CN105472361B - A kind of method and system of projector image fluorescence processing - Google Patents
A kind of method and system of projector image fluorescence processing Download PDFInfo
- Publication number
- CN105472361B CN105472361B CN201510810937.XA CN201510810937A CN105472361B CN 105472361 B CN105472361 B CN 105472361B CN 201510810937 A CN201510810937 A CN 201510810937A CN 105472361 B CN105472361 B CN 105472361B
- Authority
- CN
- China
- Prior art keywords
- image
- gray
- value
- ambient light
- pixel
- 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.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 60
- 238000005286 illumination Methods 0.000 claims abstract description 60
- 238000004043 dyeing Methods 0.000 claims abstract description 48
- 230000007797 corrosion Effects 0.000 claims abstract description 39
- 238000005260 corrosion Methods 0.000 claims abstract description 39
- 230000004927 fusion Effects 0.000 claims abstract description 16
- 238000001514 detection method Methods 0.000 claims abstract description 15
- 239000011159 matrix material Substances 0.000 claims description 30
- 230000003287 optical effect Effects 0.000 claims description 12
- 239000000284 extract Substances 0.000 claims description 6
- 238000004364 calculation method Methods 0.000 claims description 5
- 238000010586 diagram Methods 0.000 description 4
- 239000000975 dye Substances 0.000 description 3
- 230000008030 elimination Effects 0.000 description 3
- 238000003379 elimination reaction Methods 0.000 description 3
- 238000000605 extraction Methods 0.000 description 3
- 239000003086 colorant Substances 0.000 description 2
- 238000004040 coloring Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000002073 fluorescence micrograph Methods 0.000 description 2
- 241000276489 Merlangius merlangus Species 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000011084 recovery Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/20—Image enhancement or restoration using local operators
- G06T5/30—Erosion or dilatation, e.g. thinning
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N9/00—Details of colour television systems
- H04N9/12—Picture reproducers
- H04N9/31—Projection devices for colour picture display, e.g. using electronic spatial light modulators [ESLM]
- H04N9/3179—Video signal processing therefor
- H04N9/3182—Colour adjustment, e.g. white balance, shading or gamut
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/70—Denoising; Smoothing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/12—Edge-based segmentation
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N9/00—Details of colour television systems
- H04N9/12—Picture reproducers
- H04N9/31—Projection devices for colour picture display, e.g. using electronic spatial light modulators [ESLM]
-
- 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
- G06T2207/10064—Fluorescence image
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Multimedia (AREA)
- Signal Processing (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Image Analysis (AREA)
- Image Processing (AREA)
Abstract
The invention discloses a kind of method and system of projector image fluorescence processing, method includes obtaining projected image；Gray proces are carried out to projected image, obtain gray level image；From gray level image, contour images are extracted, and corrosion expansion process is carried out to contour images；The intensity of illumination of the ambient light of the ambient light for the view field that detection projection module is projected, and dyeing Fuzzy Processing is carried out to the image after corrosion expansion process according to the intensity of illumination of ambient light；By contour images and carry out the image after dyeing Fuzzy Processing and carry out fusion treatment obtaining fluoroscopic image；Projection module is set to project fluoroscopic image to view field.Through the above way, the present invention can realize that projection module projects fluoroscopic image, fluoroscopic image can make a distinction with ambient light, user is facilitated to watch fluoroscopic image, the other present invention can also be according to the intensity of illumination of the ambient light of the view field of projection module, adjust the Fluoresceinated degree of fluoroscopic image so that fluoroscopic image more conforms to project the needs of environment.
Description
Technical field
The present invention relates to projection art, more particularly to a kind of method and system of projector image fluorescence processing.
Background technology
Projecting apparatus (also known as projector), be it is a kind of can be by the equipment on image or VIDEO PROJECTION to curtain, it is projected to
Either several times are presented in the case where keeping definition in video to image on curtain or decades of times is amplified, and are convenient for people to see
See, also give the open visual field of people, therefore, projecting apparatus is welcome by user deeply.
Because projecting apparatus is that image or video be projected directly at into curtain, the projection effect of shown projected image on curtain
Fruit can be where by curtain the ambient light in region influenceed, if ambient light is too strong, ambient light can cover the throwing of projecting apparatus outgoing
Shadow light so that curtain is in the effect regarding whiting, and user can not watch projected picture, if ambient light is excessively weak, what curtain was shown
Projected picture is excessively dark, people is not understood and obtain the information that projected image is reflected.
The content of the invention
, can the present invention solves the technical problem of a kind of method and system of projector image fluorescence processing are provided
Realize that projection module projects fluoroscopic image, wherein, fluoroscopic image can make a distinction with ambient light, facilitate user to watch fluorogram
Picture, and the glimmering of fluoroscopic image can be adjusted according to the intensity of illumination of the ambient light of the ambient light of the view field of projection module
Photochemical degree so that fluoroscopic image more conforms to project the needs of environment.
In order to solve the above technical problems, one aspect of the present invention is：A kind of projector image fluorescence is provided
The method of processing, including obtain projected image；Gray proces are carried out to the projected image, obtain gray level image；From the ash
Image is spent, extracts contour images, and corrosion expansion process is carried out to the contour images；The projection module is detected to be projected
View field ambient light intensity of illumination, and according to the intensity of illumination of the ambient light to the image after corrosion expansion process
Carry out dyeing Fuzzy Processing；By the contour images and carry out the image after dyeing Fuzzy Processing and carry out fusion treatment obtaining fluorescence
Image；The projection module is set to project the fluoroscopic image to the view field.
Wherein, the step of carrying out gray proces to the projected image, obtaining gray level image includes：Obtain the perspective view
The rgb value of the pixel of picture；According to the rgb value of the pixel of the projected image, gray value is calculated；By the projected image
The rgb value of pixel is replaced into the gray value, obtains the gray level image.
Wherein, according to the rgb value of the pixel, the calculation formula for calculating the gray value of the pixel is：
Gray=α * R+ β * G+ γ * B
The Gray is gray value, and the R is the color value of red component in the rgb value of the pixel, and the G is institute
State the color value of the rgb value Green component of pixel, the B be the pixel rgb value in blue component color value,
The α is the numerical value more than 0.2 and less than 0.4, and the β is the numerical value more than 0.5 and less than 0.7, and the γ is size
0.1 and less than 0.3 numerical value.
Wherein, the intensity of illumination according to the ambient light carries out dyeing fuzzy place to the image after corrosion expansion process
The step of reason, includes：Dyeing processing is first carried out to the image after the corrosion expansion process；It is strong according to the illumination of the ambient light
The matrix template of degree selection Gaussian Blur processing, between the matrix template of the Gaussian Blur processing and the intensity of illumination of ambient light
With predetermined positive correlation；The matrix template that image after the dyeing is handled with selected Gaussian Blur is rolled up
Product computing, obtain the image after the dyeing Fuzzy Processing.
Wherein, described the step of carrying out corrosion expansion process to the contour images, includes：Extract in the contour images
The contour edge of each object；The burr of the contour edge is eliminated, and expands the contour edge, and fills up the profile
The blank parts of each interior of articles in image.
In order to solve the above technical problems, another technical solution used in the present invention is：A kind of projection fluoroscopic image is provided
System, including projection module, optical detection device and processor, the processor connects with projection module and optical detection device respectively
Connect；The processor is used for：Obtain projected image；Gray proces are carried out to the projected image, obtain gray level image；From described
Gray level image, contour images are extracted, and corrosion expansion process is carried out to the contour images；Detected by the optical detection device
The intensity of illumination of the ambient light for the view field that the projection module is projected, and according to the intensity of illumination pair of the ambient light
Image after corrosion expansion process carries out dyeing Fuzzy Processing；By the contour images and carry out the image after dyeing Fuzzy Processing
Carry out fusion treatment and obtain fluoroscopic image；The fluoroscopic image is sent to the projection module, and makes the projection module to institute
State view field and project the fluoroscopic image.
Wherein, the processor carries out gray proces to the projected image, and the step of obtaining gray level image includes：Obtain
The rgb value of the pixel of the projected image；According to the rgb value of the pixel of the projected image, gray value is calculated；By described in
The rgb value of the pixel of projected image is replaced into the gray value, obtains the gray level image.
Wherein, according to the rgb value of the pixel, the calculation formula for calculating the gray value of the pixel is：
Gray=α * R+ β * G+ γ * B
The Gray is gray value, and the R is the color value of red component in the rgb value of the pixel, and the G is institute
State the color value of the rgb value Green component of pixel, the B be the pixel rgb value in blue component color value,
The α is the numerical value more than 0.2 and less than 0.4, and the β is the numerical value more than 0.5 and less than 0.7, and the γ is size
0.1 and less than 0.3 numerical value.
Wherein, the processor dyes according to the intensity of illumination of the ambient light to the image after corrosion expansion process
The step of Fuzzy Processing, includes：Dyeing processing is carried out to the image after the corrosion expansion process；According to the light of the ambient light
According to the matrix template of intensity selection Gaussian Blur processing, the matrix template of the Gaussian Blur processing and the intensity of illumination of ambient light
Between there is predetermined positive correlation；The matrix template that image after the dyeing is handled with selected Gaussian Blur is entered
Row convolution algorithm, obtain the image after the dyeing Fuzzy Processing.
The step of wherein described processor carries out corrosion expansion process to the contour images includes：Extract the profile diagram
As the contour edge of interior each object；The burr of the contour edge is eliminated, and expands the contour edge, and fills up described
The blank parts of each interior of articles in contour images.
The beneficial effects of the invention are as follows：The situation of prior art is different from, the present invention is after projected image is got, successively
Projected image is carried out to projected image and carries out gray proces, obtains gray level image；From gray level image, contour images are extracted, and it is right
Contour images carry out corrosion expansion process；Dyeing Fuzzy Processing is carried out to the image after corrosion expansion process, finally by profile diagram
Picture and carry out the image after dyeing Fuzzy Processing and carry out fusion treatment obtaining fluoroscopic image, projection module is sent fluoroscopic image,
Projection fluoroscopic image is realized, wherein, fluoroscopic image can make a distinction with ambient light, facilitate user to watch fluoroscopic image；Enter one
Step, be the intensity of illumination of the ambient light of view field when the image after to corrosion expansion process carries out dyeing Fuzzy Processing
Carry out, the intensity of illumination of specially ambient light is stronger, and the degree of Fuzzy Processing is deeper, and image is Fluoresceinated stronger, ambient light
Intensity of illumination is weaker, and the degree of Fuzzy Processing is more shallow, and image is Fluoresceinated weaker so that fluoroscopic image more conforms to project environment
Need.
Brief description of the drawings
Fig. 1 is the schematic diagram of the system embodiment of present invention projection fluoroscopic image；
Fig. 2 is the flow chart of the method embodiment of projector image fluorescence processing of the present invention；
Fig. 3 is the flow chart that gray level image is generated in the method embodiment of projector image fluorescence processing of the present invention；
Fig. 4 is that the method embodiment of projector image fluorescence processing of the present invention to image dye the stream of Fuzzy Processing
Cheng Tu.
Embodiment
The present invention is described in detail with embodiment below in conjunction with the accompanying drawings.
Referring to Fig. 1, the system 20 of projection fluoroscopic image includes projection module 21, optical detection device 22 and processor 23,
Processor 23 is connected with projection module 21 and optical detection device 22 respectively.Optical detection device 22 is used for the throwing for detecting projection module 21
The intensity of illumination of the ambient light in shadow zone domain.The intensity of illumination of ambient light refers to the energy for receiving visible ray in unit area.
In addition to the intensity of illumination of ambient light of view field is directly detected by optical detection device 22, it can also utilize with collection
The lens assembly of function shoots width projection ambient image, then carries out gray proces to the image, by calculating gray level image
The gray value of each pixel draws the intensity of illumination of the ambient light of picture, and the illumination for as projecting ambient light in environment is strong
Degree, certainly, those skilled in the art can also use the intensity of illumination of the ambient light of other methods detection view field, herein not
Repeat one by one again.
Processor 23 is used for：Obtain projected image；Gray proces are carried out to projected image, gray level image are obtained, from gray scale
Image, contour images are extracted, and corrosion expansion process is carried out to contour images, projection module 21 is detected by optical detection device 22
The intensity of illumination of the ambient light of the view field projected, and according to the intensity of illumination of ambient light to corrosion expansion process after
Image carries out dyeing Fuzzy Processing, by contour images and carries out the image after dyeing Fuzzy Processing and carry out fusion treatment obtaining fluorescence
Image, fluoroscopic image is sent to projection module 21, and projection module 21 is projected fluoroscopic image to view field.
What deserves to be explained is：After the contour images that extraction obtains, the copy of contour images can be preserved, wherein, profile diagram
The copy of picture is identical with former contour images, after by contour images and carry out the image after dyeing Fuzzy Processing and carry out fusion treatment tool
Body is：By the copy of contour images and carry out the image after dyeing Fuzzy Processing and carry out fusion treatment.
Gray level image refers to the image for also having the color depth of many levels between black and white, and R, G, B are respectively to throw
The color value of red component, green component, the blue component three of each pixel of shadow image.Each pixel in projected image
Color there are tri- components of R, G, B to determine, and each component has 255 intermediate values can use, and such a pixel can have more than 1600
The excursion of ten thousand (255*255*255) color.And gray level image is a kind of special colour of tri- component identicals of R, G, B
Image, the excursion of one pixel is 255 kinds, and gray proces are i.e. by the color of image by changeable colored excursion
The excursion between B＆W is narrowed down to, then processor 23 carries out gray proces to projected image, obtains the step of gray level image
Suddenly include：The rgb value of the pixel of projected image is obtained, according to the rgb value of the pixel of projected image, calculates gray value, will
The rgb value of the pixel of projected image is replaced into gray value, obtains gray level image, wherein, calculate the meter of the gray value of pixel
Calculating formula is：
Gray=α * R+ β * G+ γ * B
Gray is gray value, and R is the color value of red component in the rgb value of pixel, and G is green in the rgb value of pixel
The color value of colouring component, B are the color value of blue component in the rgb value of pixel, and α is the number more than 0.2 and less than 0.4
Value, β are the numerical value more than 0.5 and less than 0.7, and γ is size 0.1 and the numerical value less than 0.3.Certainly, above-mentioned simply explanation
The method that one of which is preferably converted to projected image gray level image, those skilled in the art can also use other methods
By projected image converting gradation image.
Contour images are the images for referring to embody the profile of each object in projected image, and processor 23 is to contour images
The step of carrying out corrosion expansion process specifically includes the contour edge of each object in extraction contour images；Contour elimination edge
Burr, and expand contour edge, and fill up the space of each interior of articles in contour images.Specifically, in contour elimination
After the burr at edge, expand the profile of each object, be subsequently filled the blank parts of each interior of articles in contour images.Pass through
Above-mentioned processing, map contour image becomes more smooth, so as to reduce the requirement of the detail in contour images.
It is to be carried out according to the intensity of illumination of ambient light, specifically, the illumination of ambient light is strong when carrying out Fuzzy Processing to image
Degree is stronger, and Fuzzy Processing is deeper, and the intensity of illumination of ambient light is weaker, and Fuzzy Processing is more shallow, then processor 23 is according to ambient light
The step of intensity of illumination carries out dyeing Fuzzy Processing to the image after corrosion expansion process includes：To the figure after corrosion expansion process
As carrying out dyeing processing, the matrix template of Gaussian Blur processing is selected according to the intensity of illumination of ambient light, Gaussian Blur processing
There is predetermined positive correlation, by the image after dyeing and selected height between matrix template and the intensity of illumination of ambient light
The matrix template of this Fuzzy Processing carries out convolution algorithm, obtains dyeing the image after Fuzzy Processing.The matrix of Gaussian Blur processing
Between template and the intensity of illumination of ambient light there is predetermined positive correlation to refer to：The intensity of illumination of ambient light is stronger, selected
The matrix template of fixed Gaussian Blur processing is bigger, and the matrix template of Gaussian Blur processing is bigger, then image is obscured
The program of processing is bigger, and the intensity of illumination of ambient light is weaker, and the matrix template for the Gaussian Blur processing selected is smaller, and Gauss
The matrix template of Fuzzy Processing is smaller, then it is smaller to carry out fuzzy program to image；Certainly, the matrix template of Gaussian Blur processing
Size and ambient light intensity of illumination between predetermined positive correlation can be set according to actual conditions.
Further, processor 23 by contour images and is carrying out the image after dyeing Fuzzy Processing and carries out fusion treatment obtaining
It is the prospect using contour images as image into fluoroscopic image, dyes background of the image as image after Fuzzy Processing, wherein,
Image after dyeing Fuzzy Processing is the fuzzy image of a comparison, can be formed and seted off by contrast with contour images, so that fusion
The Fluoresceinated display of image afterwards is more prominent, and what is projected is better.
Certainly, after fluoroscopic image is obtained, before fluoroscopic image is projected, place can also be optimized to fluoroscopic image
Reason, such as：Fluoroscopic image is smoothed, improves quality of fluoroscopic image etc..
In embodiments of the present invention, after projected image is got, projected image progress is carried out to projected image successively
Gray proces, obtain gray level image；From gray level image, contour images are extracted, and corrosion expansion process is carried out to contour images；It is right
Image after corrosion expansion process carries out dyeing Fuzzy Processing, finally by contour images and carries out the image after dyeing Fuzzy Processing
Carry out fusion treatment and obtain fluoroscopic image, projection module is sent fluoroscopic image, realize projection fluoroscopic image, wherein, fluorogram
As that can be made a distinction with ambient light, user is facilitated to watch fluoroscopic image；Further, the image after to corrosion expansion process
It is the intensity of illumination progress of the ambient light of view field, the specially intensity of illumination of ambient light when carrying out dyeing Fuzzy Processing
Stronger, the degree of Fuzzy Processing is deeper, and image is Fluoresceinated stronger, and the intensity of illumination of ambient light is weaker, and the degree of Fuzzy Processing is got over
Shallow, image is Fluoresceinated weaker so that fluoroscopic image more conforms to project the needs of environment.
The present invention provides the method embodiment of projector image fluorescence processing again.Referring to Fig. 2, method includes:
Step S201：Obtain projected image；
Projected image is provided by external equipment, can also extract what is obtained from the memory of internal system.
Step S202：Gray proces are carried out to projected image, obtain gray level image；
Gray level image refers to the image of only two kinds of colors of black and white, and it can allow beholder more intuitively to distinguish figure
As the shape and profile of interior each object.The rgb value of each pixel of projected image includes R values, G values and B values, in projected image
The color of each pixel has tri- color components of R, G, B to determine, and each color component has 255 intermediate values can use, such a picture
Vegetarian refreshments can have the excursion of more than 1,600 ten thousand (255*255*255) color.And gray level image is that tri- components of R, G, B are identical
A kind of special coloured image, the excursion of one pixel is 255 kinds, and gray proces are i.e. by the color of image by more
The colored excursion of change narrows down to the excursion between B＆W.And it is exactly to be thrown to change that projected image is converted into recovery
The rgb value of each pixel in shadow image, projected image is set there was only two kinds of colors of black and white, then as shown in figure 3, step S202 bags
Include：
Step S2021：Obtain the rgb value of the pixel of projected image；
Step S2022：According to the rgb value of the pixel of projected image, gray value is calculated, wherein, calculate the ash of pixel
The calculation formula of angle value is：
Gray=α * R+ β * G+ γ * B
Gray is gray value, and R is the color value of red component in the rgb value of pixel, and G is green in the rgb value of pixel
The color value of colouring component, B are the color value of blue component in the rgb value of pixel, and α is the number more than 0.2 and less than 0.4
Value, β are the numerical value more than 0.5 and less than 0.7, and γ is size 0.1 and the numerical value less than 0.3.
Step S2023：The rgb value of the pixel of projected image is replaced into gray value, obtains gray level image.
Step S203：From gray level image, contour images are extracted, and corrosion expansion process is carried out to contour images；
What deserves to be explained is：After extraction obtains contour images, the copy of contour images is preserved, is subsequently located with facilitating
Reason.
And it is the tool to become apparent from the profile of each object in contour images that contour images, which are carried out corroding expansion process,
The step S203 of body includes：The contour edge of each object in contour images, the burr at contour elimination edge are extracted, and expands wheel
Wide edge, and fill up the gutter of each interior of articles in contour images.After corrosion expansion process being carried out to contour images, figure
As more smooth, so as to reduce some details in image.
Step S204：The intensity of illumination of the ambient light for the view field that detection projection module is projected, and according to environment
The intensity of illumination of light carries out dyeing Fuzzy Processing to the image after corrosion expansion process；
View field refers to projected picture region when projection module is projected.Fuzzy Processing is being carried out to image
When, the intensity of illumination of ambient light is stronger, and Fuzzy Processing is deeper, and the intensity of illumination of ambient light is weaker, and Fuzzy Processing is more shallow, so that glimmering
Light image more conforms to project the needs of environment, then as shown in figure 4, step S204 includes again：
Step S2041：The matrix template of Gaussian Blur processing, Gaussian Blur processing are selected according to the intensity of illumination of ambient light
Matrix template and ambient light intensity of illumination between there is predetermined positive correlation；
Between the matrix template of Gaussian Blur processing and the intensity of illumination of ambient light there is predetermined positive correlation to refer to：
The intensity of illumination of ambient light is stronger, and the matrix template for the Gaussian Blur processing selected is bigger, and the matrix of Gaussian Blur processing
Template is bigger, then bigger to the program of image progress Fuzzy Processing, the intensity of illumination of ambient light is weaker, the Gaussian Blur selected
The matrix template of processing is smaller, and the matrix template of Gaussian Blur processing is smaller, then it is smaller to carry out fuzzy program to image；When
So, the predetermined positive correlation between the size of matrix template and the intensity of illumination of ambient light of Gaussian Blur processing can root
Set according to actual conditions.
Step S2042：Image after dyeing and the matrix template that selected Gaussian Blur is handled are subjected to convolution algorithm,
Obtain dyeing the image after Fuzzy Processing.
Step S205：By contour images and carry out the image after dyeing Fuzzy Processing and carry out fusion treatment obtaining fluorogram
Picture；
By contour images and carry out the image after dyeing Fuzzy Processing carry out fusion treatment obtain referring in fluoroscopic image with
Prospect of the contour images as image, background of the image as image after Fuzzy Processing is dyed, wherein, after dyeing Fuzzy Processing
Image is the fuzzy image of a comparison, can be formed and seted off by contrast with contour images, so that the image after fusion is Fluoresceinated aobvious
Show and more protrude, what is projected is better.
Step S206：Projection module is set to project fluoroscopic image to view field.
Certainly, after fluoroscopic image is obtained, before fluoroscopic image is projected, place can also be optimized to fluoroscopic image
Reason, such as：Fluoroscopic image is smoothed, improves quality of fluoroscopic image etc..
In embodiments of the present invention, after projected image is got, projected image progress is carried out to projected image successively
Gray proces, obtain gray level image；From gray level image, contour images are extracted, and corrosion expansion process is carried out to contour images；It is right
Image after corrosion expansion process carries out dyeing Fuzzy Processing, finally by contour images and carries out the image after dyeing Fuzzy Processing
Carry out fusion treatment and obtain fluoroscopic image, projection module is sent fluoroscopic image, realize projection fluoroscopic image, wherein, fluorogram
As that can be made a distinction with ambient light, user is facilitated to watch fluoroscopic image；Further, the image after to corrosion expansion process
It is the intensity of illumination progress of the ambient light of view field, the specially intensity of illumination of ambient light when carrying out dyeing Fuzzy Processing
Stronger, the degree of Fuzzy Processing is deeper, and image is Fluoresceinated stronger, and the intensity of illumination of ambient light is weaker, and the degree of Fuzzy Processing is got over
Shallow, image is Fluoresceinated weaker so that fluoroscopic image more conforms to project the needs of environment.
Embodiments of the present invention are the foregoing is only, are not intended to limit the scope of the invention, it is every to utilize this
The equivalent structure or equivalent flow conversion that description of the invention and accompanying drawing content are made, or directly or indirectly it is used in other correlations
Technical field, it is included within the scope of the present invention.
Claims (10)
- A kind of 1. method of projector image fluorescence processing, it is characterised in that including：Obtain projected image；Gray proces are carried out to the projected image, obtain gray level image；From the gray level image, contour images are extracted, and corrosion expansion process is carried out to the contour images；The intensity of illumination of the ambient light for the view field that projection module is projected is detected by optical detection device, and according to described The intensity of illumination of ambient light carries out dyeing Fuzzy Processing to the image after corrosion expansion process；By the contour images and carry out the image after dyeing Fuzzy Processing and carry out fusion treatment obtaining fluoroscopic image；The projection module is set to project the fluoroscopic image to the view field.
- 2. according to the method for claim 1, it is characterised in thatThe step of carrying out gray proces to the projected image, obtaining gray level image includes：Obtain the rgb value of the pixel of the projected image；According to the rgb value of the pixel of the projected image, gray value is calculated；The rgb value of the pixel of the projected image is replaced into the gray value, obtains the gray level image.
- 3. according to the method for claim 2, it is characterised in thatAccording to the rgb value of the pixel, the calculation formula for calculating the gray value of the pixel is：Gray=α * R+ β * G+ γ * BThe Gray is gray value, and the R is the color value of red component in the rgb value of the pixel, and the G is the picture The color value of the rgb value Green component of vegetarian refreshments, the B be the pixel rgb value in blue component color can on, institute It is the numerical value more than 0.2 and less than 0.4 to state α, and the β is the numerical value more than 0.5 and less than 0.7, and the γ is size 0.1 And the numerical value less than 0.3.
- 4. according to the method for claim 1, it is characterised in thatThe step of intensity of illumination according to the ambient light carries out dyeing Fuzzy Processing to the image after corrosion expansion process Including：Dyeing processing is first carried out to the image after the corrosion expansion process；The matrix template of Gaussian Blur processing, the matrix of the Gaussian Blur processing are selected according to the intensity of illumination of the ambient light There is predetermined positive correlation between template and the intensity of illumination of ambient light；Image after the dyeing and the matrix template that selected Gaussian Blur is handled are subjected to convolution algorithm, obtain the dye Image after color blurring processing.
- 5. according to the method for claim 1, it is characterised in thatDescribed the step of carrying out corrosion expansion process to the contour images, includes：Extract the contour edge of each object in the contour images；The burr of the contour edge is eliminated, and expands the contour edge, and fills up each object in the contour images Internal blank parts.
- 6. a kind of system for projecting fluoroscopic image, including projection module, optical detection device and processor, the processor respectively with Projection module connects with optical detection device；The processor is used for：Obtain projected image；Gray proces are carried out to the projected image, obtain gray level image；From the gray level image, contour images are extracted, and corrosion expansion process is carried out to the contour images；The intensity of illumination of the ambient light for the view field that the projection module is projected is detected by the optical detection device, and Dyeing Fuzzy Processing is carried out to the image after corrosion expansion process according to the intensity of illumination of the ambient light；By the contour images and carry out the image after dyeing Fuzzy Processing and carry out fusion treatment obtaining fluoroscopic image；The fluoroscopic image is sent to the projection module, and the projection module is projected the fluorescence to the view field Image.
- 7. system according to claim 6, it is characterised in thatThe processor carries out gray proces to the projected image, and the step of obtaining gray level image includes：Obtain the rgb value of the pixel of the projected image；According to the rgb value of the pixel of the projected image, gray value is calculated；The rgb value of the pixel of the projected image is replaced into the gray value, obtains the gray level image.
- 8. system according to claim 7, it is characterised in thatAccording to the rgb value of the pixel, the calculation formula for calculating the gray value of the pixel is：Gray=α * R+ β * G+ γ * BThe Gray is gray value, and the R is the color value of red component in the rgb value of the pixel, and the G is the picture The color value of the rgb value Green component of vegetarian refreshments, the B be the pixel rgb value in blue component color value, it is described α be more than 0.2 and less than 0.4 numerical value, the β be more than 0.5 and less than 0.7 numerical value, the γ be size 0.1 simultaneously And the numerical value less than 0.3.
- 9. system according to claim 6, it is characterised in thatThe processor carries out dyeing Fuzzy Processing according to the intensity of illumination of the ambient light to the image after corrosion expansion process The step of include：Dyeing processing is carried out to the image after the corrosion expansion process；The matrix template of Gaussian Blur processing, the matrix of the Gaussian Blur processing are selected according to the intensity of illumination of the ambient light There is predetermined positive correlation between template and the intensity of illumination of ambient light；Image after the dyeing and the matrix template that selected Gaussian Blur is handled are subjected to convolution algorithm, obtain the dye Image after color blurring processing.
- 10. system according to claim 6, it is characterised in thatThe step of processor carries out corrosion expansion process to the contour images includes：Extract the contour edge of each object in the contour images；The burr of the contour edge is eliminated, and expands the contour edge, and fills up each object in the contour images Internal blank parts.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510810937.XA CN105472361B (en) | 2015-11-19 | 2015-11-19 | A kind of method and system of projector image fluorescence processing |
| PCT/CN2016/093404 WO2017084391A1 (en) | 2015-11-19 | 2016-08-05 | Method and system for performing fluorescence processing on an image of a projector |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510810937.XA CN105472361B (en) | 2015-11-19 | 2015-11-19 | A kind of method and system of projector image fluorescence processing |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105472361A CN105472361A (en) | 2016-04-06 |
| CN105472361B true CN105472361B (en) | 2018-03-27 |
Family
ID=55609583
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510810937.XA Active CN105472361B (en) | 2015-11-19 | 2015-11-19 | A kind of method and system of projector image fluorescence processing |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN105472361B (en) |
| WO (1) | WO2017084391A1 (en) |
Families Citing this family (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105472361B (en) * | 2015-11-19 | 2018-03-27 | 广景视睿科技（深圳）有限公司 | A kind of method and system of projector image fluorescence processing |
| CN108174170B (en) * | 2017-12-29 | 2020-03-17 | 安徽慧视金瞳科技有限公司 | Camera-based projection area size self-detection method, system and equipment |
| CN109410236B (en) * | 2018-06-12 | 2021-11-30 | 佛山市顺德区中山大学研究院 | Method and system for identifying and redefining reflecting points of fluorescence staining images |
| CN110689926A (en) * | 2018-06-19 | 2020-01-14 | 上海交通大学 | Accurate detection method for high-throughput digital PCR image droplets |
| CN110909747B (en) * | 2019-05-13 | 2023-04-07 | 河南理工大学 | Coal gangue identification method based on multi-color space principal component analysis description |
| CN111489322B (en) * | 2020-04-09 | 2023-05-26 | 广州光锥元信息科技有限公司 | Method and device for adding sky filter to static picture |
Family Cites Families (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP3719411B2 (en) * | 2001-05-31 | 2005-11-24 | セイコーエプソン株式会社 | Image display system, projector, program, information storage medium, and image processing method |
| JP2007166271A (en) * | 2005-12-14 | 2007-06-28 | Seiko Epson Corp | Projection system and projector |
| JP2007281893A (en) * | 2006-04-06 | 2007-10-25 | Olympus Corp | Projector system |
| KR100866486B1 (en) * | 2007-01-04 | 2008-11-03 | 삼성전자주식회사 | Ambient light adaptive color correction method and device for projector |
| CN101860761B (en) * | 2010-04-16 | 2012-09-05 | 浙江大学 | Correction method of color distortion of projected display images |
| CN101917631B (en) * | 2010-07-30 | 2012-04-25 | 浙江大学 | Projection display color reproduction method under normal lighting environment |
| JP6176114B2 (en) * | 2011-09-15 | 2017-08-09 | 日本電気株式会社 | Projected image automatic correction system, projected image automatic correction method and program |
| TWI504263B (en) * | 2013-03-22 | 2015-10-11 | Delta Electronics Inc | Projection sysyem, projector, and calibration method thereof |
| CN103729829A (en) * | 2013-12-13 | 2014-04-16 | 深圳市云宙多媒体技术有限公司 | Rendering method and device for color image line drawing |
| CN103942813A (en) * | 2014-03-21 | 2014-07-23 | 杭州电子科技大学 | Single-moving-object real-time detection method in electric wheelchair movement process |
| CN104063848B (en) * | 2014-06-19 | 2017-09-19 | 中安消技术有限公司 | A kind of enhancement method of low-illumination image and device |
| CN104463858A (en) * | 2014-11-28 | 2015-03-25 | 中国航空无线电电子研究所 | Projection color self-adaption correction method |
| CN105472361B (en) * | 2015-11-19 | 2018-03-27 | 广景视睿科技（深圳）有限公司 | A kind of method and system of projector image fluorescence processing |
-
2015
- 2015-11-19 CN CN201510810937.XA patent/CN105472361B/en active Active
-
2016
- 2016-08-05 WO PCT/CN2016/093404 patent/WO2017084391A1/en active Application Filing
Also Published As
| Publication number | Publication date |
|---|---|
| WO2017084391A1 (en) | 2017-05-26 |
| CN105472361A (en) | 2016-04-06 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105472361B (en) | A kind of method and system of projector image fluorescence processing | |
| CN103927741B (en) | SAR image synthesis method for enhancing target characteristics | |
| CN104717432B (en) | Handle method, image processing equipment and the digital camera of one group of input picture | |
| CN101264007B (en) | Eyelid detection apparatus and program therefor | |
| CN103310422B (en) | Obtain the method and device of image | |
| CN102314602B (en) | Shadow removal in image captured by vehicle-based camera using optimized oriented linear axis | |
| CN102547063A (en) | Natural sense color fusion method based on color contrast enhancement | |
| CN105103187A (en) | Multi-spectral imaging system for shadow detection and attenuation | |
| CN103914699A (en) | Automatic lip gloss image enhancement method based on color space | |
| US10817723B2 (en) | Image recognition system and information-display method thereof | |
| CN103034983B (en) | A kind of defogging method capable based on anisotropic filtering | |
| CN106157286A (en) | Image processing method and screen light leak test method | |
| CN106355744B (en) | A kind of recognition methods of Indonesian Rupiah value of money and device | |
| CN106096601A (en) | The method and system of character types in a kind of automatic detection bill | |
| CN105184748A (en) | Image bit depth enhancing method | |
| CN106503644A (en) | Glasses attribute detection method based on edge projection and color characteristic | |
| CN109905700A (en) | Virtual display device and its detection method, device, computer readable storage medium | |
| CN108520260B (en) | Method for identifying visible foreign matters in bottled oral liquid | |
| CN101937505B (en) | Target detection method and equipment and used image acquisition device thereof | |
| CN105869115A (en) | Depth image super-resolution method based on kinect2.0 | |
| CN109410161A (en) | A kind of fusion method of the infrared polarization image separated based on YUV and multiple features | |
| CN105919543A (en) | Multispectral endoscope imaging image acquisition method and system | |
| CN106360941A (en) | Method for locating fingernails and manicure equipment | |
| CN101872421A (en) | Colorimetry color feature vector automatic extracting method based on machine vision | |
| CN101873506B (en) | Image processing method for providing depth information and image processing system thereof |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| PP01 | Preservation of patent right |
Effective date of registration: 20231226 Granted publication date: 20180327 |
|
| PP01 | Preservation of patent right |