CN110319933A - A kind of light source light spectrum optimization method based on CAM02-UCS colored quantum noise - Google Patents
A kind of light source light spectrum optimization method based on CAM02-UCS colored quantum noise Download PDFInfo
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- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
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Abstract
The present invention provides a kind of light source light spectrum optimization methods based on CAM02-UCS colored quantum noise, comprising: initially sets up imaging model, calculates the original pixel value of image, and detect to the pixel coordinate of target area using conspicuousness detection method；Then the pixel point set for the target area that will test out is mapped in CAM02-UCS colored quantum noise, and establishes the objective function for maximizing value of chromatism, and then utilizes the genetic algorithm optimization objective function, to obtain maximizing the pixel value of value of chromatism；Optimal light source light spectrum power is finally found out according to the pixel value.The beneficial effects of the present invention are: technical solution combination LED light source spectral model proposed by the invention and optimization algorithm, and colour gamut model this intuitive description method, change chroma and form and aspect two important visual color factors by optimization light source light spectrum, can intuitively find out the effect of light source optimization.
Description
Technical field
The present invention relates to image optimization field more particularly to a kind of light source light spectrum based on CAM02-UCS colored quantum noise are excellent
Change method.
Background technique
In recent years, with the emergence of low cost, high-performance, efficient image processing system, Machine Vision Detection
Product appearance, defect location, in terms of be widely used.This mainly have benefited from CCD camera sensitivity,
The raising of computer CPU speed, image pick-up card acquisition speed.On the other hand, due to software and hardware price reduction, user is increasingly
It is more, there is extensive understanding for the importance of machine-vision lighting system, the investment in terms of lighting source is more and more, therefore
It is also more and more deep for the research of machine-vision lighting system.NI Vision Builder for Automated Inspection acquires target using video camera, camera etc.
Corresponding picture signal is handled it by image processing system, realizes detection, tracking and knowledge of the computer to target
, not final to realize the detection to the automation control, product defects of instrument and equipment, improve quality and operational efficiency.
Picture quality and programmed algorithm determine the processing speed and quality of processing system, image sheet in NI Vision Builder for Automated Inspection
The quality of body is extremely crucial to entire vision system.And light source then be influence NI Vision Builder for Automated Inspection image level an important factor for,
Because it directly affect input data quality and at least 30% application effect.Picture quality is largely by target week
The light environment that encloses, target object surface material, object placement position are determined.Good light environment can effectively dash forward
The identification target of object out can be such that target information and background information in image obtains most by light source Lighting Design appropriate
Good separation substantially reduces the algorithm difficulty of image processing, improves simultaneously to obtain the high quality graphic that computer can be analyzed
The precision and reliability of system.It can be seen that the quality of illumination system layout be directly related to acquisition equipment can obtain it is high-quality
The image of amount, good light source are the guarantees of NI Vision Builder for Automated Inspection energy efficient operation.The main purpose of illumination system layout be with
Light is irradiated to detection target surface, the characteristic information that prominent measured target needs to detect, it may be said that shine by most suitable mode
Bright system is the key that entire NI Vision Builder for Automated Inspection portion.
One outstanding lighting system can be such that the acquisition image object information of measured target separates with background information, thus
Simplify subsequent analysis, can be related to whole system operate normally.The illumination of mistake can cause the problem of many post-processings, example
Many important informations can be made to lose as light intensity is excessively high, shade can make the detection of overall size generate error.In industrial detection due to
There are miscellaneous test objects, stablize good image to obtain, it is necessary to most close to select for different targets
Suitable lighting system even needs various light sources difference layout to combine sometimes, needs to obtain by a large amount of experimental test
Optimal combination of light sources and layout out, it is seen that the research of machine-vision lighting system is field of machine vision one highly important
Project.As a kind of very useful technology, it is widely used in the fields such as medical image, lossless detection, remote sensing survey, especially
Some fields for surmounting visual threshold can be used to object analysis color abnormal phenomenon because of caused by the mixing of different material,
Such as food pollution, resource detection, material evidence identification, prints anti-fake, diseases and pests of agronomic crop at skin disease.
Traditional machine vision is mostly that the pretreatments such as smooth, filtering, contrast enhancing are carried out to original image to obtain
More specific scene description information.Pretreatment not can increase the intrinsic information of image data, the only original image of high quality
Just contain the information that more can be used for further analyzing.Original image is obtained by lighting condition and camera parameter (intensity, color
Color and relative position etc.) strong influence.By improving lighting condition, to promote the quality (information content) of original image, for
The processing of later period machine vision has very important significance.
The object that human eye is seen is that the light on surface is reflected into people in the eyes, and equally, phase function takes point on object
Image, be because the light put is captured by the camera on object, we will study the quality of image it is necessary to imaging process
And its variation of brightness is studied.The purpose for finding optimal illumination be exactly actively construct an optimal computer vision at
As environment, imaging circumstances are better, and obtained picture quality is higher.Most machine vision algorithm research, all puts center of gravity
High quality graphic is directly acquired more directly effectively to how handling on low-quality visual pattern, however by optimizing illumination,
Cost is also lower than subsequent many and diverse image procossing very much.
Due to being required to meet high color rendering index (CRI) simultaneously under different-colour, simulation is considerably complicated and difficult, therefore, research report
Road is very few.Although there are many existing bright technical research of care, comprehensive study light source light spectrum characteristic, collection image quality judge skill
Art, final establish do not have satisfactory research achievement also with optimization light source light spectrum vision-based detection lighting model.
Summary of the invention
To solve the above-mentioned problems, the light source light spectrum optimization based on CAM02-UCS colored quantum noise that the present invention provides a kind of
A kind of method, applied in light source light spectrum optimization system based on CAM02-UCS colored quantum noise；
A kind of light source light spectrum optimization system based on CAM02-UCS colored quantum noise includes: light-source box, for generating light
Source；EO-1 hyperion camera, for acquiring body surface spectral reflectivity；CCD camera, for acquiring subject image；
A kind of light source light spectrum optimization method based on CAM02-UCS colored quantum noise, specifically comprises the following steps:
S101: light-source box launches the target object that any visible light source irradiation is located in light-source box；And pass through bloom
The spectral reflectivity for composing phase machine testing target object surface at this time, acquires subject image by CCD camera；
S102: by imaging model, the pixel collection G of the subject image is calculatedC(x,y)；Wherein, mould is imaged
Shown in the calculation formula of type such as formula (1):
Gc(x, y)=∫ Rc(λ) S (x, y, λ) C (λ) d λ (C={ R, G, B }, (x, y) ∈ RIO) (1)
In above formula, R (λ) represents the spectral reflectivity of target object surface；The variation range of λ is [4000nm, 700nm]；S
(x, y, λ) represents the spectral power distribution for the visible light source that light-source box is emitted；C (λ) represents the spectrum sensitive letter of CCD camera
Number, is known CCD camera preset parameter, and (x, y) is some pixel coordinate in the subject image；Wherein, pixel point set
Close GCIt include the pixel of target object region and the picture of non-targeted object region in the subject image in (x, y)
Vegetarian refreshments；
S103: conspicuousness detection is carried out to the subject image using the conspicuousness detection method based on contrast, is obtained
The pixel collection GCThe object pixel point set of all pixels point composition of target object region in (x, y)；
S104: all pixels point that the target pixel points that conspicuousness detects are concentrated is mapped to CAM02-UCS
In colored quantum noise, the homogeneous color space that the target pixel points concentrate all pixels point in CAM02-UCS colored quantum noise is obtained
In corresponding first three-dimensional coordinate point set；
Some first three-dimensional coordinate point (J is concentrated for first three-dimensional coordinate point2,aM2,bM2), definition and the one or three
Dimension maximum second three-dimensional coordinate point of coordinate points value of chromatism is (J1,aM1,bM1), and establish as value of chromatism shown in formula (2) is excellent
Change objective function Δ E；
The objective function Δ E is optimized using genetic algorithm, is obtained with the first three-dimensional coordinate point value of chromatism most
Coordinate value (the J of the second big three-dimensional coordinate point1,aM1,bM1)；And then first three-dimensional coordinate point is calculated using this method
Corresponding second three-dimensional coordinate point of all first three-dimensional coordinate points is concentrated, the two or three of all second three-dimensional coordinate point compositions is obtained
Tie up coordinate point set；
S105: each second three-dimensional coordinate point that second three-dimensional coordinate point is concentrated is reduced to corresponding pixel
(x1, y1), and then compositional optimization pixel collection GC(x1,y1)；By GC(x1, y1) is brought into formula (1), and keeps step
The value of spectral reflectivity R (λ) and spectrum sensitive function C (λ) in S101 are constant, to be calculated and the subject image
The corresponding spectral power distribution of the maximum pixel point set of preimage vegetarian refreshments value of chromatism, that is, optimize after spectral power distribution S (x1, y1,
λ)；
S106: so that the light-source box is launched corresponding light source according to the spectral power after the optimization, be radiated at object
On, so that the color of the subject image of CCD camera acquisition is distincter, visual effect is more excellent.
Further, the light-source box includes various light sources, and can mix various light sources, launches any spectrum
The light source of power distribution.
Further, the various light sources are LED light source.
Further, in step S103, using the conspicuousness detection method (HC) based on contrast to the subject image
When carrying out conspicuousness detection, shown in the saliency value calculation formula such as formula (3) of each pixel:
In above formula, any some pixel IkSaliency value S (Ik) it is that the pixel is complete in the entire subject image
Office's contrast, i.e. pixel IkWith other all pixels points IiSum of the distance in color；IiValue range be [0,
255]；Formula (3) is converted into more intuitive color value representation formula, such as formula (4):
In above formula, ci is pixel IkColor value, be known quantity；N is different pixels color value in the subject image
Total quantity, fjIt is the frequency that pixel color value cj occurs.
Further, in step S104, lightness J ' and chromaticity in the homogeneous color space that CAM02-UCS colored quantum noise is established
Coordinate aM、bMCalculation formula such as formula (5) shown in:
In above formula,J, M and h is respectively the lightness, view chroma and color of colored quantum noise
Phase angle.
Technical solution provided by the invention has the benefit that technical solution combination LED light proposed by the invention
This intuitive description method of source spectral model and optimization algorithm and colour gamut model, passes through optimization light source light spectrum and changes chroma
With form and aspect two important visual color factors, the effect of light source optimization can be intuitively found out.
Detailed description of the invention
Present invention will be further explained below with reference to the attached drawings and examples, in attached drawing:
Fig. 1 is a kind of process of the light source light spectrum optimization method based on CAM02-UCS colored quantum noise in the embodiment of the present invention
Figure.
Specific embodiment
For a clearer understanding of the technical characteristics, objects and effects of the present invention, now control attached drawing is described in detail
A specific embodiment of the invention.
Implementation of the invention provides a kind of light source light spectrum optimization method based on CAM02-UCS colored quantum noise, is applied to
In a kind of light source light spectrum optimization system based on CAM02-UCS colored quantum noise；It is described a kind of based on CAM02-UCS colored quantum noise
Light source light spectrum optimization system includes: light-source box, for generating light source；EO-1 hyperion camera, for acquiring body surface spectral reflectance
Rate；CCD camera, for acquiring subject image；
Referring to FIG. 1, Fig. 1 is a kind of light source light spectrum optimization based on CAM02-UCS colored quantum noise in the embodiment of the present invention
The flow chart of method, specifically comprises the following steps:
S101: light-source box launches the target object that any visible light source irradiation is located in light-source box；And pass through bloom
The spectral reflectivity for composing phase machine testing target object surface at this time, acquires subject image by CCD camera；
S102: by imaging model, the pixel collection G of the subject image is calculatedC(x,y)；Wherein, mould is imaged
Shown in the calculation formula of type such as formula (1):
Gc(x, y)=∫ Rc(λ) S (x, y, λ) C (λ) d λ (C={ R, G, B }, (x, y) ∈ RIO) (1)
In above formula, R (λ) represents the spectral reflectivity of target object surface；The variation range of λ is [4000nm, 700nm]；S
(x, y, λ) represents the spectral power distribution for the visible light source that light-source box is emitted；C (λ) represents the spectrum sensitive letter of CCD camera
Number, is known CCD camera preset parameter, and (x, y) is some pixel coordinate in the subject image；Wherein, pixel point set
Close GCIt include the pixel of target object region and the picture of non-targeted object region in the subject image in (x, y)
Vegetarian refreshments；
S103: carrying out conspicuousness detection to the subject image using the conspicuousness detection method (HC) based on contrast,
Obtain the pixel collection GCThe object pixel point set of all pixels point composition of target object region in (x, y)；
S104: all pixels point that the target pixel points that conspicuousness detects are concentrated is mapped to CAM02-UCS
In colored quantum noise, the homogeneous color space that the target pixel points concentrate all pixels point in CAM02-UCS colored quantum noise is obtained
In corresponding first three-dimensional coordinate point set；
Some first three-dimensional coordinate point (J is concentrated for first three-dimensional coordinate point2,aM2,bM2), definition and the one or three
Dimension maximum second three-dimensional coordinate point of coordinate points value of chromatism is (J1,aM1,bM1), and establish as value of chromatism shown in formula (2) is excellent
Change objective function Δ E；
The objective function Δ E is optimized using genetic algorithm, is obtained with the first three-dimensional coordinate point value of chromatism most
Coordinate value (the J of the second big three-dimensional coordinate point1,aM1,bM1)；And then first three-dimensional coordinate point is calculated using this method
Corresponding second three-dimensional coordinate point of all first three-dimensional coordinate points is concentrated, the two or three of all second three-dimensional coordinate point compositions is obtained
Tie up coordinate point set；
S105: each second three-dimensional coordinate point that second three-dimensional coordinate point is concentrated is reduced to corresponding pixel
(x1, y1), and then compositional optimization pixel collection GC(x1,y1)；By GC(x1, y1) is brought into formula (1), and keeps step
The value of spectral reflectivity R (λ) and spectrum sensitive function C (λ) in S101 are constant, to be calculated and the subject image
The corresponding spectral power distribution of the maximum pixel point set of preimage vegetarian refreshments value of chromatism, that is, optimize after spectral power distribution S (x1, y1,
λ)；
S106: so that the light-source box is launched corresponding light source according to the spectral power after the optimization, be radiated at object
On, so that the color of the subject image of CCD camera acquisition is distincter, visual effect is more excellent.
In embodiments of the present invention, the visible light source that light-source box is launched in step S101 is D65 solar source.
The light-source box includes various light sources, and can mix various light sources, launches any spectral power distribution
Light source.
The various light sources are LED light source.
In step S103, conspicuousness is carried out to the subject image using the conspicuousness detection method (HC) based on contrast
When detection, shown in the saliency value calculation formula such as formula (3) of each pixel:
In above formula, any some pixel IkSaliency value S (Ik) it is that the pixel is complete in the entire subject image
Office's contrast, i.e. pixel IkWith other all pixels points IiSum of the distance in color；IiValue range be [0,
255]；Formula (3) is converted into more intuitive color value representation formula, such as formula (4):
In above formula, ci is pixel IkColor value, be known quantity；N is different pixels color value in the subject image
Total quantity, fjIt is the frequency that pixel color value cj occurs.
In step S104, lightness J ' and chromaticity coordinate a in the homogeneous color space that CAM02-UCS colored quantum noise is establishedM、bM
Calculation formula such as formula (5) shown in:
In above formula,J, M and h is respectively the lightness, view chroma and color of colored quantum noise
Phase angle.
The beneficial effects of the present invention are: technical solution combination LED light source spectral model proposed by the invention and optimization are calculated
This intuitive description method of method and colour gamut model, passes through optimization light source light spectrum and changes two important views of chroma and form and aspect
Feel color factor, can intuitively find out the effect of light source optimization.
The foregoing is merely presently preferred embodiments of the present invention, is not intended to limit the invention, it is all in spirit of the invention and
Within principle, any modification, equivalent replacement, improvement and so on be should all be included in the protection scope of the present invention.
Claims (5)
1. a kind of light source light spectrum optimization method based on CAM02-UCS colored quantum noise is applied to a kind of based on CAM02-UCS color looks
In the light source light spectrum optimization system of model；It is characterized by: a kind of light source light spectrum based on CAM02-UCS colored quantum noise is excellent
Change system includes: light-source box, for generating light source；EO-1 hyperion camera, for acquiring body surface spectral reflectivity；CCD camera,
For acquiring subject image；
A kind of light source light spectrum optimization method based on CAM02-UCS colored quantum noise, specifically comprises the following steps:
S101: light-source box launches the target object that any visible light source irradiation is located in light-source box；And pass through EO-1 hyperion phase
The spectral reflectivity of machine testing target object surface at this time, acquires subject image by CCD camera；
S102: by imaging model, the pixel collection G of the subject image is calculatedC(x,y)；Wherein, imaging model
Shown in calculation formula such as formula (1):
Gc(x, y)=∫ Rc(λ) S (x, y, λ) C (λ) d λ (C={ R, G, B }, (x, y) ∈ RIO) (1)
In above formula, R (λ) represents the spectral reflectivity of target object surface；The variation range of λ is [4000nm, 700nm]；S(x,
Y, λ) represent the spectral power distribution of the visible light source that light-source box is emitted；C (λ) represents the spectrum sensitive function of CCD camera,
For known CCD camera preset parameter, (x, y) is some pixel coordinate in the subject image；Wherein, pixel collection GC
It include the pixel of target object region and the pixel of non-targeted object region in the subject image in (x, y)
Point；
S103: conspicuousness detection is carried out to the subject image using the conspicuousness detection method based on contrast, is obtained described
Pixel collection GCThe object pixel point set of all pixels point composition of target object region in (x, y)；
S104: all pixels point that the target pixel points that conspicuousness detects are concentrated is mapped to CAM02-UCS color looks
In model, obtains the target pixel points and concentrate all pixels point right in the homogeneous color space of CAM02-UCS colored quantum noise
The the first three-dimensional coordinate point set answered；
Some first three-dimensional coordinate point (J is concentrated for first three-dimensional coordinate point2,aM2,bM2), definition and the first three-dimensional seat
Maximum second three-dimensional coordinate point of punctuate value of chromatism is (J1,aM1,bM1), and establish the value of chromatism as shown in formula (2) and optimize mesh
Scalar functions Δ E；
The objective function Δ E is optimized using genetic algorithm, is obtained maximum with the first three-dimensional coordinate point value of chromatism
Coordinate value (the J of second three-dimensional coordinate point1,aM1,bM1)；And then first three-dimensional coordinate point is calculated using this method and is concentrated
Corresponding second three-dimensional coordinate point of all first three-dimensional coordinate points, obtain all second three-dimensional coordinate points compositions second three-dimensional sit
Punctuate collection；
S105: by each second three-dimensional coordinate point that second three-dimensional coordinate point is concentrated be reduced to corresponding pixel (x1,
), and then compositional optimization pixel collection G y1C(x1,y1)；By GC(x1, y1) is brought into formula (1), and keeps step S101
In spectral reflectivity R (λ) and spectrum sensitive function C (λ) value it is constant, so that the preimage with the subject image be calculated
The corresponding spectral power distribution of the maximum pixel point set of vegetarian refreshments value of chromatism, that is, the spectral power distribution S (x1, y1, λ) after optimizing；
S106: making the light-source box launch corresponding light source according to the spectral power after the optimization, be radiated on object, with
Keep the color of the subject image of the CCD camera acquisition distincter, visual effect is more excellent.
2. a kind of light source light spectrum optimization method based on CAM02-UCS colored quantum noise as described in claim 1, feature exist
In: the light-source box includes various light sources, and can mix various light sources, launches the light of any spectral power distribution
Source.
3. a kind of light source light spectrum optimization method based on CAM02-UCS colored quantum noise as claimed in claim 2, feature exist
In: the various light sources are LED light source.
4. a kind of light source light spectrum optimization method based on CAM02-UCS colored quantum noise as described in claim 1, feature exist
In: in step S103, conspicuousness detection is carried out to the subject image using the conspicuousness detection method (HC) based on contrast
When, shown in the saliency value calculation formula such as formula (3) of each pixel:
In above formula, any some pixel IkSaliency value S (Ik) it is that the overall situation of the pixel in the entire subject image is right
Than degree, i.e. pixel IkWith other all pixels points IiSum of the distance in color；IiValue range be [0,255]；It will
Formula (3) is converted to more intuitive color value representation formula, such as formula (4):
In above formula, ci is pixel IkColor value, be known quantity；N is the sum of different pixels color value in the subject image
Amount, fjIt is the frequency that pixel color value cj occurs.
5. a kind of light source light spectrum optimization method based on CAM02-UCS colored quantum noise as described in claim 1, feature exist
In: in step S104, lightness J ' and chromaticity coordinate a in the homogeneous color space that CAM02-UCS colored quantum noise is establishedM、bMCalculating
Shown in formula such as formula (5):
In above formula,J, M and h is respectively the lightness, view chroma and hue angle of colored quantum noise.
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|---|---|---|---|---|
| CN112179623A (en) * | 2020-09-17 | 2021-01-05 | 一汽解放汽车有限公司 | Method, apparatus, system, device and medium for measuring camouflage contrast of coating |
| CN112747903A (en) * | 2020-12-28 | 2021-05-04 | 南京林业大学 | Optimal light source spectral power determination method based on colorimetry color replication |
| CN114812820A (en) * | 2022-06-23 | 2022-07-29 | 东莞市沃德普自动化科技有限公司 | Color difference detection method and system |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112179623A (en) * | 2020-09-17 | 2021-01-05 | 一汽解放汽车有限公司 | Method, apparatus, system, device and medium for measuring camouflage contrast of coating |
| CN112747903A (en) * | 2020-12-28 | 2021-05-04 | 南京林业大学 | Optimal light source spectral power determination method based on colorimetry color replication |
| CN112747903B (en) * | 2020-12-28 | 2022-07-26 | 南京林业大学 | Optimal light source spectral power determination method based on colorimetry color replication |
| CN114812820A (en) * | 2022-06-23 | 2022-07-29 | 东莞市沃德普自动化科技有限公司 | Color difference detection method and system |
| CN114812820B (en) * | 2022-06-23 | 2022-10-14 | 东莞市沃德普自动化科技有限公司 | Color difference detection method and system |
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| CN110319933B (en) | 2020-09-04 |
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