbing precision of camera and camera system |
| CN113365047B (en) * | 2021-08-10 | 2021-11-02 | 苏州维嘉科技股份有限公司 | Method and device for detecting repeated target-grabbing precision of camera and camera system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110225335B (en) | 2021-01-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US9787960B2 (en) | Image processing apparatus, image processing system, image processing method, and computer program | |
| US8600147B2 (en) | System and method for remote measurement of displacement and strain fields | |
| US10733751B2 (en) | Displacement detecting apparatus and displacement detecting method | |
| CN106097361A (en) | A kind of defective area detection method and device | |
| CN105424726B (en) | Luminescent panel detection method based on machine vision | |
| CN110225335A (en) | Camera stability assessment method and device | |
| CN106412573A (en) | Method and device for detecting lens stain | |
| US20180108143A1 (en) | Height measuring system and method | |
| CN110349195A (en) | A kind of target object 3D measurement parameter acquisition methods, system and storage medium based on depth image | |
| CN106530271B (en) | A kind of infrared image conspicuousness detection method | |
| JP2015524915A (en) | 3D information processing apparatus and method | |
| CN108074237B (en) | Image definition detection method and device, storage medium and electronic equipment | |
| CN110519588A (en) | For the Approach for detecting image sharpness of focusing, device and photographic device | |
| CN109655234A (en) | A kind of automated testing method being directed to camera | |
| CN110349216A (en) | Container method for detecting position and device | |
| CN104574312A (en) | Method and device of calculating center of circle for target image | |
| JP2011196860A (en) | Object dimension measuring method and object dimension measuring device using distance image camera | |
| CN108871197B (en) | Displacement field measuring method, device, equipment and storage medium for material surface | |
| CN112184809A (en) | Relative pose estimation method, device, electronic device and medium | |
| CN108507476B (en) | Displacement field measuring method, device, equipment and storage medium for material surface | |
| CN105427282A (en) | Method and device for testing 3D positioning accuracy | |
| JP2020512536A (en) | System and method for 3D profile determination using model-based peak selection | |
| US8102516B2 (en) | Test method for compound-eye distance measuring apparatus, test apparatus, and chart used for the same | |
| CN108781280B (en) | Test method, test device and terminal | |
| CN106969707B (en) | A kind of detection device and its control method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20210112 Termination date: 20210620 |